Essays on Mispricing in the Chinese Stock Market 302

MO ZHANG EKONOMI OCH SAMHÄLLE EKONOMI SOCIETY AND ECONOMICS ON MISPRICING ESSAYS STOCK IN THE CHINESE MARKET

MO ZHANG – ESSAYS ON MISPRICING IN THE CHINESE STOCK MARKET 302 ------

00101 HELSINKI, FINLAND TEL +358 (0)9 431 331. +358 (0)9 431 FAX 33 333 VAASA BOX 287 16, P.O. KIRJASTONKATU FINLAND 65101 VAASA, TEL +358 (0)6 3533 700. +358 (0)6 3533 703 FAX [email protected] HANKEN.FI/DHANKEN HANKEN SCHOOL OF ECONOMICS HELSINKI BOX 479 22, P.O. ARKADIANKATU show thatstate-controlled industries tend to be underesti mated when more, mispricing negative, is but to be over valued less, when mispricing positive. is efficient market theory. The second essay uses this phe nomenon as a natural experiment to test whether a new reform namely policy, granting permission for short selling, When market. stock Chinese ofbenefits efficiency the the the Chinese government lift the ban on short selling the in significantly, decreases mispricing market, stock Chinese even thoughthe volume of short selling the in Chinese stock market trivial is relative to total trading volume. Instead of studying a particular set of stocks, the third essay focuses mar general the at mechanism formation mispricing the on level. ket The market results show that both the resale op tion and inflationillusion hypotheses canexplain the level of market mispricing. Only heterogeneous investors’ beliefs affect the volatility of market mispricing, line in with the re sale option hypothesis prediction. the Additionally, results - - - 0424-7256 978-952-232-315-6 (printed) 978-952-232-316-3 (PDF) 0424-7256 (printed) 2242-699X (PDF) -L Along with Chinese economic development, the Chi single-authored essays. The first two analyzea special stock Chinese the B-share in called discounts phenomenon, market, seeking to explain why this phenomenon exists from the perspective of exchange risk. It shows that dual- class stock price disparity the in Chinese stock market can exchange by be explained, risk, meaning a way, in that “to some extent, investors are rational and ask for compensa line in with is This thetion classical for taking extra risks”. emerging markets, with huge volatility, big boom and bust cycles, driven fast-trading by individual investors, and the to Owing government. the from heavy involvement peculiarity of the Chinese economic and political system, there are some unique structures within the Chinese stock market. In one sense, this makes the Chinese stock market three comprises dissertation This laboratory. interesting an ESSAYS ON MISPRICING IN THE CHINESE STOCK MARKET CHINESE STOCK IN THE MISPRICING ON ESSAYS nese stock and now the is market sec growing is rapidly, ond largest stock market the despite in world. However, theits size, Chinese stock market trades the like wildest MO ZHANG ISSN ISSN ISSN HELSINKI JUVENES PRINT, ISBN ISBN Ekonomi och samhälle Economics and Society

Skrifter utgivna vid Svenska handelshögskolan Publications of the Hanken School of Economics

No 302

Mo Zhang

Essays on Mispricing in the Chinese Stock Market

Helsinki 2016

Essays on Mispricing in the Chinese Stock Market

Key words: Asset pricing, Mispricing, Chinese stock market, Behavioral finance, Heterogeneous beliefs

Mo Zhang Hanken School of Economics Department of Finance and Statistics P.O.Box 287, 65101 Vaasa, Finland

Hanken School of Economics

ISBN 978-952-232-315-6 (printed) ISBN 978-952-232-316-3 (PDF) ISSN-L 0424-7256 ISSN 0424-7256 (printed) ISSN 2242-699X (PDF)

Juvenes Print – Suomen Yliopistopaino Oy, Tampere 2016 i

PREFACE

It is an unbelievable and amazing venture. I am extremely grateful to my supervisor, Professor Johan Knif for his support, knowledge and guidance. Thanks for taking me in and trusting me through the whole process. I would like to thank Professor Kenneth Högholm for his valuable advice and direction.

I am indebted to Professor Timo Korkeamäki and Anders Löflund for their support when I worked in Helsinki campus. I would like to thank Professor Benjamin Maury for giving me the opportunity to assist in his courses. I enjoy the time to work with great fellow students and Professors at the Department, Abu Shaker, Agniezka Jach, David Gonzalez, Dennis Sundvik, Fredrik Huhtamäki, Gonul Colak, Hilal Butt, Jan Antell, Jesper Haga, John Petterson, Magnus Blomkvist, Nasib Nabulsi, Paulo Maio, Peng Wang, Peter Nyberg, Salla Pöyry, Sergey Osmekhin, Syed Mujahid Hussain, Yamin Xie, Zhamilya Assilbekova and many others.

I would like to thank the external examiners, Professor George Athanassakos and Professor Seppo Pynnönen. Their valuable comments help me improve this dissertation greatly.

I am very grateful with the department of finance and statistics in Hanken, the Hanken Foundation and the WCEFIR fund for providing financial support during my PhD study.

I want to thank Mikko Leppämäki, the graduate School of Finance (GSF), and the Nordic Finance Network (NFN) for the well-structured courses and good seminars.

Thanks to my parents, Ping Zhang and Yi Cao, for putting faith in me and giving me unconditional love. Your love is one of the most precious gifts in my life.

I am especially grateful to my boyfriend Yi Wang for standing with me and being through those ups and downs.

Finally, thanks to myself for being me.

August 1, 2016 Mo Zhang

iii

CONTENTS

1 INTRODUCTION...... 1 1.1 Regime shifts in the Chinese stock market ...... 2 1.1.1 Establishment and infancy period of the Chinese stock market ...... 2 1.1.2 Lift of market segmentation ...... 3 1.1.3 Split-share structure reform ...... 5 1.1.4 Life of short-selling ban ...... 5 1.2 Efficient market hypothesis vs. behavioral finance theory ...... 6 1.2.1 Efficient market hypothesis ...... 6 1.2.2Behavioral finance theory ...... 7

2 SUMMARIES OF ESSAYS ...... 12 2.1 Understanding B-share discounts: Exchange risk in the Chinese stock market ...... 12 2.2 Impact of short selling on B-share discounts in the Chinese stock market ...... 14 2.3 An analysis of Chinese stock market mispricing ...... 15

3 CONCLUDING REMARKS ...... 16

THE ESSAYS

1. Zhang, M. (2013). Understanding B-share discounts: Exchange risk in the Chinese stock market. Manuscript, Hanken School of Economics.

2. Zhang, M. (2015). Impact of short selling on B-share discounts in the Chinese stock market. Manuscript, Hanken School of Economics.

3. Zhang, M. (2015). An analysis of Chinese stock market mispricing. Manuscript, Hanken School of Economics.

Part I Background, Theory and Main Findings

1 INTRODUCTION

Along with Chinese economic development, the Chinese stock market is growing rapidly, and is now the second largest stock market in the world.1 However, despite its size, the Chinese stock market trades like the wildest emerging markets, with huge volatility, big boom and bust cycles, driven by fast-trading individual investors, and heavy involvement from the government. The modern Chinese stock market is young by global standards, with trading resuming 25 years ago after being interrupted for decades by the Communist revolution (from 1950). Owing to the peculiarity of the Chinese economic and political system, there are some unique structures within the Chinese stock market. In one sense, this makes the Chinese stock market an interesting laboratory. This dissertation comprises three single-authored essays. The first two analyze a special phenomenon, called B-share discounts in the Chinese stock market, seeking to explain why this phenomenon exists from the perspective of exchange risk. The second essay uses this phenomenon as a natural experiment to test whether a new reform policy, namely granting permission for short selling, benefits the efficiency of the Chinese stock market. Instead of studying a particular set of stocks, the third essay focuses on the mispricing formation mechanism at the general market level. The Chinese stock market has carried out a series of reforms during the 2000s. As a result, the market structures and policies have changed a great deal, noticeably affecting market participants’ behaviors. Therefore, the next section describes the special features and regime shifts within the Chinese stock market. Then, the author examines the theoretical difference between efficient market hypothesis and behavioral finance. Of the two, the features of the Chinese stock market more closely satisfy the assumptions of behavioral financial theory and, thus, the author focuses more on this theory here. The concluding section discusses the main contents of all three essays, including the contributions and implications of their results.

1 The market capitalization of the Shanghai Stock Exchange and the Shenzhen Stock Exchange are counted together. Data source: Bloomberg.

1.1 Regime shifts in the Chinese stock market

This section smmaries the eveopment path of the hinese stock market, expainin the nie characteristics of the market an h the are sef for testin prposes.

1.1.1 Establishment and infancy period of the Chinese stock market

nike the natra eveopment of estern stock markets, the hinese stock market as initia e an promote b the hinese overnment itsef. t as impemente hen the overnment, stateone enterprises, an banks ere in reat financia iffict in the s. The oriina intention behin the eveopment of a stock market in hina rin the s as to eepen economic restrctrin an to shift from the panne econom toars a market econom. efore the s, the on access to financia capita in hina as provie b commercia banks. oever, the hinese commercia banks ere compete stateone. onseent, on are, stateone enterprises ere abe to secre oans easi oin to nonconitiona overnment spport an the ack of an competition. This as in spite of the fact that these enterprises sa ha the oest proctivit an ere in a poor operationa sitation at the time. hen these enterprises encontere operationa probems an faie to pa back the bank oans, the risks ere a centraie in the bankin sstem. ecase the commercia banks ere a stateone, these risks essentia became a nationa financia risk. Ths, at the time, the extreme heav financia bren on the hinese overnment became a pressin concern for a hinese peope. To provie a ne financia channe for enterprises an to iversif the risks in the bankin sstem, the hanhai tock xchane came into existence on ecember , . bseent, the henhen tock xchane as estabishe on , . in to strinent contros on capita acconts b the hinese athorities, the hinese stock market as not open to forein investors at its inception. oever, some enterprises ha rent emans for forein capita. t the same time, there ere not enoh forein exchane reserves accessibe to sch enterprises. Ths, b the en of , both stock exchanes bean to ao some enterprises to isse acass shares, name shares, hich ere on avaiabe to hinese investors, an shares, hich ere on avaiabe to forein investors. The shares in the are trae in .. oars , hie those in the are ote in on on oars . n this a, the markets ere compete semente beteen forein investors an hinese investors beteen

an . hoers of shares have the same rihts an obiations as hoers of shares. oever, in orer to maintain corporate contro, retai investors are on allowed to hold a maximum of 25% of a firm’s Bshares. n aition, the tota forein onership of a firm cannot be reater than . This nie strctre reste in a ne phenomenon share iscont. shares are trae at reat isconts in comparison ith the corresponin shares. This nie phenomenon is the focs of the first an secon essas in this octora issertation. xcin the separation of forein investors from hinese investors, the shares isse b an enterprise are ivie into stateone shares, corporate shares, an inivia shares. tateone an corporate shares ere not exchaneabe nti ne , an accont for tothirs of a shares iste on the hinese stock market. n inivia shares are exchaneabe b orinar investors. This arranement aeviates concerns abot fnamenta variations in stock prices for the iste companies or main sharehoers, bt aso prevents merers an acisitions throh share train. n essence, it jeopardizes small and medium investors’ interests and impedes the improvement of corporate overnance. The existence of nontraabe shares aso cases a shortae of asset foats, hich makes it more ike that frenie investors can psh p the stock price an increase market voatiit. Therefore, the hinese stock market has natra acire severa sfnctiona eements becase of its artificia esine strctre.

1.1.2 Lift of market segmentation

ompare ith the share market, the iiit in the share market is mch oer, makin it ver iffict for instittiona investors to make sieabe investments. n orer to vitaie the share market, on ebrar , , the hina ecrities eator ommission aoe omestic investors to prchase shares, ner certain conitions. hinese investors ho have forein crrenc eposit acconts in a omestic commercia bank are permitte to trae shares. The share market as cose brief for a eek after this annoncement, resmin train on ebrar , . oth the prices an trnovers of a shares sre for severa eeks. ince then, share isconts have ecrease sinificant, bt have not isappeare. bseent to the openin of the share market to omestic investors, on ovember , , the annonce the aifie orein nstittiona nvestors scheme. This frther opene the oor of the hinese share market to forein

investors ith lienses loal institutional investors an u hinese uan denominated assets diretl inludin shares onds and mutual funds sujet to an overall uota limit of 2 illion n 2 the uota limit was extended to illion ive ears later in 22 it was extended to illion and then to 5 illion in 2 he sheme was supplemented in 2 the enmini ualified orein nstitutional nvestor proram his proram permitted the on on susidiaries of ualified hinese fund manaement and seurities ompanies to rele offshore enmini deposits inludin shares into China’s domestic capital market. he sheme has sine een extended to allow other on onased finanial institutions and finanial firms in ondon aris and inapore diret aess to hinese domesti seurities and funds he overall uota limit urrentl stands at illion 5 illion B the end of eptemer 25 the hinese reulator had alloated uotas of illion and 5 illion illion for the and shemes respetivel 2 The recent liberalization of China’s capital controls took the form of rapidl expandin the and uota limits and raisin the forein ownership limit to % Then, in order to satisfy domestic investors’ demand for investing in foreign seurities marets similarl to the sheme the launhed the ualified omesti nstitutional nvestor sheme on pril 2 his was a transitional arranement that provided limited opportunities for domesti institutional investors to aess forein marets at a stae when the enmini was neither ompletel freel traded nor floated s an invest in loal finanial marets via ertain asset manaement institutions approved the nitiall investments were limited to fixedinome and mone maret produts ine a 2 storelated produts have een allowed to e purhased ut the net value invested in stos must e less than 5% of the overall portfolio n pril 2 the reulation was loosened further still n areement etween the hina Banin eulator ommission and the eurities and xhane ommission made it possile for hinese individuals to invest in the sto maret he uota assined to shemes has een illion sine the end of toer 25 ine 2 the hinese sto maret has een aeleratin its maretoriented proesses and is raduall eomin interated into the loal finanial marets

2 ata soure tate dministration of orein xhane ata soure tate dministration of orein xhane

1.1.3 Split-share structure reform

s mentioned in ection .., the eistence of a large volme of nontradable state oned and legal person shares pts pblic investors in an inferior position relative to the actal controllers in terms of making corporate policies and the disposal of firms’ profits and assets. n order to solve this problem and to protect the interests of investors, especially pblic investors, on pril , , the CC annonced the lanch of a split share strctre reform to convert all nontradable shares into pblically tradable shares. The reform plans can be classified into five categories share compensation mostly, nontradable shareholders present shares to the tradable shareholders and, sometimes, listed companies make the compensation a reverse stock split non tradable shareholders contract their share according to some ratio cash compensation nontradable shareholders compensate tradable shareholders ith cash arrants nontradable shareholders isse arrants to tradable shareholders and asset restrctring maor nontradable shareholders perform some asset restrctring ith the listed company. ntil ecember , , of companies’ stocks listed in the and the had already realized fll circlation. The Chinese capital market has made significant progress in terms of the splitshare strctre reform, improvement of the ality of listed companies, comprehensive management of secrities firms, development and groth of instittional investors, and improvement of legal systems. fter the introdction of the splitshare strctre reform, a distribtion management system cold better constrain prices on the stock market and investors.

1.1.4 Life of short-selling ban

The Chinese stock market has no history of short selling. oever, to deepen the reform frther and to complete the financial market mechanism, on arch , , the CC introdced short selling and margin trading on a trial basis. The and alloed the top brokerage firms in China to by eligible stocks at a margin andor to short sell those stocks according to detailed implementation rles. nly stocks in the nde on the hanghai stock echange and the Component nde on the henzhen stock echange ere designated by the CC as eligible for short selling and

ata sorce http.ftchinese.comstoryflly

margin trading s of erar there are stocks and s eligile for short selling and margin trading in the to maor echanges in mainland hina

1.2 Efficient market hypothesis vs. behavioral finance theory

his section riefl discsses the theoretical fondation of this dissertation comparing the theoretical difference eteen the market efficienc hpothesis and ehaioral finance

1.2.1 Efficient market hypothesis

he efficient market hpothesis is the proposition that asset prices fll reflect all plicl aailale information on the ftre performance of firms ama rice changes are random and npredictale and onl affected ne nepected information epending on hat information sets are reflected in the stock prices market efficienc has three ariants a eak form in hich the information set comprises historical prices a semistrong form in hich the information set is oios plicl aailale information and a strong form in hich the information set is an information releant to price formation ama f the is alid then it is impossile for inestors to either prchase nderaled stocks or sell stocks at inflated prices n this sense ecept for taking etra risks one cannot eat the oerall market throgh stock selection or market timing The EMH relates closely to the “rational expectation” property introduced by Muth hich is ery important for deriving equilibrium asset prices satisfying Fama’s definition of market efficienc ational epectation is defined as the est gess of the ftre ased on all crrentl aailale information hs all market participants ill hae the identical epectation and conseentl the market achiees eilirim here are no sstematic errors hen predicting ftre prices he as sed in the intertemporal capital asset pricing model erton and as reired to generate eilirim asset prices cas hese models can e taken as the strong form of market efficienc oeer in a real econom these assmptions are difficlt to satisf oss deeloped the aritrage pricing theor to loosen the nrealistic assmption in the models of th and cas oss arged that een if there ere

mispriced assets in the maret active arbitrageurs ould naturally drive the price to the equilibrium price using costless short selling or margin trading n the s the EMH as advocated strongly in academic circles t that time much empirical evidence as presented in support of the EMH For example active investments such as mutual funds investment analysts and technical analyses do not consistently beat the maret Fama lume evy a b ensen ensen ennington nticipated announcements do not appear to affect stoc prices Fama et al

1.2.2 Behavioral finance theory

ith rational expectation traditional financial models based on the EMH are “appealingly simple” but “basic facts about the aggregate stock market, the crosssection of average returns and individual trading behavior are not easily understood in this framework” arberis Thaler From the s contrary to the EMH a series of anomalies ere discovered in empirical studies such as the momentum effect egadeesh Titman the anuary effect and the dayoftheee effect iegel ompared to the financial anomalies the evidence on excess volatility seems to be more troubling for the EMH hiller Therefore many academic researchers have taen a broader social science perspective to interpret financial marets shifting aay from these econometric analyses of time series based on prices dividends and earnings toard the psychology of investors and their behavior s the number of studies in this field increased they gradually formed the systematic behavioral finance theory This theory is based on the assumption that investors or at least a significant minority of them are subect to behavioral biases hich means they do not behave in a rational manner Thus behavioral finance theory applies cognitive psychology studies in a financial context The rest of this section first summaries the commonly observed psychological biases in financial marets and then discusses the foundation of behavioral finance limits of arbitrage 1) Investors’ psychological biases There are some psychological biases idely documented by empirical studies hich challenge both the ris aversion and the rational expectation assumptions These biases typically originate from cognitive psychology literature and are then utilied in a financial context

 verconience sychology stuies show that people ten to oerestimate their ability an the accuracy of their knowlege in some circumstances, especially when ealuating uncertain tasks lpert aiffa, ichtenstein, ischhoff hillips, urthermore, it is not ust orinary iniiuals who isplay such tenencies eperts isplay oerconfience as well amerer oallo, ther researchers, such as yle an ang , aniel, irshleifer an ubrahmanyam , an ean a hae stuie the implications of oerconfience on financial markets

 epresentativeness ersky an ahneman suggest that when face with uncertainty, people are likely to make ugments using a representatieness heuristic oweer, they ten to forecast by fining the closest match to past patterns, without assessing the probability of matching the pattern n financial markets, inestors ten to simply classify the stock price as ramatic an persistent price trens, instea of thinking how rarely these categories occur in funamental unerlying factors onseuently, representatieness may lea to feeback ynamics hiller,

 onservatis hen face with any new information, people are prone to stick to prior beliefs his can eplain why inestors are unable to instantly an fully react to an earnings surprise, known as the “postearningsannouncement rift,” which was first ientifie by all an Brown (1968). The “postearningsannouncement drift” phenomenon works as follows een after earnings announcements, estimate cumulatie abnormal returns continue to rift upwars for “good news” companies and to drift downwars for “bad news” companies

 vailability bias nestors cling to an oerestimate the probability of recently obsere or eperience eents because of the freshness of the eent in their memory ersky ahneman, his bias can cause an oerreaction in financial markets nestors preictably oerreact to new information, creating a largerthanappropriate effect on an asset’s price. However, this tren is not permanent

 nchoring “In many situations, people make estimates by starting from an initial value that is auste to yiel the final answer” ersky ahneman, nestment anchoring states that inestors base their ecisions on irreleant figures an statistics or eample, inestors may purchase stocks, the prices of which fall significantly in a ery short term

simply because they believe that the stock is selling at a discount compared with its historically “high” price.

 ental acconting ental accounting refers to the tendency for investors to allocate their money to separate mental compartments based on a variety of subective criteria, but to ignore fungibility and correlation effects. or eample, people save for a special purpose, such as a vacation or to purchase a house, but, at the same time, they still carry substantial credit card debt. They treat the special savings differently from the money used to pay back their debts, even though interest payments on credit card debts decrease their net worth. rational way to behave in this particular situation would be to use the savings in a ar instead of taking on new credit card debt, with its high interest. nother version of mental accounting is that people treat money differently depending on its source. or instance, people are prone to spend more “found” money, such as bonuses and tax returns, relative to a similar amount of normally epected money, such as a monthly salary. rational person understands that no matter where the money comes from, spending it will decrease his or her overall wealth.

 egret aversion ahneman and Tversky (199) propose a prospect theory, which states that people are far more upset by losses than they are pleased by similar gains. Thus, they would rather take etra risks to echange the slim chance of avoiding losses. The phenomenon reflecting this bias is that investors usually sell winning stocks too soon, but keep losing stocks for too long (dean, 1998b). he liits o arbitrage The discussion above lists the psychological biases that cause investors’ irrational activities in the first place, and states the possibility that they may cause some mispricing. However, as the H assumes, there is always smart money (fully rational) in the market, ready to correct the mispricing caused by noise traders. How then can mispricing systemically eist in the market In order to offer a possible eplanation for this anomaly, this section discusses the key argument in behavioral finance, namely the limits of arbitrage. Because of these limits, smart money cannot drive the mispriced assets down to their fundamental value. ccording to the T (oss, 196), the H holds that if noise traders (irrational investors) cause mispricing, the arbitrageurs (rational investors) will spot this opportunity and immediately correct the price, conditional on riskless and costless arbitrage and unlimited financing. However, in the real world, arbitrage is very costly and risky, not only financially, but also psychologically. The failure to eliminate an

obvious and straightforard mispricing situation proves the limitation of arbitrage. ellnon example is that the maret value of alm a spunout subsidiary of om exceeded that of its parent company om, hich retained a maority stae in the spinout amont haler, . irstly, arbitrage is financially costly arberis haler, . f arbitrageurs cannot find a fair substitute for the mispriced asset, then they are unable to avoid the large fundamental ris by effectively hedging their position in the mispriced asset from adverse changes in the fundamental. ven if a close substitute is available, arbitrageurs are still threatened by noise trader ris. ince noise traders may be more frenied than arbitrageurs expect, arbitrageurs have to bear the ris that hen they liuidate their position, stocs ould be even more mispriced than they are today. f future mispricing is more extreme than that hen the arbitrageurs start building their positions, then they ould suffer severe losses. bviously, arbitrageurs ould expose themselves to noise trader ris only if they have a finite horion. f their arbitrage horion is infinite, they may not liuidate their positions until the mispricing is diminished. oever, in most cases, arbitrageurs have short horions hleifer ishny, . rbitrageurs are usually financial institutions, such as hedge funds and mutual funds. n order to attract more investors, most funds use the openend form, hich gives investors the right to ithdra their funds on demand tein, . hleifer and ishny point out that the openend nature of most professional arbitrage firms maes it difficult for these firms to correct aggregate mispricing. ther issues inducing high costs may prevent smart money from arbitraging, especially in short selling. he folloing example is given by ones and amont . heeling ae rie ailroad, on the last trading day of anuary , had a rebate rate of , meaning that one needed to pay cents as a daily fee per day to maintain a short position. t one point during ebruary , the daily fee climbed to an incredible per day. his extremely high daily fee eliminated all possibility of arbitrage. n addition, in many emerging marets, short selling is banned by governments. ven in the .. euity marets, selling short is not easy. ccording to amont , “regulations and procedures administered by the , the ederal eserve, the various stoc exchanges, underriters, and individual broerage firms can mechanically impede short selling.” hus, most mutual funds are long only. n addition to the financial costs, the psychological cost maes arbitrage even more demanding. ost investors, even some extremely smart investors, are reluctant to engage in short selling, because short sellers usually have a bad reputation for causing

. . . . managers’ inability, they attribute this loss to bad luck. In this sense, professionals prefer . arbitrageurs’ . . . . . . . . . . . . . . Miller’s model to dynamic setting. A risky asset’s price will be even higher than the most optimistic investor’s assessment of their fundamental value. Investors expect to resell . .

his doctoral thesis, Essays on Mispricing in the Chinese Stock Market, includes three singleauthored essays. his section provides a brief overview of the three essays.

nerstaning share isconts change ris in the hinese stoc aret

ther than their currency denominations, A and shares have the same rights and obligations, but different prices. share discounts existing in the hinese stock market clearly violate the law of one price. Most previous studies explain share discounts by different risk levels, information asymmetry, or market liuidity, but few discuss the impact of exchange risks. According to Adler and umas , and olnik , asset trading in a country with prices uoted in a particular currency has an exchange risk associated with random domestic currency movements. he reason why researchers have not investigated the effect of exchange risk on share discounts is that, before uly , hina adopted defacto fixed exchange rate system, under which the exchange rate was pegged to the .. dollar and was heavily regulated by the hinese government. At the same time, until now, the ong ong dollar has been being pegged to the . herefore, there is no exchange risk when investors convert hinese yuan dividends into or in order to evaluate stock prices. In the same situation, but with a fixed exchange rate, the varies with the or at the same time, which ensures that the currency risks measured in and in or are identical. owever, on uly , , the People’s Bank of China (PBOC) announced that it was adopting a managed floating exchange rate regime, based on market supply and demand and with reference to a basket of currencies. he first essay uses the regime shift opportunity to examine whether the exchange risk has an impact on the remaining share discounts after the lifting of restrictions on foreign ownership and the foreign exchange deregulation in hina. revious studies test residual exchange risk by specifying the exchange risk factor as a separate factor and only found limited empirical evidence of exchange risk in stocks. owever, Armstrong, nif, olari and ynnnen testify that “exchange rate risk exists in the residual factor stock returns of some .. firms, but more pervasively in their market factor loadings e.g., market betas.” If the market is perfect and the currency is freely traded, then the exchange risk is loaded in the market risk. his means

that the arket should not price the exchange risk as an indiidual factor ut as a factor interacting with the arket factor (the return of the denoinated exchange rate ultiplied the arket return) ollowing rstrong et al () this stud decoposes the exchange risk factor loading into currenc index (uniersal) and hoe currenc (eg or ) coponents to test whether exchange risk affects Bshare discounts as an indiidual factor loading or through arket factor loading he epirical tests find that and real exchange rates do atter in the B share arkets in oth the and at the arket leel oweer the C real exchange rate does not affect the expected returns of shares in either of the stock exchanges he results indicate that if the appreciates the expected return of B shares will increase ince appreciation akes Chinese exports ore copetitie ut increases the iport costs for Chinese copanies one possile explanation for this result is that ost copanies issuing Bshares are iport oriented rather than export oriented his akes sense ecause copanies tpicall issued Bshares to raise foreign currencies during the strict currenccontrolled period indicating a lack of foreign currenc to iport goods fro other countries he arket index regressions also show that higher and real exchange rate olatilit will decrease the Bshare expected return oweer at the industr leel the exposures to and exchange risk ecoe less oious in contrast to the results at the aggregate arket leel lthough it is difficult to detect a clear pattern of ipacts of real exchange rates on Bshare discounts through and Bshare expected returns it is uite eas to find the effects of changes to the C and C exchange rates on Bshare discounts Based on this analsis if inestors expect a strong C in the future then the Bshare discounts will decline his conclusion is confired the longrun and shortrun results in oth stock exchanges his stud contriutes to the od of literature in the following was irstl it exaines the relation etween exchange risk and Chinese Bshare discounts which has not et een sufficientl studied econdl unlike ost preious studies it tests an international asset pricing odel that ight account for differences in shareholders’ expected returns and then uses different etas to explain the Bshare discounts

Ipact o short selling on share isconts in the hinese stoc aret

here is an onoin deate on the role of short sellin in financial arets ulic inestors dislie short sellers and tend to lae the for causin aret slus hen a crisis occurs, the regulators’ first action is usually to ban short sellin n contrast to ulic inestors and financial reulators an econoists arue that short sellers are the stailiin force in the aret ithout the oerotiistic inestors ould cause ssteatic deiations fro fundaental alues and increase the aret uncertaint iller arrison res iaond errecchia on tein cheinan ion ecause e cannot easil osere or easure the fundaental alue of an asset it is difficult to identif the seculatie ule in an asset rice ei cheinan ion n this sense it is difficult to test the iact of shortsellin constraints on the seculatie ule directl oeer the data of coanies issuin dualclass stocs in the hinese stoc aret roides a solution to this role his data set naturall controls the fundaental alue urtherore the hinese stoc aret launched a lonaaited ilot schee on arch to lift the an on short sellin and arin tradin the end of anuar of the duallisted firms’ Ashares aeared on this desinated list o shares ere eliile for short sellin or arin tradin at that tie ei et al find that the ecessiel hih turnoer of shares can elain of the crosssectional ariation in the share discount fter the liftin of the shortsellin an infored share inestors are ossil ale to short the oeralued stocs to rin the aret rice closer to the fundaental alue hort sellin is still rohiited in share aret and the ehaior of shares should aintain the sae attern hus the a eteen and shares is eected to narro he second essa studies the iact of shortsellin constraints on isricin in the hinese stoc aret usin these dual natural eerients he eent stud is used to inestiate the shortter iact of the liftin of the shortsellin an on the share discounts heoreticall short sellers are ore intellient and eerienced than are the ordinar inestors herefore this stud inestiates hether short sellers in the hinese stoc aret are ore sohisticated than are aerae inestors he fren that often characteries noise traders and the hih costs of short sellin ean that short sellers a fail to correct the isricin in the aret n addition short sellin is relatiel ne and corises a sall roortion of aret tradin aout on aerae on the and

n addition, this research tests hether short sellers are able to correct the oerricing in the hinese stoc maret he results sho that after the lifting of the shortselling ban, share discounts decreased, on aerage n line ith behaioral finance theory, hinese short sellers are more sohisticated they do use arbitrage, but they also beliee in trend ersistence and eect that the rebound folloing a donard trend is temorary en though short selling is not yet oular in the hinese stoc maret, hinese short sellers still contribute to maret stabiliation, as economists eect them to do his study contributes to the eisting literature by clarifying the ositie imact of short selling on stabiliing the maret, based on a uniue data set that aoids the ambiguity of fundamental alue y using rare eeriments, this study does not mae any unrealistic assumtions and studies the real reaction of the maret, hich ensures that the results are more reliable reious studies hae mostly focused on deeloed marets ith mature shortselling mechanisms his study highlights short selling in an emerging maret

n analysis o hinese stoc aret ispricing

ecause the hinese stoc maret is so turbulent and is also the second largest stoc maret in the orld, it is essential to understand hat factors imact the misricing in the maret n addition, as an emerging and young stoc maret, the hinese stoc maret bears characteristics common to many other emerging marets, such as immature retail inestors and tight shortselling constraints ore data are accessible in the hinese stoc marets than any other emerging marets herefore, by studying the misricing mechanism in the hinese stoc maret, inestors can better understand emerging marets n the second study, the author finds that the oint effect of shortselling constraints and heterogeneous beliefs can elain the longlasting share discounts in the hinese stoc maret his result is in line ith the behaioral theoretical models of iller , arrison and res , and cheinman and iong share discounts roide a good data set to measure the misricing, and aoid the inaccuracy of fundamental aluations oeer, a natural eeriment lie this is only feasible for a secific grou of stocs and, thus, cannot be generalied to the hinese stoc maret as a hole onseuently, in the third study, the dynamic residual income aluation model uolteenanho, is adoted to measure the fundamental alue of a stoc his simle model lins the stoc alue to mediumterm cashflo fundamentals rom these,

it is ossible to calculate the fundamental alue and to determine the misricing for each stoc his study tests to theoretical hyotheses that could elain the misricing in the hinese stoc maret, namely the resale otion hyothesis cheinman iong, and the inflation illusion hyothesis odigliani ohn, he resale otion hyothesis redicts that, along ith the shortselling constraints and oerconfidence, the surge of investors’ heterogeneous beliefs on future earnings ill increase the leel and olatility of misricing simultaneously he inflation illusion hyothesis suggests that eected inflation has a negatie correlation ith the leel of misricing his study roides maret results and microscoic results he maret results sho that both the resale otion and inflation illusion hyotheses can elain the leel of maret misricing he effects are consistent ith the theoretical redictions nly investors’ heterogeneous beliefs affect the volatility of market misricing, in line ith the resale otion hyothesis rediction esults at the industry leel sho that both the resale otion and inflation illusion hyotheses can elain the ariation in industrial misricing on the crosssectional and time series dimensions Additionally, the results sho that statecontrolled industries tend to be underestimated more, hen misricing is negatie, but to be oeralued less, hen misricing is ositie urthermore, comared ith nonstatecontrolled industries, heterogeneous beliefs hae a much greater influence on the leel of misricing in statecontrolled industries oeer, the difference beteen the inflation illusion effects on statecontrolled and nonstatecontrolled industries is triial he ariation in the misricing olatility among different industries through different eriods is too comle to be elained by the resale otion or inflation illusion hyotheses

his dissertation elores the factors influencing the misricing in the hinese stoc maret he first to essays use share discounts to measure misricing, and elore the imacts of echange ris and shortselling constraints on share discounts, resectiely he first essay interrets share discounts from a ris loading ersectie, hich relies more on the he second essay elores the henomenon from a behaioral bias ersectie, focusing on the oint effect of short selling and heterogeneous beliefs oth echange ris and shortselling constraints induce the share discounts he third essay further elores the misricing in the oerall Ashare maret to roide generaliable results. In line with the second essay, the author’s

findings are that, under shortselling constraints, different oinions and overconfidence create a seculative bubble and drive u market volatility. his indicates that, to some etent, investors are rational and ask for comensation for taking etra risks. owever, owing to the limitations of arbitrage, we should not underestimate the ability of noise traders to bias the market rice. In addition, all three essays discuss the regime shifts in the hinese stock market. he reforms have endeavored to make the hinese stock market more marketoriented in order to romote longterm healthy develoment. fter the reforms, the misricing has diminished, and the market has become more efficient.

dler, ., umas, . . International ortfolio choice and cororation finance synthesis. Journal of Finance, 38, . dler, ., umas, . . osure to currency risk efinition and measurement. Financial Management, 13, . lert, ., aiffa, . . rogress reort on the training of robability assessors. In . ahneman, . lovic, . versky ds., Judgment under uncertainty: Heuristics and biases. . . ambridge niversity ress. rmstrong, . ., nif, ., olari, . ., ynnnen, . . change risk and universal returns test of international arbitrage ricing theory. Pacific-Basin Finance Journal, 20, . all, ., rown, . . n emirical evaluation of accounting income numbers. Journal of Accounting Research, Autumn, . arberis, ., haler, . . . survey of behavioral finance. In . . onstantinides, . arris, . tul ds., Handbook of economics of finance . . lsevier cience .. amerer, ., ovallo, . . verconfidence and ecess entry n eerimental aroach. The American Economic Review, 89, . aniel, ., irshleifer, ., ubrahmanyam, . . Investor sychology and security market under and overreactions. Journal of Finance, 53, . iamond, . ., errecchia, . . . onstraints on shortselling and asset rice adustment to rivate information. Journal of Financial Economics, 18, . ama, . . fficient caital markets review of theory and emirical work. Journal of Finance, 25, . ama, . ., isher, ., ensen, . ., oll, . . he adustment of stock rices to new information. International Economic Review, 10, . ama, ., lume, . . ilter rules and stock market trading rofits. Journal of Business, 39, . arris, ., aviv, . . ifferences of oinion make a horse race. Review of Financial Studies, 6(3), . arrison, . ., res, . . . eculative investor behavior in a stock market with heterogeneous eectations. Quarterly Journal of Economics, 92, . ong, ., tein, . . . ifference of oinion, shortsales constraints, and market crashes. Review of Financial Studies, 16, .

egadeesh, ., itman, . . eturns to buying winners and selling losers Imlications for stock market efficiency. Journal of Finance, 48, . ensen, . . . isk, the ricing of caital assets, and the evaluation of investment ortfolios. Journal of Business, 42, . ensen, . ., ennington, . . . andom walks and technical theories ome additional evidence. Journal of Finance, 25, . ones, . ., amont, . . . hort sale constraints and stock returns. Journal of Financial Economics, 66, . ahneman, ., versky, . . rosect theory n analysis of decision under risk. Econometrica, 47, . yle, . ., ang, . . . eculation duooly with agreement to disagree an overconfidence survive the market test Journal of Finance, 52, . amont, . . . o down fighting hort sellers vs. firms. orking aer. vailable at httwww.nber.orgaersw.df. amont, . ., haler, . . . nomalies he law of one rice in financial markets. Journal of Economic Perspectives, 17, . evy, . a. andom walks eality or myth. Financial Analysts Journal, 23, . evy, . b. elative strength as a criterion for investment selection. Journal of Finance, 22, . ichtenstein, ., ischhoff, ., hills, . . . alibration of robabilities he state of the art to . In . ahneman, . lovic, . versky ds., Judgment under uncertainty: Heuristics and biases. . . ambridge, ambridge niversity ress. ucas, . . . sset rices in an echange economy. Econometrica, 46, . ei, ., cheinkman, . ., iong, . . eculative trading and stock rices vidence from hinese share remia. Annals of Economics and Finance, 10, . erton, . . n intertemoral caital asset ricing model. Econometrica, 41, . iller, . . . isk, uncertainty, and divergence of oinion. Journal of Finance, 32, . odigliani, ., ohn, . . . Inflation, rational valuation and the market. Financial Analysts Journal, 35, .

uth, . . . ational eectations and the theory of rice movements. Econometrica, 29, . dean, . a. re investors reluctant to realie their losses Journal of Finance, 53, . dean, . b. olume, volatility, rice, and rofit when all traders are above average. Journal of Finance, 53, . oss, . . . he arbitrage theory of caital asset ricing. Journal of Economic Theory, 13, . cheinkman, ., iong, . . verconfidence and seculative bubbles. Journal of Political Economy, 111, . hiller, . . . rom efficient markets theory to behavioral finance. Journal of Economic Perspectives, 17, . hleifer, ., ishny, . . he limits of arbitrage. Journal of Finance, , . iegel, . . . alendar anomalies. Stocks for the long run: The definitive guide to financial market returns and long-term investment strategies nd ed., . . ew ork crawill. olnik, . . International arbitrage ricing theory. Journal of Finance, 38, . tein, . . hy are most funds oenend ometition and the limits of arbitrage. orking aer. vailable at httwww.nber.orgaersw.df. versky, ., ahneman, . . udgment under uncertainty euristics and biases. Science, New Series, 185, . uolteenanho, . . Understanding the aggregate book-to-market ratio. orking aer. vailable at httssrn.comabstract

art II he ssays

nerstaning share isconts change ris in the hinese stoc aret

o hangǂ une

bstract his study investigates the imact of echange risk on the share discount by develoing an estimation model to decomose the valuation differential into two comonents the difference between the eectation of the future echange rate and the sot echange rate, and the difference between the eected returns of and shares, which both contain the echange risk. he emirical tests show that and real echange rates matter to the share markets in the hanghai tock change and the henhen tock change at the market level. owever, the real echange rate does not affect the eected returns of shares on either stock echange. In addition, at the industry level, the eosures to and echange risks become less obvious. lthough it is difficult to detect a clear attern in the imacts of real echange rates on share discounts through and share eected returns, it is uite easy to see how changes to the and echange rates affect share discounts. ased on this study, if investors eect a strong in future, then share discounts will decrease.

JEL classification: , , , Keywords: International asset ricing, share discounts, change risk, hinese stock market

ǂ anken chool of conomics, eartment of inance and tatistics, irastonkatu , , aasa, inland mail mo.zhang@hanken,fi.

iven that it is the largest emerging economy in the world, interest in hinese euity markets has grown raidly in recent years. ecause investors seek higher returns and international diversification, a flood of foreign caital has come into the hinese financial markets. In order to romote “stability,” the hinese government imosed several restrictions on foreign and rivate ownershi, dividing stocks into different classes. he hinese euity market is characteried by the eistence of multile classes of shares. or domestic shares shares, there are three maor categories state shares, held by central or local government or solely stateowned enterrises legal entity shares, held by other enterrises, foreign artners of incororated oint ventures, and nonbank financial institutions and tradable ublicly owned shares, held by individual investors. here are strict segmentations among the three categories of shares. tate and legal entity shares are rohibited from being traded. nly the last category can be freely traded on the stock echange. limited number of listed comanies that issue shares for domestic investors also issue shares in order to attract foreign caital. he two grous of shareholders have identical cash flow rights, voting rights, and obligations, with the ecetion of shares denominated by the hinese yuan , while shares trade on the hanghai tock change , denominated in .. dollars , and on the henhen tock change , denominated in dollars . igure shows the ownershi structure of the hinese stock market before .

igre nership strctre o the hinese stoc aret beore his figure summaries stock classifications and the market segmentation situation in the hinese stock market before . rrows oint out which categories of stocks are accessible for each tye of investors.

stitis i si it i ay tis ili aila sia a alaysia ay ia itla ila a i a ts ts tis ais iss stit sts sti ists ly a stit sts bt sti a i ists ia is ts ats i tat bt lasss sas a stit la i is ilat i s st ats aily ist la i ists i is sas lati t sas i t st ats it a siila stt i lass sas ly a siiiat i is ista ists is is als i by t stis a t al a a a a bay t is t t sa at t sti ists b t ia itis laty issi a t eople’s Bank of China (PBOC) introduced the Qualified Foreign Institutional st s t ta is sas as a sbstatial as i sa ists at t liti stitis i si i t is st at bt sisily sa ists i t isaa t al a aat illy a i t aii sa ists a i t tiats ts ists at t stati al i ss t sis t sa i ists i t a at t lati t ists i si sas aa isly i t ats t is st at is t ly isti at t still stat s bai al s i t t l at stt a ais tay tls is sa ists a iilt t lai a ai a l aily t al i as it a itsti ti st stis lai sa ists by it is lls iati asyty at liiity bt t is sss as yt

share isconts o ierent instries in the

20 0 -20 -40 1/01/2001 7/09/2001 1/07/2002 7/15/2002 1/13/2003 7/21/2003 1/12/2004 7/19/2004 1/10/2005 7/18/2005 1/16/2006 7/24/2006 1/22/2007 7/23/2007 1/21/2008 7/14/2008 1/12/2009 7/13/2009 1/04/2010 7/05/2010 6/20/2011 -60 12/27/2010 -80 -100 share share iscotns

-120 -140 -160

manufacture real estate transportation

retail&wholesale service other

share isconts o ierent instries in the

-20

-40 1/01/2001 7/09/2001 1/07/2002 7/15/2002 1/13/2003 7/21/2003 1/12/2004 7/19/2004 1/10/2005 7/18/2005 1/16/2006 7/24/2006 1/22/2007 7/23/2007 1/21/2008 7/14/2008 1/12/2009 7/13/2009 1/04/2010 7/05/2010 6/20/2011 12/27/2010 -60

-80

-100 share share isconts -120 -140

-160

manufacture real estate transportation other

igre share isconts o ierent instries in the an the his figure shos the ariations of Bshare discounts at the industrial leel fro to he industrial leel Bshare disocunts are calculated the eualeighted ethod ased on listing stocks in oth the and the

he ost oious differences eteen and Bshares are the currenc denoinations change rate fluctuations can affect oth e ante and e post returns Bshare holders receie C diidends ut the stock prices are denoinated in or hen the ealuate a stock the need to conert C diidends into or herefore echange rate changes affect stock prices In addition asset trading ith prices uoted in a particular currenc contains echange risk associated ith rando doestic currenc oeents (dler uas olnik ) Francis asan and unter () successfull find that echange risk is priced in the stock arket at oth the aggregate and industr leels he Chinese econo depends heail on international trading hus currenc oeents affect Chinese companies’ copetitie strength in ters of international trading For eaple doestic manufacturers’ incomes are epressed in or ut the need to pa costs in C hus the suffer fro the C appreciation It is difficult for Chinese firs to hedge against the echange rate risk ecause the Chinese goernent controls the foreign echange for capital account transactions here are fe deriaties that can e used to hedge against C echange risks and these are not idel accessile to doestic inestors and listed copanies Other sian currencies align theseles to the rather than the C here is no significant correlation eteen the C and other sian currencies hich a e used as a pro to hedge against the echange risk he first offshore C deriatie as not aailale until epteer in ong ong Before that doestic inestors and listed copanies had no efficient a to hedge against echange risks hich proal akes echange risk a ssteic risk in the Chinese stock arket hus stocks denoinated in or C proal load different echange risks If that is the case it is reasonale to suspect that Bshare discounts are partiall caused different currenc denoinations he reason h echange risk is not idel discussed in preious research is understandale Before ul China adopted de facto fied echange rate sste under hich the C as pegged to the and as strictl regulated the goernent Fro the earl s until the echange rate reained at aout C to the and ehiited alost no olatilit t the sae

ource Blooerg ikko sset anageent estiates httpennikkoacoarticlesthesutleshiftinasiancurrenciesfrothedollartothe renini B pril the correlations eteen the C and other aor currencies in sia range fro 0.16 to 0.19. However, Asian currencies’ correlations ith the hae decreased noticeal hile the hitherto noneistent correlation ith the C has increased

time, the Hon on overnment aopte a fie echane sstem, pee to the , until now. herefore, there was no echane ris when investors converte C iviens into or H in orer to evaluate stoc prices. imilarl, with the fie C echane rate, the C varies with the or H at the same time, which means that currenc riss measure C an or H are ientical. However, on ul 1, 00, the C aopte a manae floatin echane rate reime ase on maret suppl an eman, with reference to a aset of currencies. As shown in iure , from ul 00 until eptemer 011, the C has appreciate from C . to the to C 6. to the . ost proucts eporte from China are centere on lowcost consumale supplies. A trivial chane in the C echane rate can affect profit marin severel, which woul e reflecte stoc prices. herefore, this chane provies us with the opportunit to eamine whether echane riss have an impact on price isparit. his stu eamines how echane ris affects the remainin share iscounts after the liftin of restrictions on forein ownership an the forein echane ereulation in China. he stu focuses on whether echane ris affects share iscounts, an oes not claim that echane ris is the onl, or even the main influence on share iscounts. his stu contriutes to the o of literature in the followin was. irstl, it eamines the lonrun relation etween echane ris an Chinese share iscounts usin multivariate reressions. econl, in contrast to most previous stuies, this stu tests an international assetpricin moel that miht account for ifferences in shareholders’ expected returns, and then uses ifferent etas to eplain the share iscounts. he remainer of this paper is oranie as follows. ection reviews relate research. ection provies a theoretical eplanation, an ection iscusses the empirical moel an results. ection conclues the paper.

ource he People’s an of China. httpwww.pc.ov.cnenlish1011ine.html. ource Comtrae. httpcomtrae.un.orata.

CNY/USD 0.16

0.15

0.14

0.13

0.12 CNY/USD

0.11

0.1 1/1/1995 1/9/1998 1/8/1999 1/7/2000 1/6/2001 1/5/2002 1/4/2003 1/3/2004 1/2/2005 1/1/2006 1/9/2009 1/8/2010 1/7/2011 1/12/1995 1/11/1996 1/10/1997 1/12/2006 1/11/2007 1/10/2008 CNY/HKD 1.25 1.2 1.15 1.1 1.05 1 0.95 CNY/HKD 0.9 0.85 0.8 1/1/1995 1/9/1998 1/8/1999 1/7/2000 1/6/2001 1/5/2002 1/4/2003 1/3/2004 1/2/2005 1/1/2006 1/9/2009 1/8/2010 1/7/2011 1/12/1995 1/11/1996 1/10/1997 1/12/2006 1/11/2007 1/10/2008 igre he echange rate o an ro anary to epteber hs ure shos the araton o the exchane rate o hnese uan aanst dollar and on on dollar respectel he saple perod s ro anuar to epteer

I I

er decades, researchers hae tred to explan the prce dspart appearn n seented arets throuh arous as he an explanatons are as ollos

Inoration asyetry

Preous studes explaned share dscounts anl usn noraton asetr nnual reports or shareholders ollo the hnese accountn standards P, and are audted local certed pulc accountn P rs oeer, nancal reports or oren shareholders are ased on nternatonal accountn standards s, and are audted the accountn rs ao and ho cla that nancal reports ased on s prode reater noraton than those ollon P oeer, haraart, arar and u arue that een thouh shareholders hae etter accountn noraton, the hae less other noraton ecause o lanuae arrers and culture derences, and so on hat s h oren nestors as or a rs preu to copensate or ther dsadantae oeer, hen et al al to nd an sncant noraton los eteen and shares untl the end o ee et al rechec ths ssue ater the onershp dereulaton, and nd that “there is no asetrc noraton eteen nestors n the to arets.” ter the ltn o restrctons on oren onershp, the share dscounts reaned hereore, noraton asetr s not the sole reason or these derences

iiity proble

he lludt eect s another explanaton or share dscounts hud and endelson explan that nestors as or hher expected returns on relatel llud shares to copensate or ncreased tradn costs ale and atan suest that the llud eect s one o actors leadn to the prce derence n seented ha arets hen et al coe to a slar concluson or hnese share dscounts n addton, ee et al use ntrada data to conr that ludt aects share dscounts throuhout the postdereulaton saple arrat et al nd that the share aret as extreel llud pror to the ltn o the restrcton, and reaned less lud than the share aret untl

is ierentials

s thir ention the ris ierentis hothesis is se on the t tht hinese rets re hih setie n o hih ristoernt oesti inestors ho os on shortrn retrns. ore ith hinese inestors orein inestors re ore ris erse. n ine ith ie tini n n n on in ositie retionshi eteen shre isonts n ris ees. n ontrst to reios sties hen et . i to in n siniint eiene or the ierenti ris hothesis. oeer sin intr t ro rh to ee et . in tht the shre isonts reine ter the reo o the orein onershi restritions ese o the retie s o shres ierent ris ees n the iiit roe in the shre ret. hether the ris ierentis hothesis is i is inonsie.

ierent ean elasticity

eer reserhers he eine the rie rit ro s n en ieoint. oron n i roose tht hinese inestors ser ro strit e restritions hih ee the ro iersiin their ortoios o. in iite inestent oortnities n n insiient sto s oesti inestors sh shre ries ein to shre isonts. rrt et . st the se toi sin i t ro rh to n one tht ir sie n the retie s o shres he een rtir iortnt tors sine . n n on in tht shres iste on the on on to hne n shres o re hi onies re oo sstittes or the shre ret. n this se orein investors’ demand or shres is ore esti. oeer the oe rent ontrits the interntion ssetriin oe. n n nirnn eeoe sset riin oes ner seii or o rrier to interntion inestent n ointe ot tht shres one orein inestors sho e tre t rie rei retie to the orresonin shres one oesti inestors. he re tht ese

Some domestic companies operating in the People’s Republic of China issue both Ashres n shres iste on the on on to hne. hinese oesti inestors re not oe to ho n tre shres. shres roie interntion inestors ith n terntie to inest in hinese inn onies ith eer rriers n osts. ehi onies ontroe inn shrehoers re inororte otsie the hinese ontinent n re tre on the on on to hne.

foreign investors can invest globall the can diversif the specific countr ris and as for loer ris compensation n this sense foreign investors reuire loer epected returns and pa price premiums hich is opposite to the suppl and demand eplanation n summar the eplanations for share discounts are not conclusive and focus mainl on the problems brought about b maret segmentation Along ith the gradual financial deregulation in China especiall in the echange rate regime the degree and impact of maret segmentation are changing oever fe studies anale the impact of the absence of restrictions on share discounts since and onl one stud eamines the effect of the echange rate sstem reforms ing to data limitations the aforementioned studies fail to discuss the effect of echange ris on share discounts ntil the echange rate sstem reform enabled ae i and Shi to eamine this topic he sho that under a more flexible exchange rate system, investors’ attitudes to exchange risk contribute to the increase in share discounts ing to investors’ expectations of C longrun appreciation the are illing to hold C assets rather than S assets oever oing to the short sample period from une to August the are onl able to sho the shortrun change in share discounts after the Chinese currenc echange rate regime shift using the event stud method he fail to sho the sensitivit of share discounts to echange ris oever the longrun effects of an event can be significantl different from those in the short term Additional research on the relation beteen echange ris and share discounts is needed

he share price difference is defined as the logarithmic ratio of the share price converted to C to the corresponding Ashare price

, , , = ln , (1) , 𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡𝑋𝑋𝑀𝑀⁄𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 𝐷𝐷𝑖𝑖 𝑡𝑡 ( ) 𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡 here , and , are the spot prices of the A and shares for compan I respectivel𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡 and 𝑃𝑃𝑃𝑃, 𝑖𝑖/𝑡𝑡 is the spot echange rate of currenc against the C f 𝑀𝑀 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶 , , the la of one price𝑋𝑋 holds is eual to one and then , is ero f there is 𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡𝑋𝑋𝑀𝑀⁄, 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 𝑖𝑖 𝑡𝑡 𝑖𝑖 𝑡𝑡 a price discount , < 0 and vice𝑃𝑃𝑃𝑃 versa 𝐷𝐷

𝐷𝐷𝑖𝑖 𝑡𝑡

share price is determined by the expected dividend flo d and the and share investors’ expected returns and he share dividend is eual to the share dividend divided by the spot exchange𝑟𝑟𝐴𝐴𝐴𝐴 𝑟𝑟of𝐵𝐵𝐵𝐵 the denominating currency o make the model easily comparable, assume that the expected dividend flo follos a constant groth rate, hich is perceived to be the same by both and shareholders hen the share price model is as follos

( ) = . (2) , ( ) 𝐸𝐸𝑡𝑡 𝑑𝑑𝑡𝑡+1 𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝑔𝑔 igure shos that from anuary to uly , hina adopted a fixed exchange rate ith the constant groth assumption, the share price model is

( ) = , (3) , ( ) 𝐸𝐸𝑡𝑡 𝑑𝑑𝑡𝑡+1 𝑋𝑋 𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 − 𝑔𝑔

here / , = , / , = , and X is a constant /1 , ubstituting𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝑌𝑌 𝑀𝑀 𝑡𝑡+𝑠𝑠 )and 𝑋𝑋 𝑋𝑋into𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡 yields𝑋𝑋𝑀𝑀 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡

( ) ( ) ( ) ( ) = + 1 + , ( ) ( ) 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 𝐷𝐷𝑖𝑖 𝑡𝑡 𝑙𝑙𝑙𝑙 ( ) ≈ 𝜀𝜀𝑡𝑡 = ( ( 𝐸𝐸𝑟𝑟) 𝑟𝑟𝐵𝐵𝐵𝐵 −( 𝑔𝑔)) + . 𝐸𝐸 𝑟𝑟 𝑟𝑟 𝐵𝐵 𝐵𝐵 − 𝑔𝑔 (4) 𝛾𝛾 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 𝜀𝜀𝑡𝑡 he euation above shos that discounts can be only explained by different expected returns and some error term oever, in uly , the announced a managed floating exchange rate regime he began to appreciate against the maor currencies and became a partially floating currency

( ) = / , . (5) , 𝐸𝐸𝑡𝑡 𝑑𝑑𝑡𝑡+1 𝑃𝑃𝑃𝑃𝑡𝑡 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡+𝑠𝑠) 𝑟𝑟𝐵𝐵𝐵𝐵 𝑡𝑡 − 𝑔𝑔 Substituting (2) and (5) into (1) yields

( ) = ln / , · , ( ) 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶/𝑀𝑀,𝑡𝑡+𝑠𝑠) 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 −𝑔𝑔 𝐷𝐷𝑖𝑖 𝑡𝑡 ( 𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 −𝑔𝑔)

/ , ( ) ( ) = ln + + 1 / , ( ) 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡+𝑠𝑠) 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 ( ) 𝑙𝑙𝑙𝑙 ( ) 𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶/𝑀𝑀,𝑡𝑡 ( )𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵( −) 𝑔𝑔 + / , ( ) 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡+𝑠𝑠) 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 ≈ 𝑙𝑙𝑙𝑙 ( ) 𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶/𝑀𝑀,𝑡𝑡 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 − 𝑔𝑔 ln + ( ( ) ( )) + . (6) 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶/𝑀𝑀,𝑡𝑡+𝑠𝑠) ≈ ( ) 𝛾𝛾 𝐸𝐸𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 − 𝐸𝐸𝑡𝑡 𝑟𝑟𝐵𝐵𝐵𝐵 𝜀𝜀𝑡𝑡 𝑋𝑋𝐶𝐶𝑁𝑁𝑌𝑌 𝑀𝑀 𝑡𝑡 ro ution e cn see tt tetic sre discounts re decoposed into to prts one ected te excne rte o te inst orein currenc nd te oter ected te expected returns o nd sres ution deonstrtes tt teoretic te excne ris ect te sre discount in to s irst it i ect sre discounts direct ic cn enre or nrro te price prit trou pprecition or deprecition econd it cn ect te return process ese to eects coud e opposite nd coud cnce ec oter out us it is ie tt te excne ris ects te sre discounts in to directions ut tis cnnot e oserved direct ro cnes in te nitudes o te discounts ccordin to rstron ni ori nd nnnen iven cne in n asset’s price over time, it is diicut to distinuis to t extent te cne is cused cnes in te sset vue cnes in te currenc vue or ot. e decopose oc currenc denointed cnes into to prts ne cnes due to underin sset vue oveents denointed in ste set o currencies nd cnes cused excneris price oveents denointed in rndo oc currenc ters e orer is so non s univers returns or te se sset investors receive n identic univers return ut te receive dierent returns denointed in oter oc currencies e dierence depends on cnes in te oc currenc vues oon te onor return is ritten s

, = ln , , . (7)

𝑟𝑟𝑖𝑖 𝑡𝑡 (𝑃𝑃𝑖𝑖 𝑡𝑡⁄𝑃𝑃𝑖𝑖 𝑡𝑡−1) or sres te sset is trded in ic cn e ritten expicit s

( ) , , ( ) = . (8) ( ) , 𝐶𝐶𝐶𝐶𝐶𝐶⁄ 𝑎𝑎 𝑠𝑠ℎ𝑎𝑎 𝑎𝑎 𝑖𝑖 𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶 𝑙𝑙𝑙𝑙 [ ] 𝐶𝐶𝐶𝐶𝐶𝐶⁄ 𝑎𝑎 𝑠𝑠ℎ𝑎𝑎 𝑎𝑎 𝑖𝑖 𝑡𝑡−1 te denointed sre prices re in ste set o currencies te univers return is

( / ) , , ( ) = , (9) ( / ) , ∗ 𝐵𝐵𝐵𝐵𝐵𝐵 𝑠𝑠ℎ𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖 𝑡𝑡 𝑟𝑟𝐴𝐴𝐴𝐴 𝑡𝑡 𝐵𝐵𝐵𝐵𝐵𝐵 𝑙𝑙𝑙𝑙 [ ] 𝐵𝐵𝐵𝐵𝐵𝐵 𝑠𝑠ℎ𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖 𝑡𝑡−1 ere a stae aset o crrecies, , as a costat vae itot ecae ris mtipi ecae rate o te aaist te at time t a t – ,

( ) , a ( ) , , respective, e ca otai te retrs epresse i ,𝐶𝐶𝐶𝐶𝐶𝐶⁄ as𝐵𝐵𝐵𝐵𝐵𝐵 oos𝑖𝑖 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶⁄ 𝐵𝐵𝐵𝐵𝐵𝐵 𝑖𝑖 𝑡𝑡−1

, ( ) = ln ( / ) , ( ) , ( / ) , ( ) , 𝑟𝑟𝐴𝐴𝑖𝑖 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶 ([ 𝐵𝐵𝐵𝐵𝐵𝐵 𝑠𝑠ℎ𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶⁄𝐵𝐵𝐵𝐵𝐵𝐵 𝑖𝑖 𝑡𝑡][⁄ 𝐵𝐵𝐵𝐵𝐵𝐵 𝑠𝑠ℎ𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖 𝑡𝑡−1 𝐶𝐶𝐶𝐶𝐶𝐶⁄𝐵𝐵𝐵𝐵𝐵𝐵 𝑖𝑖 𝑡𝑡−1]) ( / ) , ( ) , = ln + . (10) ( / ) , 1 ( ) , 1 𝐵𝐵𝐵𝐵𝐵𝐵 𝑠𝑠ℎ𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶⁄𝐵𝐵𝐵𝐵𝐵𝐵 𝑖𝑖 𝑡𝑡 [ 𝑖𝑖 𝑡𝑡− ] 𝑙𝑙𝑙𝑙 [ 𝑖𝑖 𝑡𝑡− ] 𝐵𝐵𝐵𝐵𝐵𝐵 𝑠𝑠ℎ𝑎𝑎𝑎𝑎𝑎𝑎 𝐶𝐶𝐶𝐶𝐶𝐶⁄𝐵𝐵𝐵𝐵𝐵𝐵 or simpicit, atio ca e ritte as

, ( ) = , + / , , (11) ∗ 𝑟𝑟𝑛𝑛 𝐴𝐴𝐴𝐴𝐴𝐴 𝐶𝐶𝐶𝐶𝐶𝐶 𝑟𝑟𝑛𝑛 𝐴𝐴𝐴𝐴𝐴𝐴 𝑟𝑟𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡

ere , is te iversa retr o sare i at time t, eomiate a stae aset ∗ crrec,𝑟𝑟𝑛𝑛 𝐴𝐴𝐴𝐴𝐴𝐴 / , represets te cae i te ecae rate o te aaist te a n 𝑟𝑟𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 or 𝑡𝑡

imiar, sare retrs epresse i a ca e ritte as

, ( ) = , + / , (12) ∗ 𝑟𝑟𝑠𝑠ℎ ,𝐵𝐵𝐵𝐵𝐵𝐵 (𝑈𝑈𝑈𝑈𝑈𝑈 ) =𝑟𝑟𝑠𝑠ℎ 𝐵𝐵, 𝐵𝐵𝐵𝐵 +𝑟𝑟𝑈𝑈𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵/ 𝑡𝑡, , (13) ∗ 𝑟𝑟𝑠𝑠𝑠𝑠 𝐵𝐵𝐵𝐵𝐵𝐵 𝐻𝐻𝐻𝐻𝐻𝐻 𝑟𝑟𝑠𝑠𝑠𝑠 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡

ere , a , are te iversa retrs o sares iste o te or , ∗ ∗ respective𝑟𝑟𝑠𝑠ℎ 𝐵𝐵,𝐵𝐵𝐵𝐵 eomiate𝑟𝑟𝑠𝑠𝑠𝑠 𝐵𝐵𝐵𝐵𝐵𝐵 a stae aset crrec, / , represets te cae i te ecae rate o te aaist te a 𝑟𝑟𝑈𝑈𝑈𝑈𝑈𝑈/𝐵𝐵𝐵𝐵𝐵𝐵,𝑡𝑡 represets te cae i te ecae rate o te aaist te 𝑟𝑟𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 ive tat a sares are isse te same compa, ivestors ave te ietica rits a oiatios a sares are cosiere assets it ietica ameta vaes, te ivestors reire ieret retrs or a sares o

China's Top 10 Trading partners in 2010

Japan

ASEAN

Hong Kong

Korea

Taiwan

Australia

Brazil

0% 5% 10% 15% 20% Data source: China Customs Statistics

Figure 4. The composition of China’s main trading partners in 2010

shows the composition of China’s major trading partners China’s

, = + , + , + / , + / , (14) 𝑛𝑛 𝑛𝑛 𝑛𝑛 𝑛𝑛 2 𝐸𝐸𝑡𝑡(𝑟𝑟𝐴𝐴 𝑖𝑖𝑖𝑖+1) − 𝑟𝑟𝑓𝑓 𝛼𝛼𝑖𝑖 𝛽𝛽𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴(𝑅𝑅𝐴𝐴𝐴𝐴 𝑛𝑛 − 𝑅𝑅𝑓𝑓𝑓𝑓) 𝛽𝛽𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴(𝑅𝑅𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑡𝑡 − 𝑅𝑅𝑓𝑓) 𝛽𝛽𝑋𝑋1𝑖𝑖𝑅𝑅𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 𝛽𝛽𝑋𝑋2𝑖𝑖𝑅𝑅𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 , = + , + , + / , + / , ,(15) 𝑛𝑛 𝑛𝑛 𝑛𝑛 𝑛𝑛 2 𝑡𝑡 𝐵𝐵 𝑖𝑖𝑖𝑖+1 𝑓𝑓 𝑖𝑖 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵 𝑛𝑛 𝑓𝑓𝑓𝑓 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑡𝑡 𝑓𝑓 𝑋𝑋3𝑖𝑖 𝑀𝑀 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 𝑋𝑋4𝑖𝑖 𝑀𝑀 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡 𝐸𝐸 (𝑟𝑟 ) − 𝑟𝑟 𝛼𝛼 𝛽𝛽 (𝑅𝑅 − 𝑅𝑅 ) 𝛽𝛽 (𝑅𝑅 − 𝑅𝑅 ) 𝛽𝛽 𝑅𝑅 𝛽𝛽 𝑅𝑅

where , and , represent the domestic maret retrns of and shares respectie𝑅𝑅𝐴𝐴𝐴𝐴 𝑛𝑛 𝑅𝑅𝐵𝐵, 𝐵𝐵 𝑛𝑛is the internationa maret retrn and or he second𝑅𝑅𝐴𝐴𝐴𝐴 step𝑊𝑊𝐼𝐼 𝑡𝑡 is to cacate the epected retrns of and shares sing the etas estimated in ations and as independent ariaes in the discont regression he discont mode is ased on ation n ation the theoretica mode restricts the coefficients of the epected retrns of the and shares to e identica ere the athor oses this restriction and tests whether the coefficients of the epected retrns of the and shares are identica ecase it is ie that one maret has more of an impact on share disconts than the other he nondeierae forwards of C can e sed as the epected C echange rate at time t s natra generated the maret oweer there is no aaiae data for C wing to the ac of a maret epectation on the ftre echange rate the athor assmes that past price patterns can e sed to predict the ftre C echange rate herefore for the rostness chec and the regression in the the athor adopts an atoregressie mode to estimate the epectation of the echange rate sing the spot and foragged echange rate

/ , = C + , , + ln + (16) / , 𝑛𝑛 n n 𝑛𝑛 𝑛𝑛 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡+𝑠𝑠) 𝑛𝑛 𝑖𝑖𝑖𝑖 i 1i 𝑡𝑡 𝐴𝐴 𝑖𝑖𝑖𝑖+1 2𝑖𝑖 𝑡𝑡 𝐵𝐵 𝑖𝑖𝑖𝑖+1 3𝑖𝑖 𝑡𝑡 𝐷𝐷 = C + 𝛾𝛾 𝐸𝐸 (𝑟𝑟 ) − 𝛾𝛾 𝐸𝐸 (𝑟𝑟 ) + 𝛾𝛾 ( +𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡 ) 𝜀𝜀 , , , 𝑋𝑋 , 𝑛𝑛 n n 𝑛𝑛 n n 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶 𝑖𝑖𝑖𝑖 i 1i 𝑡𝑡 𝐴𝐴 𝑖𝑖𝑖𝑖+1 2𝑖𝑖 𝑡𝑡 𝐵𝐵 𝑖𝑖𝑖𝑖+1 1i 𝑡𝑡 2i 𝑡𝑡−1 𝐷𝐷 + 𝛾𝛾 𝐸𝐸/ (,𝑟𝑟 + ) − 𝛾𝛾 𝐸𝐸 (/𝑟𝑟 , +) 𝜃𝜃 𝑅𝑅 𝑀𝑀/ , 𝜃𝜃+ 𝑅𝑅 ,𝑀𝑀 (17) n n n 𝑛𝑛 𝜃𝜃3i𝑅𝑅𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡−2 𝜃𝜃4i𝑅𝑅𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡−3 𝜃𝜃5i𝑅𝑅𝐶𝐶𝐶𝐶𝐶𝐶 𝑀𝑀 𝑡𝑡−4 𝜀𝜀𝑡𝑡 where , and , are the epected retrns of the and shares cacated𝐸𝐸𝑡𝑡( 𝑟𝑟𝐴𝐴 𝑖𝑖 𝑖𝑖ation+1) s 𝐸𝐸𝑡𝑡(𝑟𝑟 𝐵𝐵and𝑖𝑖𝑖𝑖+1 ) respectie and / , is the retrn of the C echange rate against the or at time t - i for𝑅𝑅𝐶𝐶𝐶𝐶𝐶𝐶 i= 𝑀𝑀0,𝑡𝑡 −𝑖𝑖1, …, 4

4 T C T

he primar data set consists of wee stoc retrns on si indstr portfoios in the and for indstr portfoios in the escriptions of the indstr portfoios are proided in ppendi ppendi presents the preiminar statistics of the continos componded retrns of the indstr portfoios and the maret indices for the and shares in the and the he oera sampe period is from erar to eptemer he prereform sampe period rns from erar to t on the postreform sampe to eptemer is sed in the mtiariate regressions ecase this std focses on how the echange ris affects the share price disconts after the echange rate reform which egan in he wee Chinese and share prices Chinese stoc inde data and the forward echange rates of C from the maret are retrieed from the oomerg dataase he goa stoc inde data C are proided the organ tane Capita nternationa research center he major crrenc inde C is aaiae from the edera esere and the echange rates of C and C foow the officia echange rates ae smmaries the crosssectiona sampe statistics he data set incdes Chinese companies isted in oth the and share marets among which are isted on the and are isted on the ae aso shows that the proportions of freefoating shares are for shares and for shares in the and for shares and for shares on the ome shares not free traded most of which are state and ega person shares oweer a shares can e accessed a inestors he nmer of shares otstanding is aot haf the nmer of shares otstanding in the and aot one third in the

nti eptemer there were companies that issed oth and shares he sampe ecdes two stocs with too man missing oserations

Tae 1. escriptie statistics of duacass sampe he sampe incdes Chinese firms that are incorporated in China and hae and shares isted in the and aret ae of eit is the prodct of the tota nmer of shares otstanding and the stoc price conerted to of shares free foating is the stocs free trading in the or diided the tota otstanding stocs

change a o of aret o of of rading cass oserations ae of shares shares crrenc eit otstanding free miion miion foating C C

4.1 niariate tests of share discounts

ince the echange ris effect on share disconts cod e idirectiona it is diffict to predict the impact of the echange rate reform ae compares how the share disconts and retrn differentias changed after China shifted to a more feie echange rate regime he distritions of share discont and stoc retrns are not norma distrition n order to get rost rest the athor compares means and medians of share disconts and share retrns and oatiities in oth periods and tests mean and median changes in oth sampe periods share disconts eist and are significant different from ero in oth periods at the ee mean tests t increase after the echange rate reform from to in the in the at the maret ee cacated sing the and inde prices he rests of median tests are simiar with mean tests oweer the maret ee disconts ma not e accrate ecase the share inde incdes companies issing oth and shares as we as companies issing shares on herefore the athor considers the indstria ee to chec the effect of the echange rate reform on the share disconts n the share disconts increased in the manfactring and transportation indstries after the echange rate reform in the manfactring indstr and in the transportation indstr whie the share disconts of the remaining indstries decined ranging from to at the mean ee ince share

disconts are not norma distrited the rests of the eait tests on medians are more reiae he change of medians in each indstr shows simiar pattern as mean rests he eait tests on means and medians of share disconts in a the indstries gie consistent rests en thogh the signs of share discont differences for retail and “other” industry before and after reform period change, ttests show that the are not statica significant oweer in the on the mean of the transportation indstr disconts decreased from to ased on mean tests he share disconts of the remaining indstr portfoios increased after the echange rate reform which is opposite to the phenomenon fond in the sing t tests on mean difference we find that on the discont change of the “other” indstr is different from ero at the significance ee increasing oweer the eait tests on medians show that epect for transportation indstr a the share disconts of the remaining indstries increase significant aring from to nie the hanghai maret impacts of the echange rate reform on different indstries in the henhen maret are in the same direction increasing the and share price disparit n smmar the arge share disconts fond in ae are consistent with the findings of preios stdies n addition ae shows that share disconts sti eisted in oth the and the after the echange rate reform oweer the effects of the echange rate reform on share disconts ar in oth marets and different indstries his is reasonae ecase degrees of internationa integration ar wide in different indstries he sensitiit to echange rate moements is correated with a ee of internationa integration rancis et a nstead of eamining share disconts at the aggregate maret ee on it is more meaningf for practitioners to find the specific impact of the echange rate reform on each indstr ccording to preios discssions the ariation in the C echange rate increases in a more feie echange rate sstem ringing more echange riss to inestors in the Chinese maret t is reasonae to sspect that epected retrns ma change after the echange rate reform anes and C in ae dispa the reaied retrns of and shares in the and the n the preechange rate reform period at the aggregate maret ee share reaied retrns eceeded share reaied retrn in oth marets

n the there is on one compan in the mining indstr and two companies in the constrction indstr hese three companies are groped as the “other” indstr n the there is one compan in the serice indstr and two companies in the whoe and retai trade indstr hese three companies are groped as the “other” indstr

calculated using the and share maret inde onsistent ith the maretleel result, the means of the share realied returns in each industry are loer than the means of the share realied returns in both the and the , een though all mean alues are negatie oeer, in the postechange rate reform period, the results become mied n the , share inestors also receie higher returns than share inestors in all industry portfolios do n addition, the means of the realied returns for both and share inestors become positie, ranging from to n contrast to the results in the , the share realied return is higher than the share realied return, at the aggregate leel, in the for shares, for shares n order to determine hether the differences beteen the and share realied returns are statistically significant, anels and in able sho the results of mean and median difference tests for both the prereform and postreform periods he results indicate that no differences at the industry or maret leels are statistically significant in either stoc echange his is understandable, because anels and sho that the magnitudes of the realied returns at the mean leel are ery small, not eceeding in the oerall data set, regardless of the industry or period urthermore, none of the means of the realied returns are statistically significantly different from ero or this reason, it is difficult to say that there is no change in the and share realied returns beteen the prereform and postreform periods tatistically insignificant results do not mean that the change in the echange ris does not affect the return process in the hinese stoc maret from an economic point of ie n another ords, echange ris does matter, but probably cannot be detected using uniariate tests ccording to preious studies, the riss associated ith the and stoc marets are different, so the author also tests hether the olatility beteen and shares aries, and hether the echange rate reform affects the olatility of and shares he last to columns of anels and in able sho that the echange rate reform did change the olatility of and shares in both echanges efore the reform, shares had higher olatility in eery industry and at the maret leel in both the and the , indicating that the share maret contains less ris than the share maret oeer, after the reform, at the maret leel, the share maret still has higher olatility than the oerall share maret in the cept for the manufacturing and the “other” industry, the industries sho no olatility difference beteen and shares in the oreoer, in the , the shares in the manufacturing and “other” industries are less olatile than are the shares

te the ehe e the tt eee e t the et ee the hh tet th the et et e t the t ee the ttt t h t he tt eee ee the eee etee the tt the he the ttt t ete t tht he t hhe th he hh te t the ee e et te tet ette tht ehe e et the he t the the t t t t te hethe t the t ee t t the ehe te e et the ee et the tt he he te the et the tt etee he e th e te the e t e te the t ehe he t et e tte ee t ee th e e e

et eete 𝑉𝑉 e e t e the e h t Tae The 2. comparison in ofand share the and efore and afterthe echange ratereform. ̅ 𝐴𝐴𝐴𝐴 1 he t the e

eetehe he t t e the e ette hethe the t t 𝑉𝑉 ̅

𝐵𝐵𝐵𝐵 e 0

𝑉𝑉 ̅ tet tet e tett et e the the 𝐵𝐵𝐵𝐵 1

he t te te tt the e e e t the e

te e t the eet ee eete

Tae 2. The comparison of and share in the and efore and after the echange rate reform. he the t

e e t the h te ette the he the he t he𝑋𝑋 et tte te the ehe te e the 𝑀𝑀

, , ⁄ he t te , = ln hee𝐶𝐶𝐶𝐶𝐶𝐶 , , e the e e eh ee 𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡𝑋𝑋𝑀𝑀⁄, 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 , 𝑡𝑡 he eete , the e𝑖𝑖 𝑡𝑡 ehe𝑃𝑃𝑃𝑃𝑖𝑖 𝑡𝑡 te the et𝑖𝑖 𝑡𝑡 𝑖𝑖 𝑡𝑡 e t he eehe

𝐷𝐷 ( ) e the ehe te etthe e 𝑃𝑃𝑃𝑃 𝑃𝑃𝑃𝑃

e t he tehee e t the e t etee e ee 𝑋𝑋𝑀𝑀⁄𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 he t the ee e the te e eete , e e0 1 the he

he t

𝑖𝑖 𝑖𝑖

𝐷𝐷 𝐷𝐷 0 1

t the ee e the te e eete t he te the ee et the 𝑖𝑖 𝑖𝑖 he t t the ee e the te𝐷𝐷 e0 1 eete𝑀𝑀𝑀𝑀0 𝐷𝐷1 𝑀𝑀𝑀𝑀 𝐷𝐷 𝑖𝑖

, 𝐴𝐴𝐴𝐴 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵 𝑡𝑡 0 eeete e et 𝑟𝑟̅ 𝑟𝑟̅ 𝑟𝑟̅ 𝑟𝑟̅ he t t the e 0 0 1 1 = e e the he t t et the ee e the te𝐴𝐴𝐴𝐴 e𝐵𝐵𝐵𝐵 eete𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵

ln 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 te tt the he t t the ee e the te e ehe e t etee ̅

( 𝑉𝑉𝐴𝐴𝐴𝐴 eete1 0 tet1 e t tet et e hte tet𝑃𝑃𝑃𝑃 e t tet et e tet e t tet

𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵 e the

̅ ̅ ̅ 𝑖𝑖

𝑉𝑉 𝑉𝑉 𝑉𝑉 ,

et e te e t the eet𝑡𝑡 ee eete 𝑃𝑃𝑃𝑃 𝑋𝑋 𝑀𝑀 e e

𝑖𝑖 ⁄ , 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶 , 𝑡𝑡 hte )

he et tte te ehethe te e the hee hee e eete e e eete ee

tet et tet et e e the t e the 𝑃𝑃𝑃𝑃 𝑟𝑟 𝐴𝐴𝐴𝐴 𝑖𝑖 ̅ 0 , 𝑡𝑡 𝑟𝑟 𝑃𝑃𝑃𝑃 𝐴𝐴𝐴𝐴 ̅ 1 e e t the 𝑖𝑖 , 𝑡𝑡

e the e e eh ee eh ee e the e e 𝑟𝑟 𝐵𝐵𝐵𝐵 𝑀𝑀𝑀𝑀 ̅ 0 𝑟𝑟 𝐷𝐷

𝐵𝐵𝐵𝐵 ̅ 1 𝑖𝑖 0 te ee the et the , t he 𝑀𝑀𝑀𝑀 e eeete 𝑀𝑀𝑀𝑀 𝐷𝐷 𝑖𝑖 1 𝑟𝑟

𝐴𝐴𝐴𝐴 0 e ethe

𝑀𝑀𝑀𝑀 𝑟𝑟 𝐵𝐵𝐵𝐵 0

𝐷𝐷 tet et tet 𝑖𝑖

0 e e 𝐷𝐷

𝑀𝑀𝑀𝑀 𝑖𝑖 e 1

e ee

𝑟𝑟

𝐴𝐴𝐴𝐴

ehe ehe 1

𝑀𝑀𝑀𝑀 he he

𝑉𝑉 ̅

𝑟𝑟 𝐴𝐴 0 𝐵𝐵𝐵𝐵 1

, ,

aneThe . comparis

ane . The comparison of and shares in the efore and after the echange rate reform

reechange rate reform

0 0 0 0 0 0 0 0 ̅𝑖𝑖 𝑖𝑖 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 ̅𝐴𝐴𝐴𝐴 ̅𝑖𝑖 𝐷𝐷 𝑀𝑀𝑀𝑀𝐷𝐷 𝑟𝑟̅ 𝑟𝑟̅ 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀 𝑟𝑟 𝑉𝑉 𝑉𝑉 on of of on

𝐷𝐷

𝐷𝐷 ̅ ̅ 𝑖𝑖 𝑖𝑖 1 , 0

and

𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 , ,

𝐷𝐷 𝐷𝐷

, shares in the efore andthe echange after ratereform 𝑖𝑖 𝑖𝑖 1 0

ostechange rate reform 𝑟𝑟 𝑟𝑟 𝐴𝐴 𝐴𝐴 ̅ ̅ 1 0

1 ost 1 1 1 1 1 1 1

𝑖𝑖 𝑖𝑖 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵

𝐷𝐷̅ 𝑀𝑀𝑀𝑀𝐷𝐷 𝑟𝑟̅ 𝑟𝑟̅ re 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 𝑉𝑉̅ 𝑉𝑉̅

echange rate reform echange rate reform

𝑟𝑟 𝑟𝑟 𝐵𝐵 𝐵𝐵 ̅ ̅ 1 0

𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 ,

𝑟𝑟 𝑟𝑟 𝐴𝐴 𝐴𝐴 1 0

𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀

𝑟𝑟 𝑟𝑟 𝐵𝐵 𝐵𝐵 1 0

𝑉𝑉 𝑉𝑉 ̅ ̅ 𝐴𝐴 𝐴𝐴 1 0

𝑉𝑉 𝑉𝑉 ̅ ̅

𝐵𝐵 𝑖𝑖

1 0

ane . aneTests . on difference eteen pre

ane . Tests on difference eteen preand postreform periods in the 𝐷𝐷 ̅

𝑖𝑖 1 1 0 1 0 0 0 0 0 − 1 1 1 1 0 0 1 1

𝐷𝐷 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝑖𝑖 𝑖𝑖 𝑖𝑖 𝑖𝑖 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 ̅ 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟

̅ ̅ 𝑖𝑖

0 𝑉𝑉 − 𝑉𝑉 𝑉𝑉 − 𝑉𝑉 𝐷𝐷 − 𝐷𝐷 𝑀𝑀𝑀𝑀𝐷𝐷 − 𝑀𝑀𝑀𝑀𝐷𝐷 𝑟𝑟 − 𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 − 𝑀𝑀𝑀𝑀𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 − 𝑀𝑀𝑀𝑀𝑟𝑟

𝑀𝑀𝑀𝑀 𝐷𝐷 𝑖𝑖 1

−

𝑀𝑀𝑀𝑀

𝐷𝐷

𝑖𝑖 0 , （ 𝑟𝑟 𝐵𝐵 0

（） − 𝑟𝑟 𝐴𝐴 0

）

𝑀𝑀𝑀𝑀

𝑟𝑟 a 𝐵𝐵 0 nd post − 𝑀𝑀𝑀𝑀

𝑟𝑟 𝐴𝐴 0

reform periods in the 𝑟𝑟 𝐵𝐵 1 − 𝑟𝑟 𝐴𝐴 1

𝑀𝑀𝑀𝑀 𝑟𝑟 𝐵𝐵 1 − 𝑀𝑀𝑀𝑀

𝑟𝑟 𝐴𝐴 1

𝑉𝑉 𝑟𝑟 0 𝐵𝐵𝐵𝐵

− 𝑉𝑉 𝑟𝑟 0

𝐴𝐴

𝑉𝑉

𝑟𝑟

𝐵𝐵𝐵𝐵

−

𝑉𝑉 𝑟𝑟 1

𝐴𝐴

, ,

ane . Testsane . on difference eteen pre ane The comparisonane C. of

ane C. The comparison of and shares in the efore and after echange rate reform reechange rate reform

𝐷𝐷 ̅

0 0 0 0 0 0 0 0

𝑖𝑖 1

𝑖𝑖 𝑖𝑖 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝑖𝑖 ̅ ̅ ̅

𝐷𝐷 𝑀𝑀𝑀𝑀𝐷𝐷 𝑟𝑟̅ 𝑟𝑟̅ 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 𝑉𝑉 𝑉𝑉 − 𝐷𝐷 𝐷𝐷 ̅ ̅ 𝐷𝐷 ̅ 𝑖𝑖 𝑖𝑖 1 0 𝑖𝑖

𝑀𝑀𝑀𝑀

, 𝐷𝐷 𝑖𝑖 1 − 𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀

and

𝐷𝐷 𝐷𝐷

𝐷𝐷

𝑖𝑖 𝑖𝑖 1 0 𝑖𝑖

0 ostechange rate reform

𝑟𝑟 shares in the efore reform shares and the rate after echange in

𝐵𝐵 1 1 1 1 1 1 1 1

0 ̅𝑖𝑖 𝑖𝑖 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 ̅𝐴𝐴𝐴𝐴 ̅𝐵𝐵𝐵𝐵 − 𝐷𝐷 𝑀𝑀𝑀𝑀𝐷𝐷 𝑟𝑟̅ 𝑟𝑟̅ 𝑀𝑀𝑀𝑀𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 𝑉𝑉 𝑉𝑉 𝑟𝑟 𝐴𝐴

𝑟𝑟 𝑟𝑟 0

𝐴𝐴 𝐴𝐴

̅ ̅

1 0

ost

𝑀𝑀𝑀𝑀 𝑟𝑟

and post echange rate reform rate echange 𝐵𝐵 0 echange rate reform rate echange ,

− 𝑀𝑀𝑀𝑀

𝑟𝑟 𝑟𝑟

𝐵𝐵 𝐵𝐵 ̅ ̅ 1 0

𝑟𝑟 𝐴𝐴

anereform periods in the . Tests on difference eteen preand postreform periods in the 𝑟𝑟 𝐵𝐵 1 − 𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 10 1 0 0 0 0 0 11 1 1 0 0 11 𝑟𝑟 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝐴𝐴 𝑖𝑖 𝑖𝑖 𝑖𝑖 𝑖𝑖 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴

̅ ̅ 𝑟𝑟 𝑟𝑟

𝑉𝑉 − 𝑉𝑉 𝑉𝑉 − 𝑉𝑉 𝐷𝐷 − 𝐷𝐷 𝑀𝑀𝑀𝑀𝐷𝐷 − 𝑀𝑀𝑀𝑀𝐷𝐷 𝑟𝑟 − 𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 − 𝑀𝑀𝑀𝑀𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑀𝑀𝑀𝑀𝑟𝑟 − 𝑀𝑀𝑀𝑀𝑟𝑟

𝐴𝐴 𝐴𝐴

1 0

𝑀𝑀𝑀𝑀 𝑟𝑟 𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 𝐵𝐵

− , 𝑟𝑟 𝑟𝑟 𝐵𝐵 𝐵𝐵 1 0 𝑀𝑀𝑀𝑀

𝑟𝑟

𝐴𝐴

𝑉𝑉 𝑉𝑉 𝑉𝑉 ̅ ̅ 𝑟𝑟 𝐴𝐴 𝐴𝐴 1 0 0 𝐵𝐵𝐵𝐵

−

𝑉𝑉 𝑟𝑟 0 𝐴𝐴

𝑉𝑉

𝑟𝑟 1 𝐵𝐵𝐵𝐵 𝑉𝑉 𝑉𝑉 ̅ ̅ 𝐵𝐵 𝑖𝑖 1 0 −

𝑉𝑉

𝑟𝑟

1 𝐴𝐴

4.2 esuts ased on asset pricing mode

, , , , pricing factor. From fundraisers’ point , , , , , , , , , , , , , , , , , , , , ,

respectie. currenciesof constructed organ tane. and sos tae te is Tae .

𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

ofesuts i

. 𝑟𝑟 𝑓𝑓 𝑅𝑅 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 onstant ode 𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐻𝐻𝐻𝐻𝐻𝐻 𝐻𝐻𝐻𝐻𝐻𝐻 𝑈𝑈 𝑈𝑈 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶 𝑎𝑎 𝑎𝑎𝑎𝑎𝑎𝑎 , 2 2 2 2 𝑟𝑟 𝑡𝑡𝑡𝑡

𝑈𝑈 𝑈𝑈 / / / / 𝑡𝑡𝑡𝑡𝑡𝑡 / / 𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵𝐵𝐵 − 𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵𝐵𝐵

are inese te and.. ris free rat nternationa asset pricing themode at maret ee

𝑟𝑟 and and 𝑓𝑓

𝑟𝑟 indicate teretur 𝑡𝑡𝑡𝑡

Tae . esuts of internationa asset pricing mode𝑡𝑡𝑡𝑡𝑡𝑡 at the maret ee share’s exposures to the exchange the to exposures share’s is tae sos te and share’s exposures to the exchange ris of te denominating currencies at te maret ee. 𝑟𝑟

and indicate te returns of and sare inde in te𝐶𝐶𝐶𝐶𝐶𝐶 and . is te return of te goa inde 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 constructed organ tane. / , / , / are te returns of rea ecange rates of and 𝑟𝑟 against𝑟𝑟 a aset /

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐵𝐵𝐵𝐵𝐵𝐵 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑟𝑟 𝑟𝑟, 𝑟𝑟 of currencies. are te inese and .. ris free rate respectie𝑟𝑟 . and indicate significance at te and percent ees

𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑈𝑈 𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵 𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

𝑟𝑟 𝑟𝑟 𝑟𝑟 . , .

respectie. . . 𝑟𝑟 . .

𝑓𝑓 𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡 . . . 𝑟𝑟 𝑟𝑟 𝑈𝑈

ns of 𝑈𝑈

/ ode / 𝐵𝐵𝐵𝐵𝐵𝐵 −

onstant . .. . . 𝑟𝑟

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑓𝑓 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑓𝑓 𝑓𝑓 𝑡𝑡𝑡𝑡𝑡𝑡, 𝑡𝑡𝑡𝑡 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑓𝑓 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑓𝑓 𝑟𝑟

𝑟𝑟 − 𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑟𝑟 − 𝑟𝑟

. . .𝐻𝐻𝐻𝐻𝐻𝐻 . .

/ . .. and . . /

. . .𝐵𝐵𝐵𝐵𝐵𝐵 . .

𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑓𝑓 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 e 𝑟𝑟 − 𝑟𝑟 𝑟𝑟 . 𝑟𝑟 .

/ respectie sare inde in te 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 . . are returns te of rea ecange ratesof and . . .. . . . ris of te denominatingte of ris currencies .. .. 𝑟𝑟𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 . .. . /

. . 2 −

𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵

𝑟𝑟 ..

/ . . . . 𝑟𝑟 . 𝑓𝑓 . .. and indicate significance atte and percent ees /

𝑈𝑈𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟

𝑟𝑟 𝑡𝑡𝑡𝑡

. .

𝑡𝑡𝑡𝑡𝑡𝑡

2 . . 𝑟𝑟𝑈𝑈𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵 . / and . . 𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵

𝑟𝑟 𝑟𝑟 . / 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

. .

2 . . . . . . . 𝑟𝑟𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵 .. .. . . 2 −

𝑅𝑅 𝑟𝑟 𝑓𝑓 𝑟𝑟

at 𝑎𝑎𝑎𝑎𝑎𝑎

te maret ee. maret te 𝑎𝑎

is teis return of g te 𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 . . . . . . . . .

−

𝑟𝑟 𝑓𝑓 𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

against a aset

oa inde

𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

o otan a genera ea the an share aret nces are use to test hether exchange rs exposure can e etecte at the aggregate aret ee an hether an share arets are ntegrate n the goa stoc aret ae shos that n the the share aret s ntegrate n the goa aret th an nternatona aret eta o at the sgncance ee n contrast shares n the o not exht an tpe o resua exposure to exchange rate rs at the aret ee s outos an n pont out not nng sgncant resua exposure oes not necessar ean that a copan s not aecte exchange rate rs ecause the copan s e expose to exchange rate rs a ts aret portoo shares n the ehae erent to shares nexpecte the coecent o the goa aret s not statstca sgncant shong that the share aret oes s not ntegrate nto the goa aret he coecent o the return o the exchange rate aganst the aor currenc nex s at the sgncance ee hs ncates that the apprecates then share nestors expect hgher returns on shares he exposure to arance n the exchange rate return n the s negate th a aue at the sgncance ee ron nterprets that a copan has a greater ncente to hege hen the exchange rate oatt ncreases hus the transacton costs o hegng aganst exchange rate rs ncrease eang to oer returns nce there s no unue rsree rate cae the nternatona rsree rate t s reasonae to ueston hether there e an erence eteen the hnese rsree rate an the rs ree rate n ppenx pane the tests sho that the hnese rsree rate s statstca sgncant erent ro the t at oth the ean an the oatt ees s a roustness chec use the t nterest rate as the rsree rate or oregn nestors an run the regresson agan here are no sgncant changes to the resuts ar to the resuts o the the goa aret eta o shares s poste at the sgncance ee n the he exchange rs etas are st not statstca sgncant or the share aret the nu hpothess that the goa aret eta n the s eua to ero s reecte he exposure to the return o the exchange rate s nsgncant erent ro ero ut the exposure to the oatt o exchange rate returns s negate an statstca sgncant n suar there exsts a resua exposure o shares to exchange rs n oth the an the at the aggregate aret ee he the share aret oes not ehae n such a a ecang the resuts n ae an assocatng the th erent exposures to exchange rs n the an share arets n ae e can concue that hgher oatt o the an exchange rates aganst the cou narro the gap eteen the returns o an shares t the aggregate aret ee t sees

that nestors respon on to changes n the an aues ut not to a change n the aue ae shos the nustr ee resuts o nternatona aret ntegraton an exchange rs exposure ane n ae shos the share aret resuts n the he oestc aret etas o a nustres are sgncant poste at the ee rangng ro or the serce nustr to or the rea estate nustr ne the aggregate aret resuts on the transportaton an the “other” nustr hae sgncant goa aret etas an respecte ut the goa aret etas o the reanng nustres are not statstca erent ro ero ar to the aggregate aret resuts none o the nustres are expose to exchange rs ane n ae shos that a sx share nustr portoos hae poste an sgncant oestc aret etas n the rangng ro or the anuacturng nustr to or the rea estate nustr ar to the resuts o the share aret on to nustr portoos rea estate an serce hae sgncant goa aret etas or rea estate nustr an or serce nustr opare th the aret ee resuts exchange rs exposures at the nustr ee ecoe ess oous n the serce an “other” nustres hae sgncant coecents on the rst oent o the exchange rate aganst the th aues o an respecte hs ncates that a apprecaton aect returns n the serce nustr negate ut hae a poste pact on the “other” nustr urtherore none o shares are expose to the exchange rs easure the oatt o the exchange rate aganst the hch s opposte to the aret ee resut anes an o ae sho the resuts or the our nustr portoos hae sgncant an poste oestc aret etas at the ee he erences aong the nustres are not oous th a axu aue or the anuacturng nustr an a nu aue or the transportaton nustr n the “other” nustr portoo shos a negate an sgncant goa aret eta hch s opposte to the aretee ncaton urtherore the anuacturng an transportaton nustres sho sgncant exposures to the rst oent o the exchange rate aganst the ut th erent sgns an respecte hch s not etecte at the aret ee he sar agntues ut erent sgns o the exchange rs exposures n the share aret proa cance each other out at the aggregate ee he oestc aret etas or a our share nustr portoos are sgncant an poste th a nu o or the transportaton nustr an a axu o

the e ette t et the e ette t the te he t ete et et t the et the t t t e ee t ehe t the t ee the the ttt t h te e ee t the ehe te et he t t h ete e ee t ehe te tt hh tet th the etee et e the et e h t t t t e ee t ehe t the t ee ee he hh tt the et t the et ee t t tee tht the t t he ete et th the et et

eete ee et the eete t the ette tet the e et ee te eteethe e t t e h te h the Tae 4. 𝑟𝑟

𝑆𝑆𝑆𝑆𝑆𝑆 𝑟𝑟 𝐶𝐶𝐶𝐶𝐶𝐶 𝑟𝑟 tt 𝑟𝑟 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝐶𝐶𝐶𝐶𝐶𝐶 e 𝑆𝑆 𝑆𝑆 𝑆𝑆𝑆𝑆 / 𝑅𝑅 𝐵𝐵𝐵𝐵𝐵𝐵 /

2 − 𝐵𝐵𝐵𝐵𝐵𝐵

esuts of 𝑟𝑟

𝑓𝑓 − 𝑟𝑟

𝑓𝑓 ,

𝑟𝑟

𝑟𝑟 et 𝑡𝑡𝑡𝑡 𝑓𝑓

𝑡𝑡𝑡𝑡𝑡𝑡 eete

e hee the ee te internationa

𝑟𝑟 𝑟𝑟 𝑚𝑚 𝐶𝐶𝐶𝐶𝐶𝐶 𝑚𝑚𝑚𝑚 Tae 4. esuts of internationa asset pricing mode at the industr ee 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 / 𝐵𝐵𝐵𝐵𝐵𝐵

h te h the share’s exposures to the exchange risk of the denominating exposuresshare’s to the exchange ofrisk the denominatingcurrencies currencies t the t ee hee ee e et e t t

ette the tet et e ee𝑚𝑚𝑚𝑚𝑚𝑚 t e the te e t etee t

𝑟𝑟

t the eete the ee et 𝑈𝑈 t e the he et et

𝑆𝑆𝑆𝑆𝑆𝑆

𝑈𝑈 the eete 𝑒𝑒 e the he et etassetpricing mode the eete the / 𝑖𝑖 𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐵𝐵𝐵𝐵𝐵𝐵 et et / , / , 𝑟𝑟 / e the et e𝑆𝑆 𝑆𝑆𝑆𝑆 ehe𝑟𝑟 te 𝑟𝑟 t et 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑟𝑟

𝑟𝑟 𝑟𝑟 , 𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 ,

ee e the hee ee te eete te e t the eet ee 𝑟𝑟 𝐻𝐻𝐻𝐻𝐻𝐻

𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑈𝑈 𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵 𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑖𝑖 eete 𝑒𝑒

𝑓𝑓 𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡 𝑒𝑒𝑒𝑒 /

𝑟𝑟 𝑟𝑟 𝐵𝐵𝐵𝐵𝐵𝐵

𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟

𝑆𝑆𝑆𝑆𝑆𝑆

et the ee

e et e t t he the

𝑆𝑆 e et the e ehe te e & 𝑆𝑆 𝑆𝑆𝑆𝑆 tt

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑖𝑖𝑖𝑖𝑖𝑖 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒

𝑟𝑟 𝑟𝑟 𝑟𝑟 e 𝑟𝑟 𝑟𝑟 𝑟𝑟 eete （）（）

𝑟𝑟 at the industr ee 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 （

the

（）（）（） 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑓𝑓 & 𝑟𝑟 − 𝑟𝑟 𝑤𝑤

ℎ he et et et he 𝑜𝑜

𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

（）

）

𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑓𝑓 t 𝑟𝑟 − 𝑟𝑟 / （） 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟 / （） 𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆 （（ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 （

（（ 𝑟𝑟 𝑟𝑟 𝑆𝑆 𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠 te e eet t eethe 2 𝑆𝑆 𝑆𝑆𝑆𝑆 he the the eete 𝑅𝑅 𝑖𝑖𝑖𝑖𝑖𝑖

））

）

））

𝑟𝑟 𝑆𝑆𝑆𝑆𝑆𝑆 t 𝑆𝑆 𝑆𝑆 𝑆𝑆𝑆𝑆

the the 𝑟𝑟 𝑡𝑡 （（ 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

t e 𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡

the the 𝑡𝑡

）） 𝑡𝑡

𝑡𝑡𝑡𝑡𝑡𝑡

he etet

tet

hee ee t 𝑟𝑟 𝑟𝑟

𝑜𝑜 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 ℎ 𝑒𝑒

the

Tae Continued4. 𝑟𝑟

𝑆𝑆𝑆𝑆𝑆𝑆 𝑟𝑟 𝑈𝑈 𝑟𝑟 onstant 𝑟𝑟 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑈𝑈 ode 𝑈𝑈 𝑆𝑆𝑆𝑆 / 𝑅𝑅 𝑈𝑈 𝑆𝑆 𝐵𝐵𝐵𝐵𝐵𝐵 / 2

− 𝐵𝐵𝐵𝐵𝐵𝐵

− 𝑟𝑟

𝑓𝑓

𝑟𝑟 𝑓𝑓

𝑟𝑟

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 Tae 4. Continued

ane sset pricing modes for industr portfoios of shares in the ane pricing sset modes for industr portfoios of

ode

onstant 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 （）（𝑟𝑟） 𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟 （）（）

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑓𝑓 𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 （）

𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑓𝑓

𝑟𝑟 − 𝑟𝑟 / （） 𝑈𝑈𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟 /

𝑟𝑟 （） 𝑟𝑟𝑈𝑈𝑈𝑈𝑈𝑈 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟𝑟𝑟 2 & 𝑤𝑤

𝑅𝑅 ℎ 𝑜𝑜 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

𝑟𝑟 𝑠𝑠𝑠𝑠𝑠𝑠 shares i 𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠

n the the 𝑟𝑟 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 （（

𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

）

（（（（（ 𝑟𝑟 𝑜𝑜

ℎ 𝑒𝑒𝑒𝑒

）

））

）

Tae 4

. Contimued 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆 𝑟𝑟 𝐻𝐻

𝐶𝐶𝐶𝐶𝐶𝐶 𝑟𝑟 𝑟𝑟 onstant onstant 𝑟𝑟 𝑟𝑟 𝐵𝐵 𝑎𝑎𝑎𝑎 𝑎𝑎𝑎𝑎 𝐴𝐴 𝐻𝐻 𝐶𝐶𝐶𝐶𝐶𝐶 ode ode 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 𝑎𝑎 𝑎𝑎 / 𝑅𝑅 / 𝑅𝑅 𝐴𝐴 𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵𝐵𝐵 / / 2 2 − − 𝐵𝐵𝐵𝐵𝐵𝐵 𝐵𝐵𝐵𝐵𝐵𝐵

− − 𝑟𝑟 𝑟𝑟

𝑓𝑓 𝑓𝑓

𝑟𝑟 𝑟𝑟 𝑓𝑓 𝑓𝑓

ane pricing sset ane pricing sset modes for industr portfoios of Tae 4. Contimued ane sset pricing modes for industr portfoios of shares in henhen tock arket ode 𝑟𝑟 𝑟𝑟 onstant 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 （ 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑓𝑓 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑛𝑛 𝑓𝑓 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝑓𝑓 𝑟𝑟 − 𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑟𝑟 − 𝑟𝑟 𝑟𝑟 − 𝑟𝑟

）

𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑓𝑓

modes for industr portfoios of

− −

𝑟𝑟 − 𝑟𝑟

𝑟𝑟 𝑟𝑟

𝑓𝑓 𝑓𝑓

𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑓𝑓 𝑟𝑟 /− 𝑟𝑟 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟 / 𝑟𝑟𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵𝐵𝐵𝐵𝐵 𝑟𝑟 𝑟𝑟 2 ane sset pricing𝑟𝑟𝑟𝑟𝑟𝑟 modes for industr portfoios of𝑟𝑟𝑟𝑟𝑟𝑟 shares in henhen tock arket 𝑟𝑟 𝑟𝑟

𝑅𝑅

ode

𝑒𝑒 𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 onstant

𝑟𝑟𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 − 𝑟𝑟𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 − 𝑟𝑟𝑓𝑓 𝑟𝑟𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 − 𝑟𝑟𝑓𝑓 𝑟𝑟𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 − 𝑟𝑟𝑓𝑓

− −

𝑟𝑟 𝑟𝑟 𝑓𝑓 𝑓𝑓

（） 𝑆𝑆𝑆𝑆𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 𝑓𝑓 𝑟𝑟 − 𝑟𝑟

shares in henhen arket tock shares in henhen arket tock 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑓𝑓 𝑟𝑟 /− 𝑟𝑟 𝑟𝑟 𝑟𝑟

𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑟𝑟 /

𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡

𝐻𝐻𝐻𝐻𝐻𝐻 𝐵𝐵𝐵𝐵𝐵𝐵

𝑟𝑟 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

2 𝑡𝑡𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡

𝑛𝑛

𝑅𝑅

− − 𝑟𝑟 𝑟𝑟 𝑓𝑓 𝑓𝑓

𝑟𝑟 𝑟𝑟 𝑜𝑜𝑜𝑜 𝑜𝑜𝑜𝑜 ℎ ℎ 𝑒𝑒𝑒𝑒 𝑒𝑒𝑒𝑒

− −

𝑟𝑟 𝑟𝑟

𝑓𝑓 𝑓𝑓

4. esuts on share discount decomposition mode

his section demonstrates empirica ho exchange risk direct affects share discounts using uations and ane in ae shos the resuts of the short run impact of on share discounts in the he coefficients of the og difference eteen the expected exchange rate and spot exchange rate for a six industries are significant and positie at the ee ranging from for the rea estate industr to for the manufacturing industr ecause the share discounts are represented the og form the numerica aues are negatie n increase in the negatie numer means a decrease in the magnitude of the share discounts n other ords if the is expected to appreciate then the share discounts i ecome smaer n addition the expected returns of the and share generated the asset pricing mode in uations and do not significant affect the share discounts hich is inconsistent ith the theoretica mode in uation ane in ae reports the ongrun resuts using the month exchange rate to measure the expected exchange rate he ongrun resuts reinforce the findings of the shortrun regression he difference eteen the expected exchange rate and spot exchange rate of has a significant and positie impact on share discounts in a six industries portfoios ranging from for the transportation industr to for the manufacturing industr xcept for the rea estate industr, no industries’ expected returns affect the share discounts sing the ongrun expectation from the market the mode can expain the share discounts etter than the mode using the shortrun expectation can he s of the ongrun 2 modes are aout three to four times higher than those of the shortrun𝑅𝑅 modes ane of ae confirms the resuts using the spot and agged exchange returns herefore if the remains strong the exchange rate effects hep to narro the share discounts and consoidate the and share markets ecause the is pegged to the the resuts for the shoud e the same as those of the oeer ae shos unexpected resuts in the o of four expected returns of share industr portfoios hae significant impacts on the share discounts hie no share expected returns affect the share discounts he changes in the exchange rate hae ess oious impacts on the share discounts in the especia for the transportation industr hich is not infuenced the exchange rate change at a he ast coumn of ae een shos the negatie coefficients of the changes to the exchange rate on share discounts his impies that a more fexie exchange rate regime narros the gap

eteen and sare price parit, ain te od etter in te portfoios of serice, oesae, and retai trade copanies e reason te eaes different to te is proa ecause it is easier for inese inestors to ede aainst te excane ris of te tan tat of te oeer, te sortrun and onrun odes in te and ot contain sinificant constants, indicatin tat tere are sti soe eeents affectin te sare discounts ecause tis stud focuses on discoerin te reation eteen excane ris and sare discounts, e do not discuss oter possie reasons ere

excane rateaainst eacindustr of portfoio in te is tae sos ipactste of canete of excane rate aainst and Tae . egression resuts of discountthe mode ln ( 𝐸𝐸

𝑡𝑡 onstant ( 𝛾𝛾 𝑋𝑋 𝑋𝑋 ode − 1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶 𝐸𝐸 𝑅𝑅 − 𝐸𝐸 𝑟𝑟

2 𝑟𝑟 𝐴𝐴 / / 𝛾𝛾 𝐵𝐵 𝐷𝐷

𝑈𝑈𝑈𝑈𝑈𝑈 𝑈𝑈𝑈𝑈𝑈𝑈 2 𝑖𝑖

is te te is , , 𝑡𝑡 𝑡𝑡 + 𝑠𝑠 ) )

sare discount eac of industr portfoio 𝐷𝐷

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

in te

Tae . egression resuts of the discount mode in the 𝑅𝑅

𝑈𝑈𝑈𝑈𝑈𝑈 is tae sos te ipacts of te cane of excane rate aainst 𝐶𝐶𝐶𝐶𝐶𝐶 and and shares’ expected returns on the Bsare discounts ane iscounts reression it ont excane rate

in te is te sare discount of eac industr portfoio in te and indicate te and shares’ expected return 𝑡𝑡 𝑚𝑚

𝑚𝑚

indicates canete of excane rate aainst

/ , 𝐴𝐴 𝐵𝐵 of eac industr𝑖𝑖 portfoio in te ln indicates te difference𝑟𝑟 eteen te𝑟𝑟 expected excane rate and te spot 𝐷𝐷 / , 𝐸𝐸 𝐸𝐸 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡+𝑠𝑠) ln

excane rate aainst , indicates te𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶 cane𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡 of excane rate( aainst ( ) 𝐸𝐸 𝑡𝑡 𝐷𝐷

𝐶𝐶𝐶𝐶𝐶𝐶 ( 𝑋𝑋 𝑋𝑋 𝑟𝑟𝑟𝑟𝑟𝑟 ane iscounts reression it ont excane rate

𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶

𝑈𝑈𝑈𝑈𝑈𝑈 𝑅𝑅

ode 𝑟𝑟 &

/ / 𝑒𝑒 𝑈𝑈𝑈𝑈𝑈𝑈 𝑈𝑈𝑈𝑈𝑈𝑈 𝑒𝑒 onstant 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒

, ,

𝑡𝑡 𝑡𝑡

𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 +

𝑠𝑠

)

) ind

the in 𝐴𝐴 𝐸𝐸𝑟𝑟 icateste difference eteen te expected excane rate and spot te 𝐷𝐷 𝑟𝑟

𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟

𝐵𝐵 𝑟𝑟

−𝐸𝐸 te in / , 𝑟𝑟 ln &

𝑤𝑤

/ , ℎ 𝑡𝑡 𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡+𝑠𝑠 𝐸𝐸 (𝑋𝑋 ) 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

( )

𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡 𝑋𝑋 2

𝑅𝑅

𝐸𝐸

1 2 𝑟𝑟 𝛾𝛾 − 𝛾𝛾 𝐴𝐴

and and

a nd nd 𝐷𝐷

𝑠𝑠𝑠𝑠𝑠𝑠 𝐸𝐸 shares’ expected returns on the B the on returns expected shares’ 𝑟𝑟

𝑠𝑠 𝐵𝐵 𝑠𝑠𝑠𝑠𝑠𝑠

te indicate

𝐷𝐷 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

and and 𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡 𝑡𝑡

𝑡𝑡

𝑡𝑡𝑡𝑡𝑡𝑡

shares’ expectedshares’ return

sare discounts

𝐷𝐷

𝑜𝑜 ℎ

𝑒𝑒𝑒𝑒

Tae . Continued ln ( 𝐸𝐸

𝑡𝑡 onstant ( 𝛾𝛾 𝑋𝑋 𝑋𝑋 ode − 1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶 𝐸𝐸 𝑅𝑅 − 𝐸𝐸 𝑟𝑟

2 𝑟𝑟 𝐴𝐴 / / 𝛾𝛾 𝐵𝐵

𝑈𝑈𝑈𝑈𝑈𝑈 𝑈𝑈𝑈𝑈𝑈𝑈 2

, , 𝑡𝑡 𝑡𝑡 + 𝑠𝑠 ) )

𝐷𝐷 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 Tae . Continued

ane B scounts reresson th onth exchane rate ane B scountsreresson th onth exchane rate ode

onstant 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑣𝑣𝑖𝑖𝑖𝑖𝑖𝑖 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝑟𝑟𝑟𝑟𝑟𝑟

𝐴𝐴

𝑟𝑟 𝐸𝐸 𝑟𝑟

𝑒𝑒 𝐵𝐵 𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟

−𝐸𝐸

/ ,

ln 𝐸𝐸𝑡𝑡(𝑋𝑋𝐶𝐶𝐶𝐶𝐶𝐶/𝑈𝑈𝑈𝑈𝑈𝑈,𝑡𝑡+𝑠𝑠) ( 𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝑡𝑡 ) 𝑋𝑋 2 𝐷𝐷

𝑅𝑅 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 1 2 𝛾𝛾 − 𝛾𝛾 𝑟𝑟𝑟𝑟 &

𝑤𝑤 ℎ 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

𝐷𝐷 𝑠𝑠𝑠𝑠𝑠𝑠 𝑣𝑣 𝑖𝑖𝑖𝑖𝑖𝑖

𝐷𝐷 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝐷𝐷

𝑜𝑜 ℎ

𝑒𝑒𝑒𝑒

Tae . Continued

onstant 𝑅𝑅 𝑅𝑅 𝑅𝑅 𝑅𝑅 𝛾𝛾 ode 𝑅𝑅 𝑈𝑈𝑈𝑈𝑈𝑈 𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝐶𝐶𝐶𝐶𝐶𝐶 𝑈𝑈𝑈𝑈𝑈𝑈 𝐶𝐶𝐶𝐶𝐶𝐶 − 1 𝐸𝐸 𝑈𝑈𝑈𝑈𝑈𝑈 𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅 − 𝐸𝐸 𝑟𝑟 2 𝑟𝑟 𝐴𝐴 , , , , 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡

𝐵𝐵 𝛾𝛾

− − − − , 𝑡𝑡 2

4 3 2 1

𝐷𝐷

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

Tae . Continued

ane scount reresson on the spot and aed exchane return

ode

ane s

onstant 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝑟𝑟𝑟𝑟𝑟𝑟 𝐴𝐴 𝑟𝑟

𝐸𝐸 𝑟𝑟 count reresson on the spot and aed exchane return

𝑒𝑒 𝑒𝑒 𝐵𝐵 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒

𝑟𝑟

−𝐸𝐸

, 𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅 𝑡𝑡 𝑈𝑈𝑈𝑈𝑈𝑈,

𝐶𝐶𝐶𝐶𝐶𝐶 𝐷𝐷 𝑡𝑡−1

𝑅𝑅 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑈𝑈𝑈𝑈𝑈𝑈,

𝑟𝑟𝑟𝑟 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡−2 & 𝑅𝑅𝑈𝑈𝑈𝑈𝑈𝑈 𝑤𝑤

, ℎ 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

𝐶𝐶𝐶𝐶𝐶𝐶

𝑡𝑡−3

𝑅𝑅

𝑈𝑈𝑈𝑈𝑈𝑈

𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡−4 𝑅𝑅𝑈𝑈𝑈𝑈𝑈𝑈 2 𝑅𝑅 1 2

𝛾𝛾 − 𝛾𝛾 𝐷𝐷

𝑠𝑠𝑠𝑠𝑠𝑠 𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠

𝐷𝐷

𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝐷𝐷

𝑜𝑜 ℎ

𝑒𝑒𝑒𝑒

expected return each o ndustr portoo dscounts hs tae shosthe pactso the chane o exchane rate aanst and Tae egression . resuts of discountthe mode in the

n the the n onstant 𝑅𝑅 𝑅𝑅 𝑅𝑅 𝑅𝑅 𝛾𝛾 ode 𝑅𝑅 𝐻𝐻𝐻𝐻𝐻𝐻 𝐶𝐶𝐶𝐶𝐶𝐶 𝐻𝐻𝐻𝐻𝐻𝐻 𝐻𝐻𝐻𝐻𝐻𝐻 𝐻𝐻𝐻𝐻𝐻𝐻 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶 − 1 𝐻𝐻𝐻𝐻𝐻𝐻 𝐸𝐸 𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅 − 𝐸𝐸 𝑟𝑟 2 𝑟𝑟 𝐴𝐴 , , , , 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡

𝛾𝛾 𝐵𝐵

− , − − − 𝑡𝑡 2

3 2 1

𝐷𝐷 𝑖𝑖

Tae . egression resuts of the discount mode in the B the s hs tae shos the pacts o the chane o exchane rate aanst and and Bshares’ expected returns on the Bshare dscounts n the s the Bshare dscount o each ndustr portoo n the and ndcate the and Bshares’

expected return o each ndustr portoo n the ndcates the chane o exchane rate aanst 𝑖𝑖 , share dscount oeach ndustr portoo 𝑟𝑟𝐴𝐴 𝑟𝑟𝐵𝐵 𝐷𝐷 𝐷𝐷 𝐸𝐸 𝐸𝐸

𝐶𝐶𝐶𝐶𝐶𝐶 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 ode

𝑡𝑡

𝐻𝐻𝐻𝐻𝐻𝐻

𝑅𝑅

onstant

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 the n 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝐷𝐷 𝐷𝐷 𝐷𝐷 𝐷𝐷

𝑚𝑚

𝐴𝐴 𝐸𝐸𝑟𝑟 𝐵𝐵 −𝐸𝐸𝑟𝑟 𝑅𝑅 𝐻𝐻𝐻𝐻𝐻𝐻 𝐶𝐶𝐶𝐶𝐶𝐶 , ,

𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 𝑅𝑅 𝑡𝑡 ndcates the chane o exchane ra 𝐻𝐻𝐻𝐻𝐻𝐻, 𝐷𝐷

𝑟𝑟𝑟𝑟𝑟𝑟

𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡−1

𝑅𝑅

𝐻𝐻𝐻𝐻𝐻𝐻, 𝑟𝑟

𝑒𝑒

𝐶𝐶𝐶𝐶𝐶𝐶 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒

𝑡𝑡−2 𝑅𝑅

𝐻𝐻𝐻𝐻𝐻𝐻

𝐶𝐶𝐶𝐶𝐶𝐶

𝑡𝑡−3 𝑅𝑅𝐻𝐻𝐻𝐻𝐻𝐻 , n the 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡−4 𝑅𝑅𝐻𝐻𝐻𝐻𝐻𝐻 2 𝑅𝑅

1 2 B and

𝛾𝛾 − 𝛾𝛾

𝐷𝐷 𝐸𝐸 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑟𝑟

𝐴𝐴

shares’ expected ret expected shares’ and and 𝑡𝑡𝑡𝑡 𝑡𝑡 𝑡𝑡

𝑡𝑡

te aanst

𝐸𝐸

𝑡𝑡

𝑟𝑟 𝑡𝑡 𝐵𝐵

ndcate the urns on the B urns on the

𝐷𝐷

and B and 𝑜𝑜𝑜𝑜

ℎ

𝑒𝑒𝑒𝑒

shares’

share share

hs std estates the pact the exchae rs share dscts deep a estat de t decpse the aat dereta t t cpets ae the derece etee the expected tre exchae rate ad spt exchae rate ad the derece etee the expected retrs the ad shares hch th cta exchae rs prca tests d that ad rea exchae rates d atter r the share arets the ad at the aret ee eer the rea exchae rate des t aect the expected retrs shares ether the stc exchaes he rests dcate that the apprecates the expected retr the shares crease ce a apprecat aes hese exprts re cpette t creases the prt csts r hese cpaes e psse expaat r ths rest s that st cpaes ss shares are prt reted rather tha exprtreted hs aes sese ecase cpaes sse shares t rase re crrec the perd strct crrec ctr dcat that the ac re crrec t prt ds r ther ctres he aret dex reresss as sh that hher ad rea exchae rate att decreases the share expected retr he rest s ctrar t that ha hch states that there exsts a terreat etee the exchae rate ad the hese share aret t sch reat etee the exchae rate ad the hese share aret eer at the dstr ee the expsre t ad exchae rss eces ess s e the rests at the areate aret ee thh t s dct t detect a cear patter pacts rea exchae rates share dscts thrh ad share expected retrs t s te eas t detere h chaes the ad exchae rates aect share dscts ased ths aass estrs expect a str tre the the share dscts dece hs ccs s cred the r ad the shrtr rests th stc exchaes ecet there has ee ch deate at terataat he hese eret s tr t prte exchae rate rers t trasr the t a a crrec addt accrd t the etar thrt crssrder trade cdcted thrh reached t hs the exchae aret ad stc aret shd e rther cterated tre he exchae rs e re cse asscated th the share dscts ecase the hese eret s ccered at csdat the ad share

arets t s ea r pcaers t derstad h exchae rs aects the share dscts

der as terata prt chce ad crprat ace sthess , der as xpsre t crrec rs et ad easreet , 1 hd edes sset prc ad the das spread , 1 rstr ar e xchae rs ad ersa retrs test terata artrae prc ther , 0 ae h es the a e prce hd etter der a exe exchae rate sste , 1 ae s ad retr chas e stc arets e prear edece , – ae h a re ershp restrcts ad et prce pres hat dres the dead r crssrder estets , ae ata re ershp restrcts ad stc prces the ha capta aret , a h he seess ears ad ae r et aat eer capta arets dece r sted cpaes the pepes repc ha , 10 r aa re exchae rs th derates , 0 haraart arar rat asetr aret seetat ad the prc crsssted shares her ad edece r hese ad shares , , – he ee re ershp restrcts ad aret seetat chas stc arets , arrat e h the hese share prce dsct pe e e edece ,

, 1 , , 0 , , , , 1 , , , , , , 1

1T F F T

1 T F F T

T T TF T F . 200 to . 2011. 2 CT TTTC F

2 CT TTTC F T F

T T TF T F . 200 to . 2011. - - - 29.46369 3.33248 0.206331 11.66433 0.009347 2.918080 31.86912 𝑟𝑟 314 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎

-0.009347 0.142575 0.310863 0.343193 0.117356 0.036802 0.041529 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑟𝑟𝑟𝑟𝑟𝑟 0.206331𝑟𝑟 0.298542𝑟𝑟 0.467446𝑟𝑟 0.889464𝑟𝑟 0.432435𝑟𝑟 0.018754𝑟𝑟 0.04240 - - 4.290402 0.298542 13.93059 4.174939 0.142575 𝑟𝑟 14.92355 0.115056 0 𝑆𝑆𝑆𝑆𝑆𝑆

11.66433 289 13.93059 22.08026 15.54350 12.00533 0.096802 0.06520 𝑆𝑆

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 0

-31.86912 -14.92355 -18.16935 -16.65565 -15.99497 0.000000 0.018500

3.332482 4.174939 5.383561 4.726642 4.421603 0.038143 0.015745 22.08026 - 5.032944 0.023016 0.467446 0.310863 5.383561

-2.918080 -0.115056 0.023016 𝑟𝑟 -0.373305 -0.368815 0.375748 0.070937 18.16935 𝑆𝑆𝑆𝑆𝑆𝑆 29.46369 289 4.290402 5.032944 4.137814 3.994542 1.385263 1.603470

𝑆𝑆

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

314 289 289 287 287 302 315

- 0.889464 4.726642 0.343193 15.54350 4.137814 0.373305 𝑟𝑟 16.65565 𝑆𝑆𝑆𝑆𝑆𝑆 287

𝑆𝑆

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

T F

- - 0.432435 3.994542 4.421603 12.00533 0.117356 0.368815 𝑟𝑟 15.99497 𝑆𝑆𝑆𝑆𝑆𝑆 287 𝑆𝑆

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

0.000000 0.096802 0.03 0.038143 0.375748 0.018754 1.385263 𝑟𝑟 302 𝑡𝑡𝑡𝑡 6802

𝑡𝑡𝑡𝑡𝑡𝑡

0.018500 0.070937 0.041529 1.603470 0.015745 0.04240 0.06520 315 𝑟𝑟 0 0 𝑟𝑟𝑟𝑟

. .

. - . 2005 .2011 𝑟𝑟 𝑟𝑟 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 - 8.484944 0.546904 - 30.87836 0.796598 0.429522 4.903795 - 0.401393 18.10684 4.881186 5.590179 0.914191 0.674324 20.16663 14.23111 & 314 0.401393 0.382446 314 0.424106 0.242495 0.275730 0.567821

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟𝑟𝑟 𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑟𝑟𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑟𝑟 𝑟𝑟𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒

0.914191 0.495016 0.752674 0.770906 0.852433 1.091387

18.10684 21.84201 17.36507 17.39738 16.94904 19.16131

-20.16663 -23.64845 -21.23338 -15.48784 -20.83732 -22.03493 . . 5.590179 6.426094 5.720642 4.993134 5.450748 6.318317 - 𝑟𝑟 5.680892 - - 𝑟𝑟 0.576294 5.883410 0.455016 23.56331 0.382446 6.426094 23.95362 𝑟𝑟𝑟𝑟𝑟𝑟 0.495016 0.11197 4.548375 21.84201 23.64845 -0.674324 -0.106232 -0.4226170.10623 -0.385208𝑟𝑟𝑟𝑟𝑟𝑟 -0.616371 -0.621979 314 𝑟𝑟

4.881186 4.548375 314 3.923374 4.193118 4.521495 4.166839 𝑟𝑟

𝑒𝑒

𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒

314 314 - 314 314 314 314 - 2

. - .2005 .2011

𝑟𝑟

& 𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 - - - 4.967784 0.293144 0.575790 21.96878 0.61168 0.424106

0.429522 0.455016 0.5757905.720642 0.333757 0.290918 0.567656 3.923374 0.752674 5.421741 17.36507 16.50635 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑤𝑤0.422617 ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜21.23338 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝑟𝑟𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟 𝑟𝑟𝑟𝑟 𝑟𝑟 𝑟𝑟

0.546904 0.576294& 0.611684 0.490872 0.529720 0.658331 314 & 314 𝑤𝑤 𝑤𝑤

30.87836 23.56331ℎ 21.96878 22.65812 31.37718 28.93218 ℎ 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

71 -14.23111 -23.95362 -16.50635 -16.92860 -18.37283 -19.49301 4

. . 4.903795 5.883410 5.421741 4.840236 5.040122 5.712904

0.796598 0.111975 0.293144 -0.013823 0.569306 0.377798

8.484944- 5.680892 4.967784 5.865714 8.845198 7.004209 - 4.840236 0.490872 22.65812 0.333757 5.865714 0.013823 16.92860 - - 𝑟𝑟 0.770906 0.242495 4.993134 17.39738 0.385208 4.193118

15.48784 𝑠𝑠𝑠𝑠𝑠𝑠 𝑟𝑟 314 𝑠𝑠𝑠𝑠𝑠𝑠 314 314 314 314 314 314 314

𝑠𝑠 𝑠𝑠𝑠𝑠𝑠𝑠

𝑠𝑠

𝑠𝑠𝑠𝑠𝑠𝑠

.2005 .2011 .2005 .2011 𝑟𝑟 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 - 0.569306 0.529720 0.290918 8.845198 5.040122 31.37718 18.37283 𝑟𝑟 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 - - 0.852433 5.450748 16.94904 0.275730 4.521495 314 20.83732 𝑡𝑡 0.616371 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

314 𝑡𝑡

𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

- 7.004209 0.567656 28.93218 0.377798 0.658331 5.712904 19.49301 - - 4.166839 0.567821 1.091387 6.318317 22.03493 0.621979 19.16131 314 𝑟𝑟 𝑟𝑟 𝑜𝑜 𝑜𝑜 314

ℎ ℎ

𝑒𝑒𝑒𝑒

. . . . . .

. - . 2005 .2011

0.394185 0.361124 0.111367 0.442204 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 𝑟𝑟 0.641918 𝑟𝑟0.704420 𝑟𝑟 0.428885 1.156037𝑟𝑟

16.60844 𝑟𝑟 18.36154 𝑟𝑟 22.77861 18.57818 - 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 - - - 0.378568 0.378867 16.60844 0.394185 4.650871 4.815369 0.641918 18.26759 4.757347 4.351379 0.048091 16.39244 0.476145 -16.3924416.50414 -20.64961 -18.39946 -19.85504

. . 314 4.815369 314 5.528080 4.870397 5.808653

-0.476145 -0.358202 -0.042201 -0.307759

4.351379 4.004903 4.978085 4.160049

- - 314 314 . 2005 .2011 314 314 . - . 2005 .2011

- 𝑟𝑟 3.850864 0.762289 5.378204 0.375399 - 17.25968

0.231206 0.378867 𝑟𝑟𝑟𝑟𝑟𝑟 0.375399 0.035430 0.538882 15

𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 - 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑟𝑟 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒 - 4.004903 5.528080 0.704420 0.361124 18.36154 0.358202 𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟 𝑟𝑟 20.64961 𝑟𝑟 𝑟𝑟 314

0.378568.47115 0.762289 0.181519 0.617280 𝑟𝑟

𝑒𝑒

314 𝑟𝑟

18.26759 17.25968 12.98574 20.05468 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒

𝑒𝑒

-16.50414 -15.47115 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 -16.86777 -15.95960

. . 4.650871 5.378204 4.287564 5.559875

-0.048091 -0.231206 -0.247013 0.032022 4.757347 3.850864 4.089824 3.992854

𝑟𝑟

314 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 314 314 314 - 4.089824 - 0.035430 𝑟𝑟 4.287564 12.98574 0.181519 0.247013 16.86777 . 2005 .2011 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 - - 0.428885 4.978085 4.870397 22.77861 0.042201 0.111367 18.39946 314 𝑡𝑡𝑡𝑡

314 𝑡𝑡𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝑡𝑡𝑡𝑡𝑡𝑡

𝑡𝑡

- - - 0.032022 20.05468 0.538882 0.442204 3.992854 0.617280 5.808653 4.160049 5.559875 18.57818 1.156037 15.95960 0.307759 19.85504 𝑟𝑟 𝑟𝑟 𝑜𝑜𝑜𝑜 𝑜𝑜𝑜𝑜 314 314 ℎ ℎ

𝑒𝑒𝑒𝑒 𝑒𝑒𝑒𝑒

mpact of short seing on share discounts in the Chinese stoc maret

ǂ 2016

stract - - - . . .

31 44 12 14 - - .

ǂ 16 287 65100 - ,

1 TCT

. - . . - 1977 1987 2003 2003. - - - 2002 2011 2014. 2009. . . 84 - - - .. . - - . - -. . . 2009 - 20 - - . - - . .. - 31 2010 . 2015 30 84 -listed firms’ A- . - . - - . - .

rt selli is still riited i te sre mret d te eir f sres sld miti te sme tter s te etee A d sres is eeted t rr is lifti f te srtselli rided rre trl eerimet t iestite te imt f srt selli te seltie le irst te srt selli d mri trdi s lifted erit fr sset f sts is std determies eter d te srtselli strit trites t te Asre erlti i te srt term emii te e i te sre dist efre d fter te ed dil srtselli mritrdi d te ssited er trdi lme dt re lil ille t te idiidl st leel i te iese mret te mret l mtl srt iterest dt re serle st stdies te mret l emie te rete effet f srt selli t te mret leel is std rides rtit t iestite te relti etee sre dists d srtselli tiit te rsssetil d timeseries dimesis t trites t te itertil litertre ridi dditil eidee f te imt f srtselli strits te emeri mret ere re fe stdies te effets f srtselli i emeri mrets ee t srtselli strits re mre idi i emeri mrets t te re i deeled mrets

2 TT T T

When the market price is lower than the stock’s fundamental value, an informed investor may take a leveraged long position by borrowing capital from a broker (margin trading) or from other sources. In contrast, a leveraged short position is built by selling borrowed stocks, if the investor does not own that stock. However, short-selling activities are usually prevented by law, a lack of stock lenders, or too high lending fees. The difficulty of going short is referred to as short-selling constraints. In a static setting, if short-selling constraints and a sufficient divergence of opinions exist simultaneously, the market price of a risky asset is upwardly biased by optimistic investors, because pessimistic investors are prevented from shorting the overvalued asset (Miller, 1977). In a dynamic setting, a risky asset’s price will be even higher than the most optimistic investor’s assessment of its fundamental value (Harrison & Kreps, 1978; Scheinkman & Xiong, 2003). Investors expect to resell the asset at a higher price to more optimistic investors in future. Thus, they pay more than their expectations of the asset’s fundamental value. This causes a speculative bubble in the market price.

Harrison & Kreps (1978) further state that once the short-selling constraints are relaxed, speculation trading may still exist, but that the speculative bubble may not be clearly visible. In other words, short selling could diminish the speculative bubble. However, Lamont and Stein (2004), using data on aggregate short interests in the U.S. stock market, conclude that short selling does not play a particularly helpful role in stabilizing the overall stock market. Controversially, Autore et al. (2011) find that the 2008 short-selling ban in the U.S. stock market caused positive abnormal returns when the ban was put in place, and a reversal when the ban was lifted. Mei, Sheinkman and Xiong (2009) argue that it is complicated to test whether a speculative bubble is induced by short-selling constraints directly, owing to the difficulty in measuring the fundamental values of stocks. This could be why previous literature found controversial results. They suggest using the price difference of dual-listed companies in the Chinese stock exchanges to control for the fundamental value. Using this unique data set, they conclude that A-share investors’ speculative trading leads to B- share discounts, because of the presence of stringent short-selling constraints and heterogeneous beliefs. Similar to the A- and B-share markets, some cross-listed Chinese companies issue A-shares on mainland China’s stock markets (the SSE or the SZSE) and H-shares on the Hong Kong Stock Exchange. H-shares are also traded at a discount, on average. Wang and Li (2009) find a negative correlation between short-selling transactions in the Hong Kong market and H-share price discounts. This study further confirms that short-selling constraints in the A-share market and divergent opinions among A-share investors are the main reasons behind A-share premiums (also called H- share discounts). In March 2010, China launched a pilot scheme to lift the ban on short selling and margin trading in the A-share market for a designated list of stocks. Short sellers trade to eliminate overpricing by selling stocks with higher contemporaneous returns following a downward trend (Chang et al., 2014). However, this policy change did not include the B-share market. Thus, lifting the short-selling constraints in the A-share market should fill the gap between A- and B-share prices. Hence, the first hypothesis is expressed as follows.

Hypothesis 1: The B-share discounts of pilot stocks decrease following the lifting of the short-selling ban.

Several previous studies assume that short sellers are more rational and able to explore market mispricing (Miller, 1977; Harrison & Kreps, 1978; DeBondt & Thaler,

1985; Diamond & Verrecchia, 1987; Barberis, Shleifer & Vishny, 1998; Hong & Stein, 1999; Scheinkman & Xiong, 2003). The China Securities Regulatory Commission (CSRC) put in place stringent requirements for investors wishing to engage in short selling and margin trading. This was mainly to guarantee that such investors are more mature and have more capital relative to ordinary individual investors. However, short selling is relatively new to Chinese investors, and many institutional investors are not allowed to conduct short selling or margin trading in China. When B-share discounts increase, the amount of mispricing becomes larger. As rational investors, short sellers should try to make the prices converge by taking short positions on A-shares. Thus, it is worth examining whether Chinese short sellers are sophisticated investors with a strong willingness to correct the market. Hence, the second hypothesis is stated as follows.

Hypothesis 2: Increases in the B-share discounts of pilot stocks induce a higher short- selling turnover.

Even though short sellers should be informed investors, short selling is still highly risky (Lamont, 2012). Lamont and Stein (2004) find that arbitrageurs are reluctant to bet against aggregate mispricing using basic data on the evolution of aggregate short interest. In the U.S. stock market, only monthly short interest data are publicly available, which is not accurate enough to measure short-selling activities. However, the Chinese stock market announces short-selling trading volumes, margin-trading volumes, and associated cover trading volume data on every trading day. Daily A-share short-selling data, together with the dual-class stock structure provides an ideal data set to investigate how the speculative bubble changes along with short selling activities. This study checks whether Chinese short sellers are able to correct mispricing. Hence, the third hypothesis is stated as follows.

Hypothesis 3: B-share discounts of pilot stocks are negatively correlated with short- selling activities.

Overall, short-selling activities should decrease the overvaluation of A-share prices so that B-share discounts decrease, based on Miller’s disagreement model (1977). However, Baker & Wurgler (2007) find that stock prices are also associated with investor sentiment. When investor sentiment is booming, the speculative component of the stock price is larger. The speculative bubble in A-share prices accounts for more of the B-share discounts. Short selling may play a greater role in correcting B-share discounts. When

investor sentiment is low, the speculative bubble in A-share prices is small. B-share discounts are mainly caused by reasons other than the speculative bubble. With the up- tick rule, short sellers are even more restricted. Thus, the impact of short selling in bearish periods could be weakened. Owing to a lack of data measuring Chinese investors’ sentiment, this study examines the impacts of short selling on B-share discounts in bullish and bearish market sample periods to test whether investor sentiment affects the impact of short selling on price corrections. Therefore, the fourth hypothesis is as follows.

Hypothesis 4: The price correction effect of short selling on B-share discounts is more obvious during Bearish market sample periods.

T T

This section discusses the lifting of the ban on short selling and the data set, as well as the methodology used to test the hypotheses.

.1 ata

To support the development of the country’s finance market, Chinese securities regulators decided to promote short selling and margin trading in the Chinese stock market in March 2010. This policy shift targeted the A-share market only and advanced gradually. Sections 3.1.1 and 3.1.2 state the reform process and the data features of short selling and B-share discounts. Section 3.1.3 discusses the control variables, which may also affect the B-share discount variations.

.1.1 hort seing

On March 31, 2010, the SSE and the SZSE allowed 11 top brokerage firms in China to buy eligible stocks on margin and/or short sell those stocks according to detailed implementation rules. Only 90 stocks on the SSE 50 Index and the SZSE Component Index have been designated by the CSRC as eligible for short selling and margin trading. On November 25, 2011, the designated list of stocks was expanded from 90 stocks to 278 stocks, which appear in the SSE 180 Index and the SZSE 100 Index, as well as seven ETFs. At the same time, in order to facilitate the short-selling and margin-trading activities, on October 28, 2011, the SSE, the SZSE, and the China Securities Depository and Clearing

Corporation Limited jointly founded the China Securities Finance Co., Ltd as a financial institution specializing in providing margin financing loan services and borrowing shares. Since then, the CSRC announced that short selling and margin trading have become a permanent feature of the Chinese stock market. Regulators subsequently expanded the list of eligible stocks three times, on January 25, 2013, September 6, 2013, and September 12, 2014. As of February 10, 2015, there were 900 stocks and 15 ETFs eligible for short selling and margin trading in the two major exchanges in mainland China. Appendix 1 shows the timeline of this reform process. By the end of January 2015, 30 dual-listed companies’ A-shares (about 40% of dual- listed companies) in the SSE and the SZSE were eligible for short selling and margin trading. Appendix 2 shows these cross-listed companies. In order to prevent excessive speculation, the CSRC introduced the “up-tick rule,” which states that the short-selling price has to be no less than the current market price. Naked short selling is strictly prohibited. These rules were set to reduce the chance of short selling putting downward pressure on the market, but they also increase the difficulty of correcting overpricing. In addition, the CSRC put requirements in place for investors engaging in margin trading or short selling, while brokerage firms can make some adjustments based on the CSRC basic rules.1

1 Based on the CSRC regulation, “qualified” investors must satisfy the following reuirements 1 investors have a trading history longer than half a year, with capital of no less than RMB 500,000 2 investors have low bankruptcy risk, without bad trading records 3 investors cannot be shareholders or related parties of the security company and an investors’ fund for transaction settlement must be placed in the third party account.

Tae 1. position (%) Average covering margin turnover of daily position margin of volume Average dailycovering Average turnover daily margin purchase (%) Average d position (%) short turnoverof Averagecovering daily ofAverageshortpositions dailycovering volume Averageshort turnoverdaily (%) shortvolume Average daily stocks ofeligible No. . henhen changeane toc position (%) Average covering margin turnover of daily position margin of volume Average dailycovering Average turnover daily margin purchase (%) Average volume daily margin purchase position short turnoverof Averagecovering daily Average of volume position daily covering short shortturnoverAverage daily shortvolume Average daily stocks ofeligible No. . hanghaitocane change

aily margin purchase volume aily margin purchase ummar statistics forshort seing

Tae 1. ummar statistics for short seing and margin trading actiities

3312010-12042011 12052011-1302013 1312013-9152013 9162013-9212014 9222014-1302015

ane . hanghai toc change

No. of eligible stocks 1 3 14 1

Average daily short volume 0.00 6650.01 129203.90 1415.50 50643.30 2.94 52166.4 3.04 55492.50 0.2 141. 0.2 19269.3 1 0.3 22031. 0.41 29065.15 0.00 0.00 0.00 0.00 1 3312010 Average daily short turnover 0.00 0.5 0.52 0.5 0.0

Average daily covering volume of short position 0.00 65930. 1263.00 1410.20 50532.0

Average daily covering turnover of short

0.00 0. 0.51 0.5 0.0 - and margin trading actiities 12042011

position

Average daily margin purchase volume 29065.15 314360.00 12230932.00 24001064.00 03224.00 Average daily margin purchase turnover (%) 0.41 .40 13.21 1.5 21.60 Average daily covering volume of margin

4.95 430259.00 5.3 5295650.00 1.39 1164.10 1.41 119212.30 22031.6.0 21100.00 .40 314360.00 0. 21100.0065930. 0.5 6650.01 3 12052011 1053060.00 22534.00 6604335.00

position

Average daily covering turnover of margin 0.3 6.0 11.3 1.69 20.55 position (%) 0

ane . henhen toc change

No. of eligible stocks 1 1302013 11 11 13 Average daily short volume 19269.3 119212.30 425.30 619236.10 102916.00 Average daily short turnover (%) 0.2 1.41 1.9 2.02 1.34

Average daily covering volume of short positions 141. 1164.10 412.00 6145.20 102995.00 11.06 2003396.00 11. 220221.00 1.9 412.00 1.9 425.30 11 11.3 1053060.00 13.21 12230932.00 0.51 1263.00 0.52 12920 1312013

Average daily covering turnover of short 0.2 1.39 1.9 2.02 1.35

position (%)

3.90 -

Average daily margin purchase volume 55492.50 5295650.00 9152013 220221.00 26630.00 6940.00

Average daily margin purchase turnover (%) 3.04 5.3 11. 16.15 1.35 Average daily covering volume of margin 52166.4 430259.00 2003396.00 2600634.00 65953.00 position Average daily covering turnover of margin

16.55 2600634.00 16.15 26630.00 2.02 6145.20 2.02 619236.10 11 2.941.69 22534 1.5 24001064.00 0.5 4.951410.20 0.5 1415.50 14 9162013 11.06 16.55 1.6 position (%)

.00

9212014

1.6 65 1.35 6940.00 1.35 102995.00 1.34 102916.00 13 20.55 6604335.00 21.60 03224.00 0.0 50532.0 0.0 50643.30 1 9222014

953.00

1302015

Table 1 reports the summary statistics for short-selling, margin-trading, and cover trading activities. The trading volumes of short selling and margin purchases are taken from the overall sample. However, in contrast to the rapid increase in margin-trading turnover (on average 12.038% in the SSE and 10.958% in the SZSE), short selling does not account for a high proportion of all trading volumes (0.62% in the SSE and 1.368% in the SZSE, on average). This shows that margin trading is much more popular than short selling in the Chinese stock market. The size of the corresponding cover trading of short selling and margin purchases is similar to the short selling and margin purchases themselves in both markets. Following Lamont and Stein’s study (2004), short selling is measured as the shares sold short by public investors divided by total trading volume:

, , = , (1) , 𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴 𝑖𝑖𝑖𝑖 𝑖𝑖 𝑡𝑡 𝑆𝑆𝑆𝑆𝑆𝑆 𝐴𝐴 𝑖𝑖𝑖𝑖 where the short-selling turnover, , , is𝑉𝑉 the daily short-selling volume for stock i at time t, , , scaled by the total𝑆𝑆𝑆𝑆𝑆𝑆 A-share𝑖𝑖 𝑡𝑡 trading volume, , . 𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴 𝑖𝑖𝑖𝑖 𝑉𝑉𝐴𝐴 𝑖𝑖𝑡𝑡 .1.2 share discounts

The B-share discount is expressed as

/ , = 100 , (2) , 𝐴𝐴 𝐵𝐵 𝑃𝑃𝑖𝑖𝑖𝑖 − 𝑃𝑃𝑖𝑖𝑖𝑖 𝑋𝑋𝑀𝑀 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 𝐷𝐷𝑖𝑖 𝑡𝑡 ∗ ( 𝐴𝐴 ) 𝑃𝑃𝑖𝑖𝑖𝑖 where , , and , denote the A- and B-share price and the B-share discount of 𝐴𝐴 𝐵𝐵 a company𝑃𝑃𝑖𝑖𝑖𝑖 i at𝑃𝑃𝑖𝑖 𝑖𝑖time t, respectively,𝐷𝐷𝑖𝑖 𝑡𝑡 and / , is the exchange rate of USD or HKD against CNY at time t. 𝑋𝑋𝑀𝑀 𝐶𝐶𝐶𝐶𝐶𝐶 𝑡𝑡 On average, B-shares are 47.2% (43.69%) cheaper than A-shares in the SSE (in the SZSE) during the overall sample period. Figure 1 compares the dynamic behavior of the equal-weighted cross-sectional mean of B-share discounts allowed for short selling and margin trading relative to the cross-sectional mean of all cross-listed companies’ B-share discounts. This shows that, for the period April 2009–January 2015, the gap between shares allowed for short selling and margin trading and all cross-listed shares widened relative to the period January 2008–March 2009. This circumstantial evidence implies that short selling may decrease the speculative bubble in the A-share price so that B-

share discounts decrease. Even though the short-selling ban was lifted in March 2010, the media and investors had been expecting the policy change on short selling since March 2009. The cross-sectional mean of B-share discounts in the SSE declined from 50.50% (53.25% in the SZSE) during the period when short selling was prohibited to 46.04% (39.27% in the SZSE) after the ban was lifted. The t-test shows a significant decline in B- share discounts in both stock exchanges after the policy change.

30 08 09 10 11 12 13 14

All Short-Margin Figure 1. The euaeighted crosssection mean of share discounts in the The red line presents the eual weighted cross-sectional mean of B-share discounts allowed for short selling and margin trading. The blue line demonstrates the eual weighted cross-sectional mean of all cross-listed companies’ B-share discounts. 65

25 08 09 10 11 12 13 14

ALL Short-Margin Figure 1. The euaeighted crosssection mean of share discounts in the The red line presents the eual weighted cross-sectional mean of B-share discounts allowed for short selling and margin trading. The blue line demonstrates the eual weighted cross-sectional mean of all cross-listed companies’ B-share discounts.

.1. Contro ariaes

Amihud and Mendelson (1986) explain that investors ask for higher expected returns on relatively illiquid shares to compensate for increased trading costs. The B- share market was strictly restricted for domestic investors in mainland China before February 28, 2001. B-shares were extremely illiquid relative to the corresponding A- shares (Chen, Lee & Rui, 2001). After February 28, 2001, because the B-share market is also open to domestic investors, the liquidity of B-shares increased tremendously. However, the B-share market remains less liquid after the lifting of the market segmentation, even though it has increased (Darrent, , Wu & Zhong, 2010). Following Darrent et al. (2010), turnover is used as a proxy for liquidity, which is defined as the daily trading volume of a stock divided by . Table 2 shows that the average daily turnover of B-shares was 0.612% (for A-shares, 2.327%) period before the lifting of the short-selling ban, but decreased to 0.409% (for A-shares, 1.410%) after the ban was lifted. After security regulators lifted the short-selling ban, both A- and B-share turnovers declined significantly (with a t-statistic of -41.714 for the A-share turnover and -36.614 for the B-share turnover). The decrease in A-share turnover is consistent with the inference that allowing short selling in the A- share market can effectively reduce irrational speculating transactions caused by immature investors in the A-share market. Surprisingly, short-selling activities in the A- share market also effectively reduce the trading turnover in the B-share market. Short- selling investors are more informed in the A-share market (Chang et al., 2014). Thus, B- share investors may take short selling as a signal and follow short sellers’ trading activities. It is noticeable that the gap between A- and B-share turnovers is significantly narrower, down from 1.678% to 0.980% (with t-statistic -37.853). However, B-shares are still less liquid in comparison to their corresponding A-shares (t-statistic -45.007). As more domestic investors enter the B-share market, the number of foreign investors holding B-shares declines, domestic retail investors drive B-share prices, and the ownership structure of B-shares becomes more diversified (Ji, 2006). As the mutual fund market develops, social security funds and more QFIIs enter the Chinese stock market. The structures of investors in the A- and B-share markets become similar. As a result,

trading behaviors become more similar in the A- and B-share markets. Mei et al. (2009) state that heterogeneous beliefs are more likely to arise in firms with greater fundamental uncertainty. Thus, speculative components in these stock prices are larger than in those stocks with lower fundamental uncertainty. The firms with greater fundamental uncertainty are also expected to have higher B-share discounts. Following Mei et al. (2009), the fundamental uncertainty is measured using the idiosyncratic volatility of the stock returns. Idiosyncratic volatility is calculated as

( , , ) , with denoting the daily excess return of stock i, , is the 𝑒𝑒 𝑒𝑒 2 𝑒𝑒 market𝑟𝑟𝑖𝑖𝑖𝑖 − 𝛽𝛽𝑖𝑖 beta𝑡𝑡 ∗ 𝑟𝑟𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 downloaded𝑚𝑚𝑚𝑚 𝑡𝑡 from𝑟𝑟𝑖𝑖𝑖𝑖 the CSRC database, and , is the market𝛽𝛽𝑖𝑖 𝑡𝑡 excess 𝑒𝑒 return. The average daily idiosyncratic volatility decreases𝑟𝑟𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 from𝑚𝑚𝑚𝑚 𝑡𝑡 0.084% to 0.064% in Table 2. In addition, Bae, Li & Shi (2009) and Zhang (2013) show that under a more flexible exchange rate system, a change in the exchange rate between CNY and USD (HKD) contributes to B-share discounts. B-shareholders receive dividends in CNY, while a stock price is denominated in USD (HKD). When evaluating a stock, they need to convert CNY dividends to USD (HKD). Therefore, CNY exchange rate changes will affect a stock price. In particular, after February 28, 2001, domestic investors dominated the B-share market. Because there is no easily accessible investment tool to hedge against CNY exchange rate changes, they are exposed to high exchange risk. The log returns of the CNY exchange rate against USD (HKD) are used to control the effect of exchange rate changes on B- share discounts. The main alternatives to stocks in China are bank deposits. These deposits tend to pay interest rates below world levels. Fernald and Rogers (2002) argue that B-share discounts are caused by the interest rate difference between the Chinese market and the U.S. market (the Hong Kong market). Mei et al. (2009) confirm this view as well. This study uses the Chinese one-year deposit rate as a proxy for the Chinese risk free rate and employs the U.S. three-month bill rate as the U.S. risk free rate (the yield of the three- month Hong Kong government bond is used as the risk free rate in the Hong Kong market3). The difference is used to control this possible effect. On April 29, 2005, the CSRC announced the reform plan called “the split-share structure reform,” to convert all non-tradable A-shares (state-owned and other legal person shares) to publically tradable shares. By December 31, 2007, 98% of listed

3 Data source httpwww.investing.comrates-bondshong-kong-3-month-bond-yield-historical- data.

companies’ stocks in the SSE and the SZSE had realized full circulation.4 Wang and Li (2009) find that the removal of floating constraints on non-tradable A-shares reduced the H-share (mainland companies issued dual-class stocks in Hong Kong, denominated in HKD) price discounts. Therefore, we choose the sample period from January 2, 2008, to January 30, 2015, to exclude the effect of non-tradable shares and the completed market segmentation. The China Stock Market Trading Research (CSMAR) database provides daily price and trading data for all firms issuing both A- and B-shares, short-selling and margin purchase trading information for eligible A-shares, one-year depository interest rates in China, and the USD/CNY and HKD/CNY exchange rates. The interest on three-month treasury bills is used as the risk-free rate in U.S. market, retrieved from the website of Federal Reserve System.5 The yield of three-month Hong Kong government bonds is used as the risk-free rate in the Hong Kong market.6 Table 2 presents the dependent variable and control variables’ summary statistics. It clearly reveals that the means of all variables declined after the ban was lifted, except for the risk-free rate difference and the change of exchange rate.

4 Data source httpwww.ftchinese.comstory001043496fully. 5 Data source httpwww.federalreserve.govreleasesh15data.htm. 6 Data source httpwww.investing.comrates-bondshong-kong-3-month-bond-yield-historical -data.

post The 2010. March 30 to risk the between dailythe exchange return of CNY against against or i USD HKD rateCNY in SSE of the 𝐴𝐴𝐴𝐴 Tae ummar 2. statistics for Median 𝑡𝑡 Skew. Mean

Kurt.

Std. and and

𝐵𝐵

𝑡𝑡 0.001 0.010 .38 0.01

1.19 re stand for A for stand - free rate in the Chinese market and the US market or the HK market on on day market the HK or market US the and market Chinese the in rate free

D 𝑡𝑡 - -

0.053 8.025 1.08 0.00 0.003 ost -

and B and 8

Tae 2. ummar statistics for share discounts and contro ariaes used in pane regression lift sample period is March31 2010

and stand for A- and B-share turnover respectively on day t. is the idiosyncratic risk of A-share on day t. represents - share turnover respectively on day 3.2 .050 2.598 2.32 the daily return of exchange rate of CNY against USD in the1.523 SSE or CNY against HKD in the SZSE on day t. stands the difference between𝐴𝐴𝐴𝐴𝑡𝑡 the𝐵𝐵𝐵𝐵 𝑡𝑡risk-free rate in the Chinese market and the US marketre or the𝐴𝐴𝐴𝐴 HK𝑡𝑡 market on day t. The pre-lift sample period is𝑅𝑅𝑅𝑅𝑅𝑅 2 January𝑡𝑡 2008

𝑡𝑡

share discounts and contro ariaes used in pane 𝐷𝐷𝐷𝐷𝐷𝐷 to 30 March 2010. The post-lift sample period is 31 March 2010 to 30 January 2015.

𝐴𝐴𝐴𝐴

𝑡𝑡 2. .00 2.109 0.811 1.15 D ost re ost re ost re ost re ost re ost re ost

𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡

Mean 0.010 -0.003 2.32 𝐴𝐴𝐴𝐴 1.15 0.13 𝐵𝐵𝐵𝐵 0.11 0.08 𝐴𝐴𝐴𝐴 0.03 -0.013 𝑅𝑅𝑅𝑅𝑅𝑅-0.010 0.822𝐷𝐷 𝐷𝐷𝐷𝐷0.951 Median 0.01 -0.008 1.523 0.811 0.12 0.253 0.059 0.03 -0.001 -0.003 0.895 0.92 21.992 0.0 3.55 0.12 0.13

Std. 1.19 1.08 2.598 2.109 0.0 0.525re 0.19 0.251 0.088 0.1 0.12 0.05

Skew. 0.001 0.053 .050 .00 3.55 .91 12.99 28.038 -11.12 -22.808 -1.38 -2.188

𝐵𝐵

Kurt. .38 8.025 3.2 2. 21.992 8.25 223.320 990.832 55.31 12.82 .82 9.0

𝑡𝑡 8.25 to 30 January 2015.

0.253 0.525 .91 0.11 ost t

8 .

𝐴𝐴𝐴𝐴

𝑡𝑡

223.320 12.99 is theis idiosyncratic risk of A 0.08 0.059 0.19 re

𝐴𝐴𝐴𝐴

𝑡𝑡 990.832 28.038

0.03 0.03 0.251 ost n SZSE the on day t

pre The .

55.31 - - - regression 0.088 11.12 0.001 0.013 re - lift sample period is2008lift sampleJanuary period2

- share on day day on share

𝑅𝑅𝑅𝑅𝑅𝑅

t 12.82 - . - - 𝑡𝑡 22.808 0.1 0.003 0.010

𝐷𝐷 ost

𝐷𝐷𝐷𝐷 𝑡𝑡

stands differencethe

8 .

𝑅𝑅𝑅𝑅𝑅𝑅 - 0.822 0.895 .82 0.12 1.38 re 𝑡𝑡

represents

𝐷𝐷

𝐷𝐷𝐷𝐷

- 0.05

0.92 9.0 𝑡𝑡

0.951 2.188 ost

.2 ethodoog

This study focuses on the short-term effect of the lifting of the ban on short selling on B- share discounts, as well as the covariation between the short-selling amount and the B- share discounts. The rest of this section describes the methods used to achieve these two goals.

.2.1 ent stud

The ban on short selling and margin trading was lifted for designated stocks overnight. Conducting a series of event studies enables us to compare the changes in B-share discounts caused by the lifting of the ban. However, other shocks in the market may also lead to B-share discount changes. In order to control for other possible effects, the abnormal B-share discount for each stock on the designated list is used instead. To test for changes before and after the additional events, an abnormal discount is calculated as follows:

, = , , (3)

𝐴𝐴𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡 𝐷𝐷𝑖𝑖 𝑡𝑡 − 𝐷𝐷̅𝑎𝑎𝑎𝑎𝑎𝑎 𝑡𝑡 where , is the B-share discount for each stock allowed to be sold short and traded on margin,𝐷𝐷 and𝑖𝑖 𝑡𝑡 , is the cross-sectional mean at time t of all shares’ B-share discounts. The addition𝐷𝐷̅𝑎𝑎𝑎𝑎𝑎𝑎 al𝑡𝑡 event day, day 0, is defined as the day on which an individual stock is added to the designated list and can be sold short and purchased on margin. The pre- and post-event windows are 22 trading days, or approximately one calendar month. The relatively short window is chosen to exclude significant fundamental changes in the markets. There are 30 events in the sample period. This tests the impact of the lifting of the ban in the short term.

.2.2 ane regression

In the Chinese market, investors can publicly obtain short-selling, margin-trading, and the corresponding cover trading information at the individual stock level on a daily basis. Using this data set, it is possible to study the relation between short-selling activities and B-share discounts on the cross-sectional and time-series dimensions.

The second hypothesis implies that short sellers should be more active after periods of high B-share discounts. Thus, the first model analyzes short sellers’ reactions to past B-share discounts. As can be seen in Table 1, short sellers usually cover their position on the same day. Therefore, this study focuses on the short-term short-selling strategy. The window to calculate past B-share discounts is four days. The equation used to test hypothesis 2 is expressed as follows:

, = + , , + , + , , + , + , , + , + , (4)

𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖 𝑡𝑡 𝐶𝐶0 𝐶𝐶1∆𝐷𝐷𝑖𝑖 −1 −4 𝐶𝐶2∆𝐷𝐷𝑖𝑖 𝑡𝑡 𝐶𝐶3𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡−1 𝑡𝑡−4 𝐶𝐶4𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡 𝐶𝐶5𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡−1 𝑡𝑡−4 𝐶𝐶6𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡 𝜖𝜖𝑡𝑡 where short-selling turnover, , , is the daily short-selling volume for stock i at time t, , , scaled by the total A𝑆𝑆𝑆𝑆𝑆𝑆-share𝑖𝑖 𝑡𝑡 trading volume, , ; , is the cumulative difference𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴 𝑖𝑖𝑖𝑖 of B-share discounts from day t – to t – 𝑉𝑉 𝐴𝐴 𝑖𝑖𝑖𝑖 , ∆𝐷𝐷 is−1 the−4 contemporaneous difference of B-share discounts; , is the four-day∆𝐷𝐷𝑖𝑖 𝑡𝑡 past average of -share turnover , is the four-day past𝐴𝐴𝐴𝐴−1 average−4 of the idiosyncratic volatility of A-shares; and , 𝐴𝐴𝐴𝐴 and−1 −4 , are the contemporaneous A-share turnover and A-share idiosyncratic𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡 volatility𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡, respectively. The unit root test on B-share discounts shows that the data series is non-stationary. Therefore, the first difference of the B-share discounts is used instead of the B-share discount level in all regressions. To control for other reasons that could possibly change the B-share discounts, following Diether, Lee & Werner (2009), Equation (4) includes the A-share idiosyncratic volatility to examine whether short sellers provide additional risk bearing capacity in more turbulent periods. However, elevated uncertainty may be caused by information asymmetry or the divergence of opinions. Owing to a lack of transaction-level data, this study does not distinguish between uncertainty caused by information asymmetry and differences of opinion through the bid–ask spread. This study uses the A-share turnover to measure the divergence of opinions directly (Mei et al., 2009). The uncertainty triggered by asymmetric information cannot be examined here. The following model is used to test the predictability of short-selling turnover on the B-share discounts:

, = + , + , + , + , + ,

∆𝐷𝐷+𝑖𝑖 𝑡𝑡+1 , 𝐶𝐶+0 𝐶𝐶1𝑆𝑆𝑆𝑆𝑆𝑆, +𝑖𝑖 𝑡𝑡 𝐶𝐶2𝑆𝑆𝑆𝑆𝑆𝑆, +𝑖𝑖 𝑡𝑡 𝐶𝐶3𝑀𝑀,𝑀𝑀𝑀𝑀+𝑖𝑖 𝑡𝑡 , 𝐶𝐶 4𝑀𝑀 𝑀𝑀𝑀𝑀 𝑖𝑖 𝑡𝑡 𝐶𝐶 5𝐴𝐴𝐴𝐴 𝑖𝑖 𝑡𝑡 (5) 𝐶𝐶6𝐵𝐵𝐵𝐵𝑖𝑖 𝑡𝑡 𝐶𝐶7𝐴𝐴𝐴𝐴𝑖𝑖 𝑡𝑡 𝐶𝐶8𝑅𝑅𝑅𝑅𝑅𝑅𝑖𝑖 𝑡𝑡 𝐶𝐶9𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖 𝑡𝑡 𝜀𝜀𝑡𝑡

or brevity, the unit root test results are not included here, but are available on reuest.

where , is the margin-trading turnover; , is the cover trading turnover of margin𝑀𝑀𝑀𝑀𝑀𝑀 purchase𝑖𝑖 𝑡𝑡 s; , represents the daily return𝑀𝑀𝑀𝑀𝑀𝑀𝑖𝑖 𝑡𝑡 of the CNY exchange rate against USD in the SSE or against𝑅𝑅𝑅𝑅𝑅𝑅𝑖𝑖 𝑡𝑡 HKD in the SZSE; , represents the difference between the risk-free rate in the Chinese market and the𝐷𝐷 U.S.𝐷𝐷𝐷𝐷𝑖𝑖 𝑡𝑡 market or the HK market. The SSE and the SZSE have similar regulations and trading mechanisms, and the same trading costs. Because the number of sample firms for each stock exchange is relative small relative to the longer period, this study uses observations from both exchanges simultaneously to generate the main results in the panel regression. The panel regression sample period is March 31, 2010 to January 30, 2015. Table 3 shows the correlation among the B-share discount difference and the independent variables. Contrary to the theory, the correlation between the B-share discount difference, , and SSR is positive (0.088). Moreover, the corresponding cover trading of short selling,∆𝐷𝐷 SRR, is also positively (0.035) correlated with . However, SSR and SRR are highly correlated (0.901). Thus, most short-selling positions∆𝐷𝐷 are closed on the same day. In order to avoid the multi-collinear problem, these two elements are included in the regression individually. In addition, margin purchases have a negative correlation (- 0.017) with B-share discount changes.

day turnover on t ∆ Ta .

D 𝑆𝑆𝑆𝑆𝑆𝑆 𝑡𝑡

is the difference the is B of e . e 𝑡𝑡

is theis daily covering trading of

𝐷𝐷 𝑅𝑅 𝐴𝐴𝐴𝐴 𝐵𝐵 𝐴𝐴 𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆 ∆ Correlation The correationThe of matri dependentthe and independent ariaes in pane regression

D 𝑅𝑅𝑅𝑅 𝐷𝐷𝐷𝐷 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑀𝑀

𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡

𝑡𝑡 𝑡𝑡

t . 𝑀𝑀𝑀𝑀𝑀𝑀

0.011 - 0.010 0.027 0.091 0.001 - 0.035 0.088 1 0.089 0.01 𝑡𝑡

- ∆ is the is covering trading turnover margin of purchase on day sharedaydiscount on Tae . The correation matri of the dependent and independentD ariaes in pane regression

𝑡𝑡

D is the difference of B-share discount on day t. is the -share short-selling volume scaled by total -share trading volume on day

t. is the daily covering trading of - -share0.001 0.009 short- - -selling0.008 - scaled0.901 1 by total -share trading volume on day t.. is the margin trading 0.18 0.00 0.055 0.03 𝑡𝑡 𝑡𝑡 turnover∆ on day t. is the covering trading turnover𝑆𝑆𝑆𝑆𝑆𝑆 of margin purchase𝑆𝑆𝑆𝑆𝑆𝑆 on day t. 𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡 𝑀𝑀𝑀𝑀𝑀𝑀𝑡𝑡

𝑡𝑡

𝑡𝑡 Correlation𝑀𝑀 𝑀𝑀𝑀𝑀 D short share

D 1 - - 0.007 - - 0.01 - 1 0.19 0.007 0.012 0.057 0.030 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡

∆ 𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆 𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀𝑆𝑆𝑆𝑆𝑆𝑆 𝑀𝑀𝑀𝑀 𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵 𝐴𝐴𝐴𝐴 𝑅𝑅𝑅𝑅𝑅𝑅 𝐷𝐷𝑅𝑅𝐹𝐹

0.088 1 t ∆ 𝑡𝑡 .

𝑆𝑆𝑆𝑆𝑆𝑆

𝑡𝑡

0.035 0.901 1

𝑡𝑡 -

𝑆𝑆𝑆𝑆𝑆𝑆 selling scaled by total

-0.01 -0.03 -0.030 1 𝑡𝑡

𝑡𝑡 0.18 0.015 0.01 - 0.127 0.7 1 𝑆𝑆𝑆𝑆𝑆𝑆 the is 0.027 0.001 0.008 0.01 0.7 1 𝑀𝑀𝑀𝑀𝑀𝑀𝑡𝑡 𝑀𝑀𝑀𝑀 0.091 -0.055 -0.057 0.127 0.071 1

𝑡𝑡 𝑀𝑀

𝑀𝑀𝑀𝑀𝑀𝑀 𝑡𝑡

0.027 -0.00 -0.012 -0.027 -0.0 0.508 1 𝑡𝑡 - 𝐴𝐴𝐴𝐴 short share 0.010 0.009 0.007 0.01 0.017 0.025 0.025 1

𝑡𝑡 0.379 0.015 0.017 - 0.071 1 0.0 𝐵𝐵𝐵𝐵 𝑀𝑀𝑀𝑀𝑀𝑀 91 𝑡𝑡 -0.089 0.001 -0.007 0.015 0.015 -0.035 -0.031 -0.02 1 𝐴𝐴𝐴𝐴

0.011 -0.18 -0.19 0.18 0.379 0,025 -0.097 0.010 0.017 1 𝑡𝑡 𝑡𝑡

𝑅𝑅𝑅𝑅𝑅𝑅 - -

𝑡𝑡 selling volume scaled totalby

𝐷𝐷𝐷𝐷𝐷𝐷 share trading volum 0,025 - 0.025 0.508 1 0.035

𝐴𝐴 𝑡𝑡 t

- - 0.025 1 0.097 0.031

𝐵𝐵 𝑡𝑡

e on day on day e 0.010 - 1 0.02

𝐴𝐴𝐴𝐴 𝑡𝑡 t

- share trading volume on day 𝑀𝑀𝑀𝑀

0.017 1 𝑀𝑀

𝑅𝑅 𝑡𝑡 𝑅𝑅𝑅𝑅

is the margin the is trading

𝑡𝑡

1 𝐷𝐷

𝑅𝑅

𝐹𝐹

𝑡𝑡

4 C T

This section discusses the short-run impact of the lifting of the short-selling ban on B- share discounts and on short-sellers’ roles in market stabiliation.

4.1 Changes in share discounts efore and after the shortseing an

Table reports the means of the abnormal B-share discounts for all individual stocks eligible for short selling and margin purchases. Here, 15 of 30 B-share discounts decreased significantly, while 8 of 30 B-share discounts increased after the ban was lifted. The remaining seven B-share discounts did not change significantly. Comparing the two stock exchanges, short-selling activities effectively bring down B-share discounts in the SZSE (eight decreasing vs. three increasing). The result for the SSE is mixed, with seven B-share discounts increasing, but five decreasing. This is possibly because of the less active short selling in the SSE compared with the SZSE. However, it is still noticeable that, even though some B-share discounts decrease, they do not disappear. In summary, in line with Miller’s (1977) overpricing hypothesis and Mei et al. (2009), the event study results show that the strict short-selling ban in the -share market is one of reasons for the -share overvaluation. However, as is well known, it is difficult to control for all possible elements that may affect the B-share discounts using the event study method only. Therefore, panel regressions are used to examine the effect of short-selling activities on B-share discounts further in next section.

Tae 4. The anorma share discounts around addition eents he addition event day day is deined as the day on hich an individal stoc is added to the designated list and can e sold short and prchased on argin. he anoral share discont is deined as the share discont o a given stoc ith shortselling perission ins the crosssectional ean o all share disconts in or . he preevent and aterevent indos are oth trading days. and indicate signiicance at the 1 and 1 percent levels respectively.

reeent ftereent ean ean ifference Ttest anel . hanghai toc change 1. 1. .7 .919 1 7. .7 1.7 1. 7.11 1.77 .9 1.9 9 1. 1.719 1.17 .71 1 1.9 1.9 . 1.7 1 1.9 1.97 .97 .1 7 .9 .9 .7 .919 11.1 1.1 .1 1.7 11 1.1 9. . .71 9. 17.7 . 1. 71 1. 1.9 .1 .97 . 1.97 .7 .9 1 1. 9.1 .77 1.11 1. 1.1 1.79 .1 9 7. .17 1.97 . 1. 19.7 1.799 .97 77 1. 11.97 1.9 .99 anel . henhen toc change 1.7 19.99 . .9 1 1.7 . . 1. 1 .7 .7 . 1.19 . 1.7 .79 . 1 .1 1. 1.9 . .11 1. 1.1 1.1 9 1. 1.9 . .9 9.7 1.7 . . 9 .1 . 1.9 .91 9 .1 .7 .9 .9 7 . . 1.9 .11 1 . 7.1 11. 9. 71 .7 .1 .79 1.1

4.2 re shortseers more sophisticated

oe researchers consider shortsellers as a grop to e ore sophisticated than average investors ale to ind price deviations ro the ndaental vales and to aritrage these deviations. n contrast to the rational aritrager assption conired y evidence ro the .. aret (iether et al. 9) this stdy inds a signiicant negative coeicient on

, (.1 at the 1 signiicance level). oever the coeicient on is

∆𝐷𝐷signiicant−1 −4 and positive and the agnitde o the coeicient o (.11 at ∆𝐷𝐷the𝑡𝑡 1 signiicance level) is aot ten ties larger than that o , . his∆𝐷𝐷 reslt𝑡𝑡 is consistent ith the conectre and the indings in the .. aret (iether∆𝐷𝐷−1 −4 at al. 9). hen the dierence in share disconts in the previos orday declines y 1 the short selling trnover increases y .1. oever a 1 conteporaneos dierence in share disconts increases the shortselling trnover y 1.1. evertheless this inlence is noticeale ecase the average daily shortselling trnover is only 1.1.

e interpret the coeicients o , and separately the conclsion

old e contradictory. hen e only consider∆𝐷𝐷−1 −4 the sign∆𝐷𝐷 o 𝑡𝑡the coeicient o , e ind that short sellers are st nave trend chasers. hen short sellers oserve∆𝐷𝐷 −1a higher−4 past dierence o share disconts they reain ot o the aret rather than pshing don the share overprice. oever hen e consider the sign o the coeicient o they ehave lie rational aritragers. the gap eteen the conteporaneos

∆𝐷𝐷and𝑡𝑡 share prices idens shortsellers step into the aret trying to correct the ispricing. y coining these to reslts e can conclde that 1) hinese short sellers do engage in aritrage ) hinese short sellers elieve trend persistence and epect that reonds olloing a donard trend are teporary.

dditionally the negative coeicient o , (.7 at the signiicance level) sggests that short sellers avoid trading 𝐴𝐴𝐴𝐴when−1 −4 market participants’ opinions are highly divergent. ven thogh the coeicient on the conteporaneos share trnover is not statistically signiicant the sign is also negative (.1). his sggests that𝐴𝐴𝐴𝐴 𝑡𝑡short sellers preer intervening in the aret hen it is less active. n contrast to reslts in the .. aret (iether et al. 9) short selling is not correlated ith past or conteporaneos volatility in the hinese stoc aret. his iplies that hinese short sellers do not provide opportnistic risearing.

Tae . ane regressions short seing and margin trading turnoers and coering trading turnoers in oth the and the in percent oit regression is adopted to deal with the trncated short selling and margin trading data , is the cmlative dierence o share disconts rom da t to t , is the orda past average o share trnover , is the orda past −1 −4 average∆𝐷𝐷 o the idiosncratic volatilit o share he time period is arch to −1 −4 −1 −4 anar𝐴𝐴𝐴𝐴 statistics are presented in parentheses𝐴𝐴𝐴𝐴 and indicate signiicance at the and percent levels respectivel

odel 𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡 𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡 𝑀𝑀𝑀𝑀𝑀𝑀𝑡𝑡 𝑀𝑀𝑀𝑀𝑀𝑀𝑡𝑡 , ∆𝐷𝐷−1 −4 ∆𝐷𝐷𝑡𝑡 , 𝐴𝐴𝐴𝐴−1 −4 𝐴𝐴𝐴𝐴𝑡𝑡 , 𝐴𝐴𝐴𝐴−1 −4 𝑡𝑡 𝐴𝐴𝐴𝐴 he reslts are ite similar when sing the cover trading trnover o short selling as the dependent variale he negative coeicient o , at the signiicance level sggests that the holding period o a short∆𝐷𝐷−1 −4position is ver short owever the coeicient o is also signiicantl positive at the signiicance level his iners∆𝐷𝐷 that𝑡𝑡 short sellers cover their short positions when contemporaneos share disconts increase his is nepected and seems irrational n addition to stding shortselling activities this std eamines margin traders’ ehavior argin traders condct opposite trading activities to short sellers he provide additional ing pressre ecase past share disconts increase and decrease their position as the contemporaneos share disconts increase the coeicient o , is signiicantl positive at the level with a vale o

ccording𝐴𝐴𝐴𝐴 to−1 hang−4 et al the casalit etween short selling margin trading and share disconts cannot e arged the other wa arond

4. Can shortseing turnoer predict future share discounts

e atde eta trad s arer ta tat srt se addt te at srt se te ese aret s reate ared t tat te aret e t srt seers te ese aret artrae aast err t s erta eter te a sess rret sr s te atr dts a ae reress s srtse trer t redt te deree sare dsts ae sares te rests te arate reress t ea e atr reated t srt se ar trad ad te tarate reresss s a r a sset eaatr araes ased te ae reress at sstet t tess ad edee d te aret eter et a sat eate eets t arate ad

tarate reresss at te sae ee𝑆𝑆𝑆𝑆𝑆𝑆 s𝑡𝑡 tat srt se a derease te se sare dsts e te srtse trer reases te deree sare dsts dees eer te srtse trer s reate aerae da srtse trer s ee a rease s ddta te srtse sess s dee rad ad e a e rt sre r a rerae aes s eete ee sare dsts te ear tre e eate eet er trad srt se s a t dd ease t dates tat srt seers a attes as dra d sare dsts eer t s d sat at te ee ad ts s t reae erere srt seers te ese aret are as red traders e t stae te aret as st ests eet e t te d a et a ar traders a a tra re rret te aret e te ar trad r er trad eets are statsta sat s a e see r ae ar traders aas trade ste t srt seers te teta red estrs s s te d t trte t sta te aret

aar des ad stadard errrs are rreted ta rss srt st atrreress deree te e Tae .

d d ∆ 𝐷𝐷 𝑅𝑅 𝐴𝐴𝐴𝐴 𝐵𝐵 𝐴𝐴 𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀𝑀𝑀 𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆 de 𝐷𝐷 𝑅𝑅𝑅𝑅

𝐷𝐷𝐷𝐷 se ee tr araes sare 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑡𝑡 𝑀𝑀

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ae aa t ae ee t

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te at srt se te eet s er ta tat te eet

s std eaes te at srtse strats te ese aret te seate e s a e data set rsssted ese ad sares rst s a eet std sare dst aes are estated ere ad ater te srtse a as ted e rests s tat tere are re sares t dereas sare dsts ta t reas sare dsts ts d te atr eaes eter srt seers are re sstated ta are aerae estrs e t srt se s e t ese estrs srt seers te ese aret s tat te are re rata ad eereed a te atr tests eter srt seers are ae t rret te err te aret ased deret saes t s sae t de tat ese srt seers trte t aret staat ee t te e srt se s reate sa eer arets estrs are sa tt t e atre ad a aa ede er te eeteess aret aaeet eret reatrs sa estate t a srt se s std rdes ste edee t srt te srtse eas ee eer arets

d edes sset r ad te das sread ii i tre se as e srt sae a dt dsers ad te rssset retrs aa sts i i ae es te a e re d etter der a ee eae rate sste titi ii t arers eer s de estr setet ii i aer rer estr setet te st aret r aer aae at tt tterraersd a e rtse artrad ad re ee dee r te ese aret i i e ee re ers restrts ad aret seetat as st arets ii arrat e te ese sare re dst e e e edee i edt aer es te st aret erreat i ad errea strats srtse ad asset re adstet t rate rat ii i eter ee erer rtsae stratees ad retr redtat i ii ti erad ers es te ese st aret i i ttiti arrs res eate estr ear a st aret t eterees eetats t i te ed ter derreat et trad ad erreat asset arets i

te eree srtsaes strats ad aret rases i ii ti e teres ad ede ese st aret

t i iti t 开启中国证券市场大门 st ed

aa a ser es at rt sae strats ad st retrs ii i at d t rt seers s rs i t ii ti at te reate srt terest ad aret aats i i i e ea eate trad ad st res dee r ese sare rea i i er s ertat ad deree i ea erdee ad seate es iti a rt se at strats ad rsssted st res i ti i i a derstad te sare dsts ae rs te ese st aret i i i

1 s tae sares te rrees eets te as srtse ad artrading are lifted for a subset of Chinese stocks. “Announcement day” dd s te da te resed st s aed e rea s s te er e sertes added te desated st ad te tta er sts rea te st aa st eae ad ee st eae resete eet ta ta a added added added added sts s sts sts s s st st ated

2 A share share hort trading irm name code code starting date ane . hanghai toc change reatton oldings ainan Airline henhua eay ndustries Comany hibei hitech grou ahong ransortation rou ingli echnology eeloment rou hanghai iniao ort rocessing one eeloment aigaoiao ree rade one eeloment uiaui inance rade one eeloment hanghai oteio ianin arine hiing astern Communications uain Cement ailian rou echanical and lectrical ndustry anhua Chemical echnology aiin rou ane . henhen toc change C olding China erchants roerty eeloment China ational Accord edicines Cor ongu toelectronic echnology uangdong lectric oer eeloment oshan lectrical and ighting iangling otors Cor eifu ighechnology rou Anhui uing istillery Chonging Changan Automobile echnology rou engang teel lates antai Changyu ioneer ine

n anasis of Chinese stoc maret mispricing

Mo Zhang* July, 2016

Abstract This study investigates the cause of mispricing and its volatility in the Chinese stock market. The findings show that heterogeneous beliefs among investors and investors’ inflation illusions simultaneously lead to mispricing. In line with U.S. studies, heterogeneous beliefs are positively related to both the level and the volatility of mispricing at the market level. The role of inflation illusion on market mispricing volatility is not statistically significant. Furthermore, the evidence suggests that government interventions can decrease upward mispricing, but aggravate downward mispricing. The mispricing level of state-controlled industries is more sensitive to changes in heterogeneous beliefs relative to that of non-state-controlled industries. Inflation illusion is the driving force behind mispricing volatility in the state-controlled industry sample, but does not affect the non-state-controlled group.

JEL classification: E31, E44, G12, G14 Keywords: Stock mispricing, Heterogeneous beliefs, Short-selling constraints, Resale option, Inflation illusion, Emerging markets.

anken chool of conomics eartment of inance and tatistics irastonkatu aasa inland mail oananenfi

s the second largest stock market1 in the world, as well as one of the most turbulent, the Chinese stock market affects, and is affected by other maor markets. From mid- June to ugust 201, the collapse in the Chinese stock market captured the world’s attention. Share prices had been rising rapidly since mid-2014. n June 12, 201, the Shanghai Composite Inde surged to an eight-year high of 1.1 points, and then suddenly slumped 3.3 in approimately two months. hile the Shenhen Composite Inde also sharply dropped 4. during the same period. This collapse dragged down the sian market, as well as the U.S. and European markets, bringing with it the fear that Chinese economic weakness would affect the global economy. The influence is not ust limited to the stock market, but includes the commodity market as well.2 The ew ork Times pointed out that this steep fall was not a sudden shock. Instead, it was a necessary adustment to the stock market, even though it was etremely painful. Thus, regulators should not intervene in the market. However, facing such heavy losses, public investors and companies’ shareholders urged the government to rescue the stock market. There is always a debate over whether financial regulators should suppress bubbles when the stock market rises suddenly and sharply, or should prop up share prices when the market inde falls too far and too fast. hen the market is eperiencing a rapid advance or decline of this kind, it is one of the most troublesome problems financial regulators need to deal with, and results in significant challenges to listed companies and investors’ risk management. Unfortunately, such large price movements are uite normal in the Chinese stock market. However, the fundamental value of the overall market cannot change fast enough to cause sharp swings between bull and bear periods in a very short term. The ecessive volatility is far too high, and cannot be eplained by cash flow or risk changes Shiller, 11. Therefore, there must be some mispricing in stock prices. s a result, understanding the causes of mispricing in the Chinese stock market has become important for financial regulators, listed companies, and investors. This understanding will help financial regulators predict bubbles in order to take preventive measures and to implement relevant tactics to lead the market. Investors should also pay close attention to factors causing bubbles so that they can react promptly.

1 The market capitaliation of all companies listed on the Shanghai and Shenhen stock echanges on pril , 2014. ata from loomberg. 2 httpwww.bbc.comnewsbusiness-34114. 106

revious research has mostly studied ule formation in the U.. market cheinkman and iong, , ong, cheinkman ei, , hen, ung ang, , which is a lieral and highly developed market without regular government interventions. nstitutional investors dominate the U.. market and most retail investors hold their portfolios through institutional investors. he market is the main force driving stock prices. owever, conditions are very different in emerging markets, especially in a country such as hina. he structure of investors in the hinese stock market is different from those in the U.. market. oung retail investors play a primary role in the hinese stock market. any of them appear to e ineperienced retail investors, likely making decisions ased on friends’ advice or media information, rather than relying on financial statements, company pulic announcements, and financial institution’s research reports. nstead of purchasing assets run y professionals, over of retail investors choose to uy stocks directly. heir portfolios are not well diversified only containing 4.39 listed companies’ stocks, on average. urthermore, their holding periods are relatively short, averaging aout two weeks. The Chinese are the world’s most optimistic investors, according to a egg ason and itiank survey. out of retail investors are only concerned aout asset returns, regardless of risk. n addition, institutional investors in the hinese stock market do not play a role as a stailiing force. nstead, institutional herding ehavior increases a stock price crash risk at the firm level u, u i, . n other words, institutional investors in the hinese stock market, to some etent, ehave like retail investors. he uniue features of hinese stock market and its nonnegligile influence on oth hinese and international investors make it worth eamining the mispricing mechanism in hina. ore importantly, and in contrast to the U.. market, a powerful central government in hina has a strong influence on the security market, making it very sensitive to government policy, and even rumors. he hinese government is so powerful that it can control capital floats y implementing relevant policies, sometimes even y supraeconomic administrative means to support or suppress an industry. he stocks of industries heavily affected y the government may ehave differently to

httpswww.sec.govewspeechetailpeech. httpwww.fores.comsitesnylandercrayfactsaoutchinasstockmarket thatwillmakeyouthinktwiceeforeinvesting. investigation report on hinese retail investors, issued y henhen stock echange. investigation report on hinese retail investors, issued y enghua inancial institute. httpwww.finfo.comspecialreport.pdf. hinas superrich confident of going it alone in investing survey httpwww.scmp.comnewschinamoneywealtharticlechinassuperrichconfidentgoing italoneinvestingsurvey. hinese stock retail investor report .

industries that are less monitored the government. ithout this institutional feature most previous studies targeting the .. market focus onl on the macroscopic view market level. Thus in order to check whether government supervision aids market efficienc this stud anales the mispricing at the market level and at the industr level. This stud contriutes to the literature eamining the role of government supervision in stock mispricing which few previous studies have done. This paper is structured as follows. ection presents a rief literature review and develops the hpotheses. Then ection 3 discusses the structure of model. et ection 4 descries the data and the empirical results. The final section concludes the paper and discusses possile eplanations for the results.

A A

ased on the efficient market hpothesis mispricing should not eist ecause each investor holds an identical epectation of oth future cash flows and discount rates generating a uniue valuation in the market. lanchard and atson 93 provide a rational ule model ased on assumptions of rational epectations and constant epected returns. n their model investors are rational with homogenous epectations. n asset lives infinitel and has no upper limit on its price. The price of an asset is composed of its fundamental value and a rational ule. The value of the ule epected toda must eual the discounted value of net periods anticipated value and e independent of fundamentals. evertheless this model is uestioned oth theoretical and empirical arguments iong 3. iller 9 challenges the rational epectation paradigm releasing the homogeneous elief assumption. n a heterogeneous beliefs framework, investors’ suective eliefs of future cash flows and discount rates can lead to mispricing of a stock price. hen short selling is ound the market price onl reflects the most optimistic investor’s valuation. To simplify the problem, assume there are only two different groups of investors and with their suective valuations of the same stock and . Then the market𝛼𝛼 price𝛽𝛽 we oserve is 𝑉𝑉𝛼𝛼 𝑉𝑉𝛽𝛽 = max , . (1)

𝑃𝑃𝑡𝑡 (𝑉𝑉𝛼𝛼 𝑉𝑉𝛽𝛽)

et the funamental value of a stock be . The mispricin comin from the oint effect of heteroeneous beliefs an shortsellin𝑃𝑃̃𝑡𝑡 constraints is = max , , an depends on the dispersion of investors’ opinions. 𝜀𝜀𝑡𝑡 (𝑉𝑉𝛼𝛼 𝑉𝑉𝛽𝛽) − 𝑃𝑃̃𝑡𝑡 urthermore, cheinkman an ion propose that, in a ynamic settin, when short sellin is boun, heteroeneous beliefs enerate by an overconfience bias will inuce a resale option. current buyer is willin to pay more relative to his own funamental valuation for the possibility of sellin the asset to other more optimistic investors at a hiher price in future. This speculative train amon investors can push prices even hiher an cause wil fluctuations. The speculative component of an asset price is the value of a resale option. oth the manitue an the volatility of a bubble have a positive correlation with heteroeneous beliefs. The oint effect of heteroeneous beliefs an shortsellin constraints on mispricin in the .. market has been confirme by many empirical stuies. sin the breadth of a stock’s ownership, hen, on tein fin that the stock price tens to be upwar biase relative to its funamental when short sellin is boun. iether et al. take the forecast ispersion as a measure of heteroeneous beliefs, an conclue that stocks with hiher forecast ispersion on future earnins commit to lower future returns relative to otherwise similar stocks. on et al. aain testify that investors’ timevaryin heteroeneous beliefs, toether with shortsellin constraints motivate them to value the resale option associate with ownin the asset when the number of shares outstanin is limite. ompare with the rational bubble theory, the main assumptions of the resale option hypothesis are a better fit for the current situation in the hinese stock market. renie retail investors hol universifie portfolios in a very short term. etail investors’ main purpose for participatin in the stock market is speculation. The short sellin mechanism bean in , on a small scale an, currently, with too many restrictions. revious stuies testify to the eistence of the resale option in the hinese market, but with a limite an special ata set. or eample, ion u use hinese warrant ata for the perio – an fin that the oint effects of shortsellin constraints an heteroeneous beliefs can eplain speculative bubbles across warrants an timetomaturity. ei, cheinkman ion testify that a speculative bubble in the hinese share stock market is ue to share investors’ excessive train. There are only put warrants an corresponin stocks in ion an u’s stuy an ualliste companies in the sample of ei at al. . Their

sampes on cover about . and of hinese isted companies respective. herefore their resuts need to incude more isted companies in order to ensure their eneraiabiit. direct detectin mispricin in stock prices and usin a the stocks isted in the and the this stud tests the fooin to hpotheses.

: isricin in te inese aret as a ositie correlation wit te disersion of eteroeneos eliefs

: olatility of isricin in te inese stoc aret is ositiely correlated wit te disersion of eteroeneos eliefs

he other ide discussed hpothesis on mispricin formation is infation iusion. odiiani ohn suest that iusionar investors mix up chanes in nomina interest rates ith rea rates especia hen infation fuctuates. nce investors fai to adust their expected returns in time hen infation increases the nomina discount rate the stock price i be underestimated and vice versa. n particuar firms ith hih everae are usua the most undervaued. he infation iusion hpothesis associates macroeconomic deveopment ith bubbe eneration. ased on the infation iusion hpothesis the sie of a bubbe is neative correated ith infation. oever this hpothesis does not address the reation beteen infation and the voatiit of the bubbe. ampbe uoteenaho provide empirica evidence to support this hpothesis usin – .. stock market data. ater ohen ok uoteenaho presented crosssectiona evidence to confirm this hpothesis b simutaneous testin the future returns of treasur bis safe stocks and risk stocks. runnermeier uiard find supportive evidence from the .. housin market. oever recent studies have cast doubt on the empirica vaidit of the infation iusion hpothesis. iaesi chneider arue that not a investors suffer from infation iusion. here are aas some smart aents ho understand the isher euation. he buit a enera euiibrium mode predictin a nonmonotonic reationship beteen the pricetorent ratio on housin and nomina interest rates. ei finds a positive association beteen infation and dividend ieds hich is

ata source tatistica earbook from pubished b the and . he averae number of isted companies in the and the durin sampe period used in ion u is . he averae number of isted companies in the and the durin sampe period used in ei et a. is .

: win to inflation illsion inflation is neatiely correlated wit isricin in te inese stoc aret

: nflation as a sinificant iact on te olatility of isricin

Shiller’s model, Chen

oeer, here is siien eidene hllenin he sle diidend oli ssmion iller odilini, Sord, o ddress hese rolems, oleennho rooses he dnmi residl inome lion model o onne so ries o medimerm shlo ndmenls his model lins he ooomre rio o sseen roiili, ineres res, nd eess so rerns, oidin modelin he oenill nsle diidend roess

o es he ors ein Chinese so misriin, e irs need o mesre misriin n onrs o reios sdies, his sd does no se Cmell nd Shiller’s dnmi lion model, ese l irmsnes in he Chinese so mre iole o min ssmions o he model Chinese lised omnies rrel disrie sh diidends nd do no he onsisen nd sle diidend oliies Si, nesors re more ineresed in he roiili o lised omnies rher hn diidends o , n he Chinese so mre, inesors do no re diidends s imorn hen rhsin sos he ere holdin eriod is eremel shor, roimel o ees he ininie horion ssmion is lso inlid in he Chinese so mre oleenho rooses n lernie model o mesre he ndmenl le o so, hih is sed on hree ssmions or ehnil resons, he oo le nd he mre le o so shold e osiie lerelene, menin so rie les rond ndmenl le nd len srls onin relion, in he inome semen nd lne shee dnmis oeher he ondiions o he oleenho model hold eer in he Chinese so mre hereore, his sd ollos he roh o oleenho o deine misriin Seion dissses misriin enerion hen, Seion deelos esle models o emine ho heeroeneos elies nd inlion e he leel o misriin nd is olili serel

tc src

he el le he lr re ri e ese

s lls leeh 𝜃𝜃̂𝑡𝑡

= log( ) log( ) = ∞ ∞ , (2) 𝑗𝑗−1 𝑗𝑗−1 𝜃𝜃̂𝑡𝑡 𝐵𝐵𝑡𝑡 − 𝑝𝑝̂𝑡𝑡 ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡𝑟𝑟𝑡𝑡+𝑗𝑗 − ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡𝑒𝑒𝑡𝑡+𝑗𝑗 𝑗𝑗=1 𝑗𝑗=1 here is he le rereses he el le s he ( ) ees𝐵𝐵𝑡𝑡 he eess l rer 𝑝𝑝̂𝑡𝑡 = log 1 + is sile rer s 𝑟𝑟𝑡𝑡 is el l e ls he ieres𝑟𝑟𝑡𝑡 re𝑅𝑅 𝑡𝑡 −= 𝑟𝑟log𝑓𝑓𝑓𝑓 𝑅𝑅𝑡𝑡 s he eess l 𝐵𝐵𝑡𝑡+𝐷𝐷𝑡𝑡 rer𝑟𝑟𝑓𝑓𝑓𝑓 he le ls lle riili𝑒𝑒𝑡𝑡 (is𝐵𝐵 he𝑡𝑡−1 )sh − 𝑟𝑟𝑓𝑓 𝑓𝑓iie is

s le esie + = + 𝐷𝐷𝑡𝑡 + 𝜌𝜌 hs he lr el𝜃𝜃𝑡𝑡−1 le𝑒𝑒𝑡𝑡 − 𝑟𝑟𝑡𝑡 s𝛼𝛼 𝜌𝜌𝜃𝜃 𝑡𝑡 e𝜅𝜅𝑡𝑡 iie i he lr rre le he ieree eee he eie eee s rers riili s lls

log ( ) = log( ) + ∞ ∞ . (3) 𝑗𝑗−1 𝑗𝑗−1 𝑝𝑝̂𝑡𝑡 𝐵𝐵𝑡𝑡 ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡𝑟𝑟𝑡𝑡+𝑗𝑗 − ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡𝑒𝑒𝑡𝑡+𝑗𝑗 𝑗𝑗=1 𝑗𝑗=1 he sere s rie e ese s

log( ) = log( ) + ∞ ∞ . (4) 𝑗𝑗−1 𝑠𝑠 𝑗𝑗−1 𝑠𝑠 𝑝𝑝𝑡𝑡 𝐵𝐵𝑡𝑡 ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡 𝑟𝑟𝑡𝑡+𝑗𝑗 − ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡 𝑒𝑒𝑡𝑡+𝑗𝑗 𝑗𝑗=1 𝑗𝑗=1 herere he isrii is

= log( ) log ( ) =

𝑀𝑀𝑡𝑡 𝑝𝑝𝑡𝑡 − 𝑝𝑝̂𝑡𝑡 𝜃𝜃̂𝑡𝑡 − 𝜃𝜃𝑡𝑡 = ∞ ∞ ∞ ∞ , (5) 𝑗𝑗−1 𝑠𝑠 𝑗𝑗−1 𝑠𝑠 𝑗𝑗−1 𝑗𝑗−1 ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡 𝑟𝑟𝑡𝑡+𝑗𝑗 − ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡 𝑒𝑒𝑡𝑡+𝑗𝑗 − (∑ 𝜌𝜌 𝐸𝐸𝑡𝑡𝑟𝑟𝑡𝑡+𝑗𝑗 − ∑ 𝜌𝜌 𝐸𝐸𝑡𝑡𝑒𝑒𝑡𝑡+𝑗𝑗) 𝑗𝑗=1 𝑗𝑗=1 𝑗𝑗=1 𝑗𝑗=1

his is se le srls i he le ie t is el he le ie t ls eris less he iies ie t

here ees iestors’ subjective expectation of excess returns 𝑆𝑆 𝑠𝑠 riili𝐸𝐸𝑡𝑡 𝑟𝑟𝑡𝑡+𝑗𝑗 reseiel𝐸𝐸𝑡𝑡 𝑒𝑒𝑡𝑡+𝑗𝑗 irsl e esie he rel lr re ri , se

leeh’s sse ih r riles l re𝜃𝜃̂𝑡𝑡 ri

𝑡𝑡 he eess l rer l rer le he risree re 𝜃𝜃,

ere , , and re lle𝑟𝑟𝑡𝑡 si he leeihe𝑒𝑒𝑡𝑡 eh h he re𝑟𝑟𝑓𝑓 𝑡𝑡 leel 𝜃𝜃𝑡𝑡 𝑟𝑟he𝑡𝑡 isr𝑒𝑒𝑡𝑡 leel he eih is eie he ilii s i

iie he s he ilii ll lise ies i re r isr

e he er = , he se he el esie he

el le 𝑦𝑦𝑡𝑡 he( l𝜃𝜃𝑡𝑡 𝑟𝑟𝑡𝑡 𝑒𝑒𝑡𝑡 𝑟𝑟𝑓𝑓 𝑡𝑡re) ri

= A + , (4)

𝑦𝑦𝑡𝑡 𝑦𝑦𝑡𝑡−1 𝜁𝜁𝑡𝑡 here is he esie eiie ri i he eie eee s rers riili le he er = (0 1 0 0) = (0 0 1 0) he he

el le he lr 𝑒𝑒2re ri 𝑒𝑒3 e rie i ri r s lls 𝜃𝜃̂𝑡𝑡

∞ = ( ) (5) 𝑗𝑗−1 −1 ∑ 𝜌𝜌 𝐸𝐸̂𝑡𝑡𝑟𝑟𝑡𝑡+𝑗𝑗 𝑒𝑒2𝐴𝐴 𝐼𝐼 − 𝜌𝜌𝜌𝜌 𝑦𝑦𝑡𝑡 𝑗𝑗=1 ∞ = ( ) (6) 𝑗𝑗−1 −1 ∑ 𝜌𝜌 𝐸𝐸̂𝑡𝑡𝑒𝑒𝑡𝑡+𝑗𝑗 𝑒𝑒3𝐴𝐴 𝐼𝐼 − 𝜌𝜌𝜌𝜌 𝑦𝑦𝑡𝑡 𝑗𝑗=1 = ∞ ∞ . (7) 𝑗𝑗−1 𝑗𝑗−1 𝜃𝜃̂𝑡𝑡 ∑ 𝜌𝜌 𝐸𝐸̂𝑡𝑡𝑟𝑟𝑡𝑡+𝑗𝑗 − ∑ 𝜌𝜌 𝐸𝐸̂𝑡𝑡𝑒𝑒𝑡𝑡+𝑗𝑗 𝑗𝑗=1 𝑗𝑗=1 he e i he isrii le lli

= = ( ) ( ) . (8) −1 −1 𝑀𝑀𝑡𝑡 𝜃𝜃̂𝑡𝑡 − 𝜃𝜃𝑡𝑡 𝑒𝑒2𝐴𝐴 𝐼𝐼 − 𝜌𝜌𝜌𝜌 𝑦𝑦𝑡𝑡 − 𝑒𝑒3𝐴𝐴 𝐼𝐼 − 𝜌𝜌𝜌𝜌 𝑦𝑦𝑡𝑡 − 𝜃𝜃𝑡𝑡

tss tst

fter cacuatin te ispricin series fooin ei et a e use te sare turnover as a prox for eteroeneous beiefs aon investors are turnover is efine as

, = 𝑛𝑛 , , (9) 𝑉𝑉, 𝑖𝑖 𝑡𝑡 𝑡𝑡𝑡𝑡𝑡𝑡 ∑ 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 ∗ 𝑤𝑤𝑖𝑖 𝑡𝑡 𝑖𝑖=1 𝑁𝑁𝑖𝑖 𝑡𝑡 ere is te vaueeite turnover at te aret or te inustr eve

𝑡𝑡 , enotes𝑡𝑡𝑡𝑡 te train voue of stoc i at tie t , is te nuber of iui 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 stocs𝑉𝑉𝑖𝑖 𝑡𝑡 of copan i at tie t , is cacuate as te𝑁𝑁 capitaiation𝑖𝑖 𝑡𝑡 of stoc i ivie b te su of te capitaiation𝑤𝑤 of𝑖𝑖 𝑡𝑡 iste copanies in te overa aret or inustr iiar to te eto use b apbe uoteenao te soote ovin averae of infation is epoe to easure te expectation of infation 𝑚𝑚𝑚𝑚 ina ene cai𝜋𝜋𝑡𝑡 tat te ifference beteen noninexe bons an infationinexe bons is coon use as te expectation of infation oever current tere is no infationinexe bon in ina urin te perio – a i infation perio te inese overnent issue infation inexe bons cae aoi onai to protect investors but tis is no oner te case t te aret eve te autor uses te oe to test te effects of eteroeneous beiefs an infation iusion on bot te eve an voatiit of ispricin incuin sare turnover an expecte infation in te ean an variance euations te oe can test a four poteses siutaneous

= + + + (10)

= +𝑀𝑀𝑡𝑡 𝐶𝐶1 +𝐶𝐶2𝑡𝑡𝑡𝑡𝑡𝑡 +𝐶𝐶3𝜋𝜋𝑡𝑡 𝜀𝜀+𝑡𝑡 + , (11) 2 𝑉𝑉𝑡𝑡 𝐶𝐶4 𝐶𝐶5𝜀𝜀𝑡𝑡−1 𝐶𝐶6𝑉𝑉𝑡𝑡−1 𝐶𝐶7𝑡𝑡𝑡𝑡𝑡𝑡 𝐶𝐶8𝜋𝜋𝑡𝑡 𝜇𝜇𝑡𝑡 ere is te suare of te error ter in te ean euation an is te one 2 ae 𝜀𝜀𝑡𝑡−1 ter 𝑉𝑉𝑡𝑡−1 fter stuin te aret eve te autor constructs te tieseries inustria ata as a pane structure an exaines eter eteroeneous beiefs an te infation iusion potesis can expain te crosssectiona ifference in ispricin aon

acuate usin ata fro te inese tate tatistica ureau

𝐷𝐷 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐

, = + , + , + , (13)

, =𝑀𝑀𝑖𝑖 𝑡𝑡 + 𝐶𝐶1 ,𝐶𝐶2+𝑡𝑡𝑡𝑡𝑖𝑖 𝑡𝑡 , 𝐶𝐶+3𝜋𝜋𝑖𝑖 𝑡𝑡 𝜗𝜗𝑖𝑖 𝑡𝑡 + , . (14) 𝑀𝑀𝑖𝑖 𝑡𝑡 𝐶𝐶1 𝐶𝐶2𝑡𝑡𝑡𝑡𝑖𝑖 𝑡𝑡 𝐶𝐶3𝜋𝜋𝑖𝑖 𝑡𝑡 𝐷𝐷𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝜏𝜏𝑖𝑖 𝑡𝑡

𝐶𝐶2 𝐶𝐶3

𝜎𝜎𝑡𝑡

, = + , + , + , (15)

, =𝑉𝑉𝑖𝑖 𝑡𝑡 +𝐵𝐵0 𝐵𝐵, 1+𝑡𝑡𝑡𝑡𝑖𝑖 𝑡𝑡 ,𝐵𝐵+2𝜋𝜋𝑖𝑖 𝑡𝑡 𝜑𝜑𝑖𝑖 𝑡𝑡+ , . (16) 𝑉𝑉𝑖𝑖 𝑡𝑡 𝐵𝐵0 𝐵𝐵1𝑡𝑡𝑡𝑡𝑖𝑖 𝑡𝑡 𝐵𝐵2𝜋𝜋𝑖𝑖 𝑡𝑡 𝐷𝐷𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝛿𝛿𝑖𝑖 𝑡𝑡

AA A A

Shares carrying “ST” (special treatment) or “*ST” tags suffer losses for two consecutive Campbell and Shiller’s (1988) dividend

e Board (“SME”) and the ChiNext Board.

the maret price does. Thus there must be some other force causing the maret price to deviate from the fundamental value. t the same time we find that the uarter mean and standard deviation of turnover is 88.1 and .1 respectively. The average annualied turnover in the Chinese stoc maret () is approximately twice the annualied turnover in the .S. maret (1). 1 The excessively high turnover combined with the ineffective mechanism in the Chinese stoc maret closely follows the assumption of the resale option hypothesis. ab scrt statstcs This table reports descriptive statistics on maret level for log bootomaret ratio log dividend yield log profitability log stoc return turnover log interest rate and inflation rate from 1 to 11. The maret level variables are calculated by the valueweighted method based on 1 listing stocs in both the SSE and the SSE. The weights are decided by the maret capitaliation of liuid stocs.

artr r rr at scrt bt tabt stc trst rat art rtr rat ar rat ar Mean .9 1.91 . .8 .881 . . Std. ev. . 1. . .1 .1 . .18 Median . .1 . . . . . Maximum .9 . .11 .8 .1 .1 .8 Minimum 1. . .19 .81 . . . Sewness . . 1.118 .1 1.9 . .8 urtosis . 1.1 .89 . .8 . .

bs.

src stat

The principal assumption of the ulteenaho model (1999) is that the bootomaret ratio is stationary. n other words an accounting uantity is associated statistically with prices or returns (rancis Schipper 1999). owever ulteenaho (1999) argued that “een if te ootoaret ratio is not stationary t ily eanreertin te odel ay sere as an adeate aroiation.” The realized log booktomaret ratio of the maret in our sample is not stationary1 but the variable behaves as a meanreverting process. Therefore the returnprofitability model still holds true in the Chinese stoc maret. s described in Section .1 the real log bootomaret ratio is estimated by the fourvariable model stated in Euation (). Table shows the results of the

1 ata source orld Ban website. httpdata.worldban.orgindicatorCM.MT.TN. 1 or simplicity the test result is not shown here but is available upon reuest. 118

odel. The ir ol idiae ha he lagged log bookoarke raio ha a oiie orrelaio ih he log bookoarke raio a he igiiae leel. The oeiie o he lagged log bookoarke raio i loe o oe . ggeig rog eriee i he book ale. The ee log ok rer i he oher ariable ih a igiia b egaie orrelaio ih he log bookoarke raio a he leel. Thi odel elai . o he ariaio i he log bookoarke raio. ab ctr Atrrss A aratr stats Thi able ho he orariable araeer eiae. dogeo ariable are ho i he ir ro. i log bookoarke raio. i he eeie log ok rer. i he roiabili. i he rikree rae. Te 𝑒𝑒rel are i arehee. 𝜃𝜃 𝑟𝑟 ad idiae igiiae a he ad ere leel reeiel. 𝑒𝑒 𝑟𝑟𝑓𝑓

, , , , , . .𝑒𝑒 . . 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡 𝑓𝑓 𝑡𝑡 𝜃𝜃. 𝑟𝑟. 𝑒𝑒. .𝑟𝑟 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡−1 𝜃𝜃 , . . . . 𝑒𝑒 . . . . 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡−1 𝑟𝑟 , . . . . . . . . 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡−1 𝑒𝑒 , . . . .

𝑓𝑓 𝑡𝑡 −1 . . . . 𝑟𝑟 d. . . . . 2 𝑅𝑅 igre lo he deooiio o he log bookoarke raio a he arke leel ro o . ere he rerroiabili odel a eiae he iriig i he hiee ok arke ie ell. The ah o iriig aord ih he arke reali. er he ide reahed a eak i he bear arke laed or ie ear i he hiee ok arke. The ok ale i eerel dereiaed. ih he oleio o he hareli reor roe ad he irodio o he e eriie a i he arke reoered ad ke ireaig o he eak haghai ooie de . oi o ober idiaig a obio bbble i he arke. he global iaial rii alo hi he hiee

The li hare rre reer o he eiee o a large ole o oradable aeoed ad legal ero hare i hiee ok arke. Thi ea ol abo oehird o he hare i doeiall lied ir loa o he ok arke. The reor oer he eeial aagee raoraio o aeoed ae i hia. aii hoed ha doei oaie ere lied o hia hare ad hare ok arke i o o hih ere aeoed oaie. ordig o he reor rooal he oaie or aor hareholder hold oeae abo hree hare er hare o radable hareholder o a o ake all heir hare radable. oeer ieor i hia hare ad hare arke ill o ake ar i he hare arke reor ad hereore ill o reeie oeaio.

eoo hard. he ok arke bbble br he arke ared oerreaig o bad e ad dereiaed he ok ale badl ro o . To ilae he eoo o oeber he hiee ae oil aoed a la o ie rillio eiale o billio i irarre ad oial elare b he ed o . The arke ikl reboded. oeer he il la alo brogh hge ide ee ael a rge i loal goere deb ad ho oe rhig io he eri arke ad hig ero ae rie. The oiie iriig ro o a a large a he iriig i he re iaial rii eriod. The arke did o reere il he laer hal o . The i eered io a relea ead eriod ad did o ho a ild laio il . oeer ro he arke ke ireaig raidl. i hoed obio oeralaio. eioed i eio hi oeralaio e b i he iddle o . edi ho he iriig ariaio o eah idr. The hage i iriig i all he idrie oiide ih he ereel olaile oee i he arke b he leel o iriig aog ario idrie are obiol diere. or aioal eri reao he goere heail orol oe idrie. eio . ill ake a loer look a heher hee aereglaed idrie behae dierel o oher idrie ig a ael regreio odel.

0.80

0.60

0.40

0.20

0.00

-0.20 2001Q4 2002Q2 2002Q4 2003Q2 2003Q4 2004Q2 2004Q4 2005Q2 2005Q4 2006Q2 2006Q4 2007Q2 2007Q4 2008Q2 2008Q4 2009Q2 2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 -0.40

-0.60

-0.80

-1.00

-1.20

Book-to-Market ratio Estimated Book-to-Market ratio Mispricing

r tart rat stat tart rat a src art Thi igre ho he ariaio o log bookoarke raio eiaed log booko arke raio ad iriig o arke leel ro o . The arke leel ariable are allaed b he aleeighed ehod baed o liig ok i boh he ad he . The eigh are deided b he arke aializaio o liid ok. The eiaed log bookoarke raio baed o odel reree he daeal ale ooe o he realized log bookoarke raio. arke iriig i he dieree beee he realized log bookoarke raio ad eiaed log bookoarke raio.

t rt tst a statar crt

eio . aalze iriig iiiel b hekig heher he iriig ariaio aord ih arke ee ad olde ha he dai rer roiabili odel a eare iriig i he hiee ok arke aroriael. Thi eio ill e he aioari o all ariable ed i he odel. ageed ik–ller e ho ha arke iriig erie ad ok roer are o aioar ih a ale . ad . reeiel. i ell ko he o reel ed ehod or oerig oaioar erie o aioar erie i o ake he ir dieree. oeer hi d doe o ollo he oeio b iead ollo he e al. adoig he hiig eadae

tss tst rsts at t art

– tudent’s t

eteeneus ees nd ntn usn e tnt esns usn et sn

0.60 0.08

0.07 0.40 0.06

0.20 0.05

0.04 0.00 0.03 2001Q4 2002Q2 2002Q4 2003Q2 2003Q4 2004Q2 2004Q4 2005Q2 2005Q4 2006Q2 2006Q4 2007Q2 2007Q4 2008Q2 2008Q4 2009Q2 2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 -0.20 0.02

0.01 -0.40 0.00

-0.60 -0.01 Mispricing Stock turnover Expected inflation

r src trr a at at t art s ue ts te tns sn tune nd ntn n et ee t e et ee es e uted te ue eted etd sed n stn sts n t te nd te e ets e deded te et ttn ud sts e sn nd st tune sees e dusted te stn stedstte ettu nd eueu e ntn nd st tune e enent sted usn u ute s

ne e ets te esuts n te ne eutn en usn te n dstutn s te e dstutn te esuts s tt st tune nd eeted ntn n use ne n sn tt ut n te ste detn nsstent t te ese tess st tune dss ste nd snnt etn t et sn tt t eent t te ee en tu te ntn usn tess des nt e n edtn n te t eeted ntn n sn tt te eessn esuts s snnt nete etn eteen eeted ntn nd et sn tt t eent t te ee ee en dtn tudent’s tdstutn s te e dstutn te eets t ts e eened e eent st tune neses t ut

ees d snnt t te ee t te se te te eent ntn ses dn ut s ees sttst nsnnt euse tee s n teet ndtn te etn eteen ntn nd sn tt te ut ns te ste nuene st tune n te tt sn ab cts trr a at t a att t art src stat b A s te ets esttn esuts ets tune nd ntn n te ee nd tt te et sn t tune nd eeted ntn e nuded t en nd tt eutn s n eenus 𝑡𝑡 es s te sue e te n te en eutn 𝑡𝑡𝑡𝑡 s te ne ed 𝑡𝑡 te𝜋𝜋2 e n dstution and student’s tdstutn e used sete s e dstutn𝜀𝜀𝑡𝑡−1 en esttn te de nd ndte𝑉𝑉𝑡𝑡−1 snne t te nd eent ees esete

a A a at ra strbt Student’s tstrbt td td e ttst e ttst 𝑡𝑡𝑡𝑡𝑡𝑡 a arac at 𝜋𝜋𝑡𝑡 ra strbt Student’s tstrbt td td e ttst e ttst 2 𝜀𝜀𝑡𝑡−1 𝑉𝑉𝑡𝑡−1 𝑡𝑡𝑡𝑡𝑡𝑡

𝜋𝜋𝑡𝑡 tss tst rsts at t stra

e st setn tests te st tee teses t te et ee n ts setn te stud uses n te stutue usn te ne eessn etd e ets te eets tune nd ntn n te ee nd tt ndust sn ed sssetn nd ed eets e seed e ee–est stndd es e dted t utetn nd etesedstt es e st un ss tt t st tune nd eeted ntn n en te tn n ndust sn n t te sssetn nd te sees densns t ts e snnt t nsstent sn s nd edt e dusted s ete eeteess te ntude te eent tune 2 deese𝑅𝑅 s ete t te et esut ee te eent te eeted

ination is esistent on te siia ee in te industia estiation in te aet estiation is eans tat te ination iusion aets te isiin in ea indust at uite a siia ee oee te iat o eteoeneous eies on te isiin in dieent industies aies ide e ets tune nd ntn n te ee nd tt te ndust sn estted ne eessn is tae eots te eets o tunoe and ination on te ee and oatiit o te industia isiin estiated ane eession e sae ontains industies e sae eiod is o to , and , ae te ee and oatiit o isiin o indust i at tie t esetie , is te sto 𝑖𝑖 𝑡𝑡 𝑖𝑖 𝑡𝑡 tunoe o indust i at tie t is te eeted ination𝑀𝑀 at tie 𝑉𝑉t is a 𝑖𝑖 𝑡𝑡 du aiae eua to en an indust is a stateonto indust𝑡𝑡𝑡𝑡 and indiate siniiane at te and𝝅𝝅 𝒕𝒕 eent ees esetie 𝐷𝐷𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐

e , , , ,

𝑖𝑖 𝑡𝑡 𝑖𝑖 𝑡𝑡 𝑖𝑖 𝑡𝑡 𝑖𝑖 𝑡𝑡 𝑀𝑀 𝑀𝑀 𝑉𝑉 𝑉𝑉 , 𝑖𝑖 𝑡𝑡 𝑡𝑡𝑡𝑡 𝑡𝑡 𝜋𝜋 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝐷𝐷 osssetiona eet ied one ied one eiod eet ied ied ied ied

d 2 𝑅𝑅 en te seond oun sos tat te oeiient o te stateontoed du is siniiant neatie at te ee ote tat tis does not ean tat stateontoed industies sue ess o isiin oes eause isiin an e te esut o an oeauation o undeestiation en isiin is ositie stateontoed industies ae ess oeaued tan ae nonstateontoed industies oee en isiin is neatie stateontoed industies tend to e oe undeestiated tou te esae otion and ination iusion oteses an eain te ee uite e te tid oun in ae sos tat te annot do so o te oatiit o isiin e sto tunoe oses its oe to eain te aiation aon dieent industies t is notieae tat een te eeted ination as a id siniiant iat on te oatiit o isiin ut it a ositie oeiient o dditiona unie te esuts eneated o te ee o isiin tee is no oious dieene eteen stateontoed and nonstateontoed industies

ae iies tat oenent inteentions a aet industia isiin us it is easonae to test ete te inuenes on te sto tunoe and eeted ination ae dieent eteen tese to ous nae stateontoed and non stateontoed industies ae oaes te ane esuts o te to susaes in ode to ie esuts tat ae oe eaoate e ist to ouns so tat sto tunoe as a eate inuene on stateontoed industies tan it does on non stateontoed industies en tou te oeiients o sto tunoe ae ot i siniiant and ositie in te to susaes te anitude o te oeiient in te stateontoed sae is aoiate tie as ae as in te nonstate ontoed sae and esetie oee te iats o te eeted ination in tese to ous do not disa su oious dieenes e oeiient o te eeted ination in te stateontoed sae is and i siniiant ie te oeiient in te nonstateontoed sae is and i siniiant e ets tune nd ntn n te ee nd tt te ndust sn n suse is tae eots te eets o tunoe and ination on te ee and oatiit o te industia isiin in susae industies ae sit into to ous state onto industies industies and nonstate onto industies industies e sae eiod is o to , and , ae te ee and oatiit o isiin o indust i at tie t esetie e sueio aate distinuises 𝑀𝑀𝑖𝑖 𝑡𝑡 𝑉𝑉𝑖𝑖 𝑡𝑡 state onto and no state onto sae , is te sto tunoe o indust i at tie t is te eeted ination at tie t and indiate siniiane at te 𝑡𝑡𝑡𝑡𝑖𝑖 𝑡𝑡 and eent ees esetie 𝝅𝝅𝒕𝒕

e , , , , 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏𝒏 𝒊𝒊 𝒕𝒕 𝒊𝒊𝒕𝒕 𝒊𝒊 𝒕𝒕 𝒊𝒊 𝒕𝒕 𝑴𝑴 𝑴𝑴 𝑽𝑽 𝑽𝑽 , 𝑖𝑖 𝑡𝑡 𝑡𝑡𝑡𝑡 𝑡𝑡 𝜋𝜋 osssetiona eet ied ied ied ied eiod eet ied ied ied ied

d 2 𝑅𝑅 n tes o oatiit tee eist dieenes tat ae oe distint eted ination as an iotant oe in ineasin te isiin oatiit in te state ontoed sae e oeiient is and i siniiant is is oosite to te aet esut i states tat te sto tunoe is te ain oe eind te

isiin oatiit en te esuts in oun so tat neite sto tunoe no eeted ination aets te isiin oatiit in te nonstateontoed sae e onstant in te eession is i siniiant and ositie is iies tat tee eists soe unoseed ato tat an inease te isiin oatiit o nonstateontoed industies odin to odiiani on oanies it ie eeae tend to sue oe o te ination iusion oe is eans tat i eeaed oanies ae oe ie to e undeaued and oe seee tan ae te o eeaed oanies duin ties o i ination and ie esa n ina tee ae oe stateoned oanies in te stateontoed industies e ae usua te iant and eadin is doinatin tese industies and ae ose eationsis it te ans eeoe te an otain oans oe easi tan otes an and usua aintain a ie ee o eeae is a eain eeted ination aets stateontoed industies oe tan it does nonstateontoed industies

sin te etunoitaiit ode uoteennano tis stud estiates te isiin in te inese sto aet at ot te aet ee and te industia ee o oteses ae tested to eain te isiin enoenon nae te esae otion otesis eian ion and te ination iusion otesis odiiani on uate data o oanies isted on te and te o to ae used o te eiia anasis inudin te sto tunoe and eeted ination in te ean and oatiit oess in a eession at te aet ee tis stud inds tat ot te esae otion otesis and te ination iusion otesis an eain te ee o aet isiin e eets ae onsistent it te teoetia editions oee on investors’ heterogeneous beliefs affect the volatility of market mispricing i is in ine it te esae otion otesis edition ese esuts ae siia to indins in te aet en et a sin a ane eession on industia ee data te eiia stud sos tat ot te esae otion otesis and te ination iusion otesis an eain te aiation in te industia isiin in tes o te osssetiona and tie seies diensions dditiona te esuts so tat en isiin is ositie state ontoed industies tend to e ess ositie i eans tat te ae ess oeaued tan nonstateontoed industies ae oee en isiin is neatie state

controlle inustries ten to be more severely unerestimate urthermore compare ith nonstatecontrolle inustries heterogeneous beliefs have a much higher influence on the level of mispricing in statecontrolle inustries oever the ifferences beteen the inflation illusion effect in statecontrolle an nonstate controlle inustries are trivial he variation in the mispricing volatility among ifferent inustries through ifferent perios is too comple to be eplaine by the resale option hypothesis or the inflation illusion hypothesis oever the empirical results sho that inflation illusion has a istinct influence on statecontrolle an nonstatecontrolle inustries nflation illusion can cause an increase in the mispricing volatility of state controlle inustries but has no impact on nonstatecontrolle inustries his stuy reveals ifferent patterns in the level an volatility of mispricing beteen statecontrolle inustries an nonstatecontrolle inustries t inicates that national intervention is beneficial for preventing bubble formation in boom perios but easily causes unervaluation in recession perios

ai erron ultiple structural change moels simulation analysis n orbae urlauf ansen s Econoetric teory and ractice st e pp ambrige ambrige niversity ress lanchar atson ubbles rational epectations an financial markets orking paper vailable at httpnberorgpaperspf runnermeier ulliar oney illusion an housing frenies eiew of inancial tdies ampbell hiller tock prices earnings an epecte iviens Jornal of inance ampbell uolteenaho nflation illusion an stock prices erican Econoic eiew hen ung ang here are the sources of stock market mispricing an ecess volatility eiew of antitatie inance and ccontin hen ong tein reath of onership an stock returns Jornal of inancial Econoics ohen olk uolteenaho oney illusion in the stock market he moiglianicohn hypothesis arterly Jornal of Econoics iether alloy cherbina ifferences of opinion an the cross section of stock returns Jornal of inance inlay ene stimating inflation epectations ith a limite number of inflationinee bons nternational Jornal of entral anin rancis chipper ave financial statements lost their relevance Jornal of ccontin esearc ong cheinkman ei sset float an speculative bubble Jornal of inance ettau ieuerburgh econciling the return preictability evience eiews of inancial tdies ei cheinkman iong peculative traing an stock prices vience from hinese share premia nnals of Econoics and inance iller isk uncertainty an ivergence of opinion Jornal of inance

iller oigliani ivien policy groth an the valuation of shares Jornal of siness oigliani ohn nflation rational valuation an the market inancial nalysts Jornal iaesi chneier nflation illusion creit an asset prices n ampbell sset rices and onetary olicy st e pp niversity of hicago ress ao a he analysis of the psychological responses of hinese scattere investors to cash ivien Jornal of entral ot niersity cheinkman iong ei verconfience an speculative bubbles Jornal of olitical Econoy hiller o stock prices move too much to be ustifie by subseuent changes in iviens erican Econoic eiew taffor anaging financial policy vience from the financing of etraorinary investments orking paper vailable at httppeoplehbseuestafforapersissertationpf ui roblems eisting in ivien policies in china liste companies an countermeasures sian ocial cience uolteenanho nerstaning the aggregate booktomarket ratio orking paper vailable at httppapersssrncomsolpaperscfmabstracti ei nflation an stock prices o illusion Jornal of oney redit and anin iong ubbles crises an heterogeneous beliefs n eanpierre oseph s andoo on systeic ris st e pp ambrige ambrige niversity ress iong u he hinese arrants bubble erican Econoic eiew u u i nstitutional investor hering an stock price crash risk anaeent orld

classes base on to igital coes in from turn coe is using is lettersthe to represent ifferent categories in turn Companies theby issued China SecuritiesRegulatory Commission (“CSRC”) in 201 tablehis gives the information of

anufacturing of railays ships aircrafts spacecraft an other transportation euipment transportation other an spacecraft ships aircrafts railays of anufacturing manufacturing utomobile pecial manufacturing euipment eneral inustry prouct etal non of nustry processing rolling an smelting metal ferrous of nustry non of nustry proucts plastic an rubber of nustry manufacturing fiber hemical inustry harmaceutical a processing fuel nuclear an coking processing petroleum of nustries inustry prouct paper an apermaking inustry apparel an garment etile etile inustry re an beverage lcohol manufacturing oo inustry processing foo sieline an gricultural ining inustry fishery husbanry an animal forestry griculture nufacturing of chemical ra materials an chemical proucts chemical an ra materials chemical of nufacturing

purpose euipment manufacturing euipment purpose

ince the manufacturinginustry alone accountsfor

ferrous metal ferrous his table gives the information proucts mineral metallic of each inustry he inustry is classifie base on the uielines for the nustry lassification of iste Companies issued by the China Securities Regulatory Commission (“CSRC”) in 201 he coe of category is inicate by a atin letter that

each inustry he inustry classifieis base on t is using the letters to represent ifferent categories in turn an the coe of class is inicate by toigit rabic numerals that

is coe in turn from ince the manufacturing manufacturing tea fine inustry alone accounts for of the hole market it is subivie into ifferent

classes base on to igital coes

e ndust nes eent

e e

griculture forestry animal husbanry an fishery

ining inustry

gricultural an sieline foo processing inustry ndust oo manufacturing

lcohol beverage an refine tea manufacturing etile inustry

etile garment an apparel inustry

apermaking an paper prouct inustry an coethe class of inicateis to by

nustries of petroleum processing coking an nuclear fuel processing anufacturing of chemical ra materials an chemical proucts

harmaceutical inustry

hemical fiber manufacturing he uielines f he coe of category of he coe inicateis aby atin letterthat

nustry of rubber an plastic proucts is it market holethe of nustry of nonmetallic mineral proucts nustry of ferrous metal smelting an rolling processing nustry of nonferrous metal etal prouct inustry or theor nustry lassification iste of

eneral euipment manufacturing nes pecialpurpose euipment manufacturing utomobile manufacturing anufacturing of railays ships aircrafts spacecraft an other transportationigitrabic numerals that euipment

subivie

eent eent

into ifferentinto

each industry iseach holeo less sample mentioned 0 aboe than the aboe is reproductionindustry rinting mediaand recording and ood processing t S R C1 C0 C C

2 1

ther manuacturing includes ther industries iersiied industriesindustry includes ccommodation and and catering () social or ealth ()() iersi ducation

less 1 than

o the hole hole the o industr ther entertainment and sports culture o ndustry industry management acility public and enironment conserancy ater industry serice technical and research Scientiic a easing industry Real estate industry inancial serices technology inormation and sotare transmission inormation o ndustry industry serice postal and storage ransport a holesale industry Construction supply and production ater gas and heat poer electric o ndustry industries manuacturing ther Special other and communications computers o anuacturing manuacturing euipment and machinery lectric

ood bamboo rattan alm iber and stra product industry stra product and iber ood bambooalm rattan purpose euipment manuacturing euipment purpose nd commercial serice industry serice commercial nd nd retail industry retail nd manuacturing industry manuacturing C lectric machinery and euipmenties manuacturing 1 2

2 C anuacturing o computers communications and other electronic euipment 2

C0 Specialpurpose euipment manuacturing 12

C1 ther manuacturing industries1 0 21

supplies sports and arts stationery entertainment industrial o anuacturing ndustry o electric poer heat gas and ater production and supply 22

(C2) Construction industry 2 1

holesale and retail industry 12 0

resource utiliation aste o comprehensieo ndustry ransport storage and postal serice industry 0

ndustry o inormation transmission sotare and inormation technology serices 1 0

inancial industry 11

Real estate industry 11

easing and commercial serice industry 2 10 Scientiic research and technical serice industry 20 02

ater conserancy enironment and public acility management industry euipment electronic 2 11 12

R (C20) ndustry o culture sports and entertainment 12

S ther industries2 11 t industry ootear related and products and eathers urs eathers

(C2)

1 ther mentioned industry each he o percentage manuacturing industries includes anuacturing o stationery industrial arts sports and entertainment supplies (C2) urniture manuacturing(C21) ood processing and ood bamboo rattan alm iber and stra product industry (C20) eathers urs eathers and related products and ootear industry (C1)

rinting and recording(C media reproduction industry (C2) ndustry o comprehensie utiliation o aste resources (C2) he percentage o each industry mentioned 2 ied industries (S)

aboe is less than 1 o the hole manuacturing industry 2 1 1 12 11 20 0 2 0 2 2 iersiied ) industries includes ccommodation and catering industry () ealth and social or () ducation () iersiied industries (S) he percentage o urniture manuacturing urniture

each industry mentioned aboe is less than 0 o the hole sample

he percentage o he o percentage 0 2 2 02 0 22 10 12 21 12 11 11 11

(C21) (C21) (C1) (C1) .2 0 - digital codes tablehis shos mispricingthe or each industry .0 0 .2 0 .4 0 .6 0 .8 0 .0 1 -.3 -.2 -.1 -.4 -.2 -.8 -.6 -.4 -.2 .0 .1 .2 .3 .0 .2 .4 .6 .0 .2 .4 102 01 02 01 02 01 02 01

03 03 03 03 04 04 04 04

05 05 05 05 06 06 06 06 he other industries are grouped based on the irst 07 07 07 07 08 08 08 08 R K A F 09 09 09 09 10 10 10 10

11 11 11 11 12 12 12 12 13 13 13 13

14 14 14 14 15 15 15 his15 table shos the mispricing or each industry he manuacturing industry is subdiided into dierent classes according to the last to digital codes he other industries are grouped based on the irst atin letter -1.50 -1.25 -1.00 -0.75 -0.50 -0.25 0.00 .0 0 .5 0 .0 1 .5 1 .0 2 .5 2 .0 3 -.4 -.2 -.8 -.6 -.4 -.2 Mispricing on industrial level .0 .2 .4 .6 .8 .0 .2

102 01 A 02 01 02 01 B 02 01 E D .4 0.00 3 .0 .0 03 03 .2 03 03 -0.25 2 .5 -.2 04 04 .0 04 04 -0.50 2 .0 05 05 -.2 05 05 -0.75 1 .5 -.4 06 06 -.4 06 06 -1.00 1 .0 -.6 07 07 07 07

-.6 -1.25 0 .5 he manuacturing industry subdiidedis intodierent classes according the to last 08 08 08 08 G B S -.8 -1.50 L 0 .0 -.8 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 09 09 09 09

10 F 10 10 G 10 I J 11 11 11 11

.6 .2 2 .4 level industrial on Mispricing 0 .0 12 12 .4 12 12 .0 2 .0 - 0 .2 13 13 13 13 .2 -.2 1 .6 - 0 .4 14 14 14 14 atin letter atin

.0 15 15 -.4 15 15 1 .2 - 0 .6

-.2 -.6 0 .8 - 0 .8 1 .4 0 -

-.4 .0 0 .4 0 .8 0 .2 1 -.8 .6 1 .4 0 .8 0 .2 1 .6 1 .0 2 .4 2 .0 0 .5 0 .0 1 .5 1 .0 2 0 .4 .5 2 .0 3 - 1 .0

01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 102 01 02 01 02 01

K L M N

.3 03 .8 03 03 1 .6 0 .4 04 04 04 .2 .6 1 .2 0 .0 .1 05 .4 05 05 0 .8 06 06 06 .0 .2 - 0 .4

07 07 07 0 .4 -.1 .0

08 08 08 - 0 .8 M E -.2 -.2 I 0 .0 09 09 09 -.3 -.4 - 0 .4 - 1 .2

01 02 03 04 05 06 07 08 09 10 10 11 12 13 14 15 01 02 0310 04 05 06 07 08 09 10 11 1210 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 11 11 11 R S 1 .0 12 3 .0 12 12

0 .8 13 2 .5 13 13

0 .6 14 2 .0 14 14 15 15 15 0 .4 1 .5

0 .2 1 .0 .2 1 - .8 0 - .4 0 - .0 1 - .8 0 - .6 0 - .4 0 - .2 0 - .0 0 .4 0 .0 0 0 .0 0 .5 -.8 -.6 -.4 -.2 .0 102 01 02 01 02 01 - 0 .2 0 .0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 03 03 03 04 04 04 05 05 05 06 06 06 1 07 07 07

08 08 08 N D J 09 09 09

10 10 10

11 11 11 12 12 12 13 13 13 to to 14 14 14 15 15 15

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 -.4 -.2 -.6 -.4 -.2 -.6 -.4 -.2 -.8 -.6 -.4 -.2 .0 .2 .0 .2 .4 .0 .2 .4 .6 .0 .2 02 02 02 02 02

04 04 04 04 04

06 06 06 06 06 C28 C37 C33 C34 C39 08 08 08 08 08 10 10 10 10 10 12 12 12 12 12 14 14 14 14 14

Mispricing on industrial level -0.8 -0.4 0.0 0.4 0.8 1.2 -.8 -.6 -.4 -.2 -.8 -.4 C39 -.6 C26-.4 -.2 -.6 -.4 -.2 C38 C27 C35 .0 .4 .8 .0 .2 .4 .6 .0 .2 .0 .2 .2 .2 .4 -0.2 .2 02 02 02 02 02 .0 .1 .0 .2 -0.4 .0

04 04 -.2 04 04 04 -.2 .0 -0.6 -.1 -.4 -.2 -.4 06 06 06 06 -.2 06 -0.8 -.6 -.3 C25 C15 C17 C36 C26 08 08 08 -.6 08 08 -.8 -.4 -1.0 -.4 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14

10 C34 10 10 C36 10 C30 10 C32 C29 .6 .2 .1 .4 0.0

.4 12 12 12 12 .0 12 .2 -0.2 .0 .2 -.1 .0 -0.4 14 14 14 14 14 .0 -.2 -.2 -.2 -0.6

-.2 -.3 -.4 -0.8 -.4 -.4 -.4 -.6 -1.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 -.6 -.4 -.2 -.6 -.4 -.2 -.5 -.4 -.3 -.2 -.1 -.4 -.2 -.6 .0 .2 -.6 .0 .2 .4 .6 -.5 .0 .1 .0 .2 .4 -.8 -1.2 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 02 02 02 02 Mispricing on industrial Mispricinglevel on industrial C33 C17 C13 C40 C31 04 04 04 0.2 04 04 .6 .6 1.6 0.0

0.0 .4 .4 1.2

06 06 06 06 06 -0.4 -0.2 .2 .2 0.8

-0.4 C41 .0 C18 C13 .0 C30 C38 0.4 -0.8 08 08 08 08 08 1 -0.6 -.2 -.2 0.0 -1.2

-0.8 10 10 -.4 10 10 -.4 10 -0.4

-1.0 -.6 -.6 -0.8 -1.6 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 12 12 12 12 12

C37 C15 C18 C14 C22 .4 14 14 1.2 14 14 3.0 14 .6 0.4

0.8 2.5 .4 .2 0.0 2.0 .2 0.4 -0.8 -0.4 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.4 0.8 1.2 1.6 -.6 -.4 -.2 -.8 -.6 -.4 -.2

.0 .0 .2 .4 .6 1.5 .0 .2 .4 .0 -0.4 0.0 1.0 -.2 -.2 02 02 02 02 -0.8 -0.4 0.5 -.4

-.4 04 -0.8 04 04 0.0 04 -.6 -1.2 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14

C28 06 06 C25 06 C41 06 .2 .8 .2 C14 C40 C32 C27 08 08 08 08 .0 .4 .0

-.2 10 10 10 10 .0 -.2 -.4

12 -.4 12 12 -.4 12 -.6

-.8 14 -.8 14 14 -.6 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14 02 04 06 08 10 12 14

-1.2 -0.8 -0.4 -1.6 -1.2 -0.8 -0.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.4 0.0 0.0 -.4 -.3 -.2 -.1 .0 .1 .2 02 02 02 02

04 04 04 104

06 06 06 06 C22 C31 C29 C35 08 08 08 08 10 10 10 10 12 12 12 12 14 14 14 14

EKONOMI OCH SAMHÄLLE Skrifter utgivna vid Svenska handelshögskolan

ECONOMICS AND SOCIETY Publications of the Hanken School of Economics

266. HANNA-RIITTA HARILAINEN: Managing Supplier Sustainability Risk. Helsinki 2014.

267. JACOB MICKELSSON: Customer Activity: A Perspective on Service Use. Helsinki 2014.

268. MIKAEL LAAKSO: Measuring Open Access: Studies of Web-enabled Innovation in Scientific Journal Publishing. Helsinki 2014.

269. HANNA KIEHELÄ: Dimensionality of the Consumer Perceived Value of Product Colour. Helsinki 2014.

270. LINDA TALLBERG: Processing Puppies: An Animal Shelter Ethnography. Helsinki 2014.

271. PIA HELLMAN: The Effect of Communicating E-service Benefits on Consumer E- service Adoption. Helsinki 2014.

272. PENG WANG: Four Essays on Corporate Finance of Chinese Listed Firms. Helsinki 2014.

273. DHANAY MARÍA CADILLO CHANDLER: The Role of Patents in Latin American Development: 'models of protection' of pharmaceutical patents and access to medicines in Brazil, Chile and Venezuela. Helsinki 2014.

274. CARLOS A. DIAZ RUIZ: Market Representations in Action: Foundations for the Performativity of Representations in Marketing. Helsinki 2014.

275. IRA HAAVISTO: Performance in Humanitarian Supply Chains. Helsinki 2014.

276. SALLA PÖYRY: Essays on Financial Market Frictions and Imperfections. Helsinki 2014.

277. HELENA LIEWENDAHL: What Motivates Employees to Live up to Value Prom-ises: An Employee Discourse. Helsinki 2014.

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MO ZHANG EKONOMI OCH SAMHÄLLE EKONOMI SOCIETY AND ECONOMICS ON MISPRICING ESSAYS STOCK IN THE CHINESE MARKET

MO ZHANG – ESSAYS ON MISPRICING IN THE CHINESE STOCK MARKET 302 ------