Is Moscow Stock Exchange Sufficiently Liquid

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In requirements for fulfillmentof the Master thedegreeArts partial of of Is Moscow Stock Exchange Sufficiently Liquid Sufficiently StockExchange Moscow Is T he Evidence from Cross from he Evidence E Supervisor: ProfessorKondor Peter conomic Policy Markets onGlobal Central European University Department ofEconomics Budapest, Hungary Ekaterina Serikova Submitted to Submitted 2012 By

Listing

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Keywords: Moscow Exchange. Stock better, become not does situation the time over Moreover, Russia. to investors foreign more attracting of think should authorities policy Also, prices. the equalize to and integrated it make to market Fir authorities. policy market financial not is market for implications several have Russian them of Both market. financial that global the in enough integrated represent results the hand, other the From markets. two on Londo in and Russia in stocks for returns determine that effects local significant statistically show findings our hand, one the From estimation. OLS for model the into taken were receipts depositary as London in and Russia in traded stocks goa stated the reach To 2012. March, to 2006 from period the for dynamics h ppr netgts h lqiiy f ocw tc ecag, nlzn its analyzing exchange, Stock Moscow of liquidity the investigates paper The

emerging exchange, markets,stock liquidity, cross listing hc cls o imdae teto t te rbe o ilqiiy f the of illiquidity of problem the to attention immediate for calls which

stly, more professional arbitrageurs should be on the on be should arbitrageurs professional more stly, Abstract i

n, allowing for persistent arbitrage persistent for allowing n,

l, cross listed listed cross l, CEU eTD Collection

being away. sofar t me help hesis. Special thanks to my parents and f and parents my to thanks Special hesis. Travel

during my work. Also, Also, work. my during I would like to thank my supervisor, my thank to like Iwould

Research Grant, during which I managed to collect a collect to managed I which during Grant, Research

I would like to express my sincere gratitude to gratitude sincere my express to like would I Acknowledgements amily for the for amily Professor ii

Peter K Peter ir

huge support and belief in me even even me in belief and support huge ondor, for valuable advices valuable for ondor, ll the necessary data for this this for data necessary the ll

CEU for giving for CEU

and CEU eTD Collection

Biblio Appendixes Conclusion 3.3.2. Dynamics themodel to 3.3.1. Extension 3.3. Results 3.2. Data 3.1. The baseline model Chapter 3.The model lis 2.3. Cross 2.2. Cross 2.1. Cross LiteratureChapter 2. review oncross listing DRs 1.3. Russian London1.2. and dep Exchange its Stock 1.1. Chapter onthemarkets 1. Current situation Introduction

Russian stockRussian exchange MICEX graphy

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...... ting ofRussian stocks

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Table of of Table ...... ositary receipts

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...... iii Contents

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27 24 21 21 16 13 60 47 45 39 38 36 32 30 30

4 4 1

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RUR RTS MICEX LSE ISIN GDR GBP CBR ADR

– – – – – – – –

London

Russian TradingRussian System

Great Pound Britain InternationalIdentification Security Number CentralRussia Bank of Russian Ruble Russian Global depositoryreceipts Americanreceipts depository

–

Moscow Interbank CurrencyMoscow Exchange Stock Exchange Stock

List of abbreviations of List iv

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the market does not tend to improve to tend not does market the between markets’ is largely for larger are effects” “local e LSE. Russia of instead London in IPOs their doing chose companies Russian exchange: London to exchange Russian from migration” “issuers’ deposita issue companies Russian accordin that, fact the by explained be can model the for LSE there ex we However, exchanges. currency and indexes localas factors such local main ofinclusion the its to due research our ofpurpose the paper Debora’s and Froot is research the for model baseline The that any features the for account accounting while shocks, into stocks’ specific take not does it because liquidity analyzing for method advantageous listing cross of model OLS exchanges before, existing which tookplacein2011. two the of merger the and Exchange Stock Moscow the of development the was goal the C Financial International an create to plan pcain o ivsos are investors of xpectations

rdd oe ciey accounting actively, more traded

are independent effects independent are h find The The goalThe istoanalyze paper ofthis Moscow E liquidity Stock of the strategic innovative an announced Medvedev Dmitry Russia, of president the 2008 In

Russian currency and returns of Russ of returns and currency Russian indexes. Exchange rate is more significant for sm for significant more is rate Exchange indexes. ns o ings or ae show paper our f

Russian stocks on London Stock Exchange. Stock London on stocks Russian

of currency exchange and VIX index VIX and exchange currency of

impor ry receipts mostly on mostly receipts ry - ; instead, the model seems to describe movements of the the of movements describe to seems model the instead, ; at eemns f rc return price of determines tant capitalized stocks on those markets where the company the where markets those on stocks capitalized o lre cmvmn o return of comovement larger for

Introduction ht oa idxs crec ecag rt, n the and rate, exchange currency indexes, local that enter in Moscow. One of the priorities to achieve to priorities the of One Moscow. in enter edd h mdl y dig I idx because index VIX adding by model the tended 1

, together with outflow of trading activity on activity trading of outflow with together , ian stock relative to London to relative stock ian

LSE. Moreover, there is a is there Moreover, LSE. all stocks showing comovement comovement showing stocks all g to The Bank of New York New of Bank The to g matter on both markets only. markets both on matter

(1997)

separately

differential

that is relevant for relevant is that Cross listing is an an is listing Cross xchange using t differential . After the After . . The choice of choice The s

So . problem of problem with s -

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nowadays o the give to order in presented be will exchanges London and thatcould stocks liquid most betradedgovernment’shands. being instead inthe of USD is that Index MICEX of 27% for accounts which companies, largest exchange. solutions ofthe One the on investors foreign and domestic both attracting for measures pursue should authorities Vishny and Scleifer with consistent nowadays. ca they 2, Chapter in discussed be will which models, the of simplicity the and stocks, traded actively found R underlying dividing of model listing cross of day the on returns abnormal used Smirnova aspects. several in different are and issuing through listing cross about studies regulations. and policy its in changes further pursue to order in creating whilst beca significan less leaving better, returns Jithendranathan me more riskme more av no arbitrage between them. between arbitrage no

The structure of the paper is the following: firstly, following:the is paper the structureof The is which arbitrage, persistent of possibility the shows model the words, other In Thus, the importance of the paper is obvious is paper the of importance the Thus, oe tm, hc ws expected was which time, over t Imp . b ue ol fr itrcl nlss f h pr, o fr oiy implications policy for not part, the of analysis historical for only used be n

policy rat o oe ht eety at recently, that note to ortant ’s erseand their expectations influence

for Moscow Stock Exchange it iscrucial to it Moscow Exchange for Stock (2006) lc fr admes Epcain’ volatility Expectations’ randomness. for place

papers are t are papers

is ussian stock’s price to its depositary r depositary its to price stock’s ussian

to lower the governmentto lower the inthe share Due to several limitations, namely old data, exclusion og exclusion data, old namely limitations, several to Due s model ’s he most relevant for this research this for relevant most he

usa dpstr rcit: Smirnova receipts: depositary Russian

2 and several days after days several and eas atr and after because

h ed f 2011, of end the 19) T ipoe h stain policy situation the improve To (1997). GRH oe ad found and model GARCH a

first of all for policy implications policy for all of first

returns differentials. differentials. returns the current situation on current situation verall picture of both markets both of picture verall Moreover, there are only fe only are there Moreover,

during during know how liquid it istoday it liquid know how the two largest largest two the . Jithendranathan used a a used Jithendranathan . ownership eceipts in the US and US the in eceipts h cii investors crisis the

432 million million 432 . Their .

eoe more becomes

the structure of structure of

researches ’s negative Russia Russian

(2004) : of the of

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CEU eTD Collection

explanations andexplanations relevant policy recommendations. especi markets, emerging last in pursued researchers few only while experience, and have exchanges their because countries developed for literature of plenty is ad the measure economists other how and listing cross do companies why analyze to well as economies developing for and developed countries for presented be will listing cross on review literature the Exchange, Russian selecte was listing cross since Then, chapter. first merged were RTS, and MICEX exchanges, ally for Russia. Russia. for ally The paper closes with our model, its results, their their results, its model, our with closes paper The vantages and disadvantages of cross listing. There listing. cross of disadvantages and vantages , which has several consequences analyzed in the in analyzed consequences several has which , 3

a a a t maue h lqiiy of liquidity the measure to way a as d few

er ae vial for available are years a longer history longer CEU eTD Collection occurr RTS of centers clearing of merge the 2008 in traded, financial tobe started futures In and options futures. tocommodity2001 instruments fromequities cash of range full the trading now Russia, in market stock regulated first the as 1995 estab was RTS merger. the before functioning were exchanges these how analyze firstly us Let similarities. and differences their with together Russia in exchanges different Interbank (MICEX) Currency Exchange mak main agenda o global center. financial a Moscow make to target the announced publicly first Medvedev, Dmitry Russia, lat in alternative: latter the chosen has aspects, different in world the in position leading its restore to attempts its in Russia, Currently, position. competitive away the research. data statistical and way the introduces depositorycurrentof the receiptsituation then studied, exchanges’is Russian merger have to order in features specific a egr f w Rsin xhne: usa Tae ytm RS ad Moscow and (RTS) System Trade Russian exchanges: Russian two of merger a e

In the globalization period each transition country is faced with a choice: either to stay to either choice: a with faced is country transition each period globalization the In 1.1. and structure their analyze to markets, both present to is chapter this of goal The First center, financialglobal a conceptof the In from competing with already settled global leaders or to intervene and try to get its own its get to try and intervene to or leadersglobal settled already with competing from

of all, there is a reasonable question concerning the initial existence of the two two the of existence initial the concerning question reasonable a is there all, of

f financial andeconomicf Russi

Now

of Russian ADRs in London, which explains the choice of exactly LSE for for LSE exactlychoiceof the explains which London,in ADRs Russian of companies do cross listing there. The chapter fin chapter The there. listing cross do companies an an stock exchange MICEX the creation of International Financial Center in Moscow is Moscow in Center Financial International of creation the Chapter 1. an Current situation on the on markets situation Current overview about the exchanges that we analyze. Firstly, Firstly, analyze. we that exchanges the about overview

strategy of Russ of strategy which 4

took place 2011. 19, onDecember took

financial market financial ia.

ed and in 2010 RTS Exchange RTS 2010 in and ed

policy authorities authorities policy 20 te rsdn of president the 2008 e ishes with ishes

an an

now decided to decided overview s on LSE on s ihd in lished on the on

CEU eTD Collection Index RTS the 2010, In capitalization. Index RTS the of 4% roughly up makes sector 8% about for accounts sector utilities electric The sectors. mining & metals the and finance & banking the are Index RTS the in reflected industries large Other lately. positions their strengthening been have Howevsectors other representing index. the of capitalization total the of 47% than more for account market capitalizationwa i each of proportion the Indices, RTS the on issuers individual of highly co generallyis it and 1995 1, September on calculated wasStandard Index RTS time first Forthe the first held RTS of branch this 2010 In sugar. and metals products, oil oil, Indices, RTS currency, rates, interest term short bonds, companies, Russian of shares on offered are contracts 47 areinvestors. Over 500 securities trading market; onthis currency. foreign and rubles by depositing;asset 100% absence of several products: of consists RTS Today Europe. in RTS of representative a as created was Limited Europe nsidered to be the overall indicator for Russian securities market. 50 of the most liquid and liquid most the of 50 market. securities Russian for indicator overall the be to nsidered RTS exchange had exchange RTS    The structure of RTS Index can be represented in Figure 1. The oil & gas issuers issuers gas & oil The 1. Figure in represented be can Index RTS of structure The -

capitalized securities were selected to consist RTS Index. To limit the impact of stocks of impact thelimit To Index. RTS consist to selected weresecurities capitalized FORTS R Standard RTS

place in the world accordingplace offutures intheto world tradevolume contracts. TS Classica TS -

futures and futures - -

the only trading platform in Russia that allows for settlement in both both in settlement for allows that Russia in platform trading only the an equity market for the most liquid Russian securities characterized securities Russian liquid most the for market equity an s capped allowedat level. acertains maximum

its own indicators own its

options market with ruble settlement traded since 2001. Today, 2001. since traded settlement ruble with market options RTS Classica is equally accessible to both Russian and foreign and Russian both to accessible equally is Classica RTS

–

indices depending on the industries and regions. regions. and industries the on depending indices 5

wees h ceia industry chemical the whereas , ssuer’s securities in t in securities ssuer’s

er, companies companies er, - he total he weight CEU eTD Collection Exch Commodities National Center, Depositary National House, Settlement MICEX the day), every issuers Russian leading of hundreds of bonds and shares in trading holds which exchange, stock Russian leading (the CJSC Exchange Stock MICEX platform: tec unified a using services their perform that companies several includes currently Group MICEX The rate. MICEX to currency Russian of pegging of mechanism official the steps purchasein Russian of Association the commercial leading among growth50% of thetotal Uralkali than more for NOVATEK, accounts which up points 182 Index RTS the moved together taken constituents Sberbank, NICKEL, NORILSK MMC of shares ordinary were leaders effect positive The points). 325.7 by (or 22.5% by increased in forming the infrastructure of the Russian financial market. In May 1996 CBR gaveup CBR 1996 InMay market. financial Russian the of infrastructure formingthe in MICEX Group, the other exchange, was established in 1992 as a result of agreement agreement of result a as 1992 in established was exchange, other the Group, MICEX - sale of foreign currencies for Russian rubles. MICEX creation was one of the first the of onewas creation MICEXrubles. Russian currenciesfor foreign of sale

(RTS, 2011) (RTS, B banks, Central Bank of Russia (CBR), Moscow government, and and government, Moscow (CBR), Russia of Bank Central banks, anks, the main goal of which was the initiative to start operating start to initiative the was which of goal main the anks, .

and Gazprom. These These Gazprom. and ange, National National ange, hnological

CEU eTD Collection misprese magnitude, same the by appreciates Index RTS depreciates, rate exchange Dollar US of changes the in changes the by influenced is Index RTS of dynamics the Thus, rubles. Russian in is Index MICEX while dollars, US in denominated Surgutneftegas (5,38%). and (8,53%), Nornikel (13,85%), Sberbank (14,91%), Lukoil (15%), Gazprom to belongs price oil Index correlate should and RTS isrepresentedgassomehow thus, with the sector; index oil by RTS’ of that to similar be to seems Ex the on traded stocks liquid most 10 the of change price average the measuring Index, 10 MICEX the offers Exchange Stock MICEX the Index, in the exchange Moscow in and market inlargefinanc both organizations Russian leading 1,500 about to services depositary and clearing, settlement trade, provide companies group’s The etc. exchanges, regional Center, Clearing MICEX has a similar index’ scheme as RTS (Figure 2), in addition to the main MICEX main the to addition in 2), (Figure RTS as scheme index’ similar a has MICEX The difference between these two these between differenceThe –

the price is up (or f up (or priceis the

utures for oil), the index is also up. The most weight to the Index Index the mostThe weightto alsoup. is index the oil), forutures -

as we can see from from see can we as indexes 7

is that RTS Index is based on the st the on based Indexis RTS that is change. MICEX index structure also also structure index MICEX change. Figure 2 Figure ial - industrial centersindustrial ofRussia. , the significant part of the of part significant the , nting the real price price real the nting

participants participants ock prices prices ock –

if USD if

- CEU eTD Collection 2011) and IPO, do will News, exchange (Forbes billion $4,5 exceeds joint already capitalization its estimates, new experts’ to according the that planned is it 2013 By shares. exchange is rest the and cash in out paid be will stocks of 35% negotiated, was As USD estimated was value RTS’ i Taking signed. was merger the of idea the MICEX, concerning of size larger much consideration agreement final the 29, June on and merge, the for procedures exact the out work to began directors of board 2011 February In versus RUR 11, 2billion 3,1 bi derivatives R of vo trade the MICEX on 2010: from data statistical the by supported be can This trading. currency and bonds, stocks, in leader isfree ofRTS which 30% government. holds ofownership,whilethe from ownership the Bank Central is shareholder major MICEX’ example, For shareholders. of composition and all of First aspects. several market dynamics. of sense the in representative more Index MICEX makes which graph), the (see RTS of that volu trade the Generally, information. wider and reliable Index RTS of advantage the is this securities; 30 covers Index MICEX while securities, 50 of basis the on calculated is Index RTS Secondly, securities. of change R ad currency and UR,

Generally speaki Generally and indices exchanges’ from Aside T he process of the merger started at the end of 2010 when first negotiations took place. took negotiations first when 2010 of end the at started merger the of process he –

29,3 billion 29,3

ng, RTS is a country leader in derivatives trading, while MICEX is a a is MICEX while trading, derivatives in leader country a is RTS ng, –

RUR. MICEX stock exchange is much larger than that of MICEX of that than larger much is exchange stock MICEX RUR.

95 billion 79,5 they have different complicated structures, technical indicators, indicators, technical structures, complicated different have they llion in RTS in in2010llion ( 1,15 billion, MICEX billion, 1,15 lume of stocks was 13,3 billion RUR, bonds RUR, billion 13,3 was stocks of lume

U, hl on while RUR, trade volumes, the exchanges were exchangesthe volumes, trade 8

RTS andMICEXRTS websites). official –

acquiring RTS was obvious ( obvious was RTS acquiring

three times more expensive than RTS. than expensive more times three me in MICEX is much higher than than higher much is MICEX in me RTS RTS –

stocks in new merged stock stock merged new in –

, billion 3,1

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UR, nto –

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Although this range of financial instruments seems to be a great advantage, this is not is this advantage, great a be to seems instruments financial of range this Although

Hong Kong, Hong

and Brazilianand exchanges 1) (Table of the new exchange among its competitors from other developing developing other from competitors its among exchange new the of

broad (the full specter of services in London) or narrow (as (as narrow or London) in services of specter full (the broad 9

fferent spheres of economic and and economic of spheres fferent

CEU eTD Collection this USA and UK the in while GDP, Russia’s with comparing level low considerable the at stays value total the but trades), derivatives’ in exchanges biggest 10 among was RTS 2010 and Stock Percentage Derivatives: concerning especially huge, is growth for potential the that see obviously can US and Germany, China Brazil, with derivatives of volume trade the comparing Rus in them trade to opportunity the and resources raw many having in MICEX for ma stock domestic of size huge the of because trades stocks in advantage competitive great a has YorkNew or London, example, forare concentratedin bonds internationalof 70% and metals financial underdevelopedgrowth sphere isso can thatthe be huge. extensively developed be can sector banking the development, exchange Beside privatization Russian in transactions especially grows, place, market take financial will When transactions privatization. privatization be can direction this in perspectives the just are there now, for f wide specialization of propositions narrow such no is there Russia In development. rkets the center of which is Wall Street. Some experts say that the largest potential to grow to potential largest the saythat experts Some Street. Wall is which of center the rkets Moreover, taking th taking Moreover, A ccording to the statistics, the to ccording - ’ RTS is a derivative market, which will help Russia to exploit fully its advantages fullyits exploit to Russia help will which market, derivative a is RTS potential inancial services both in financial sector and on the exchange. One of One exchange. the on and sector financial in both services inancial

in the worldwide context: about USD 200 billion (Guriev, 2011). 2011). (Guriev, billion 200 USD about context: worldwide the in e specializations of exchanges in more detail, 90% of world trade of of trade world of 90% detail, more in exchanges of specializations e the derivative market in Russia is developing very well (in well very developing is Russia in market derivative the 10

sian currency. Also, currency. sian

(Table 2) (Table –

the current the

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huge , we we , CEU eTD Collection 1 194 and MICEX on investors 622 were there trade tothel existing of share stock its increase to exchange new a for potential huge a is there that demonstrate can we capita, per GDP against GDP to relative trading stock of share the regression of result my something be not will oil for prices domestic the and demand large have will exchanges resources’ raw Russian happens, this When prices. market of creation the and production oil in innovations in interested be will who investors get will companies these result, a as and laws, antimonopoly need we Thus, companies. integrated vertically large of hands the in concentrated is oil all because market, derivative domestic no is there and London well already are prices export for markets derivatives th exceeds number

Koms

it will be too d too be will it In addition, there seems to be a real broadening of the clients because before the merger merger the before because clients the of broadening real a be to seems there addition, In omolskaya pravda Newspaper, Newspaper, pravda omolskaya –

odnPtoemEcag, odnMtl Exch Metal London Exchange, Petroleum London i GP oe hn 0 ie ( times 10 than more GDP eir ifficult for Russia to be a be to Russia for ifficult

evel ofGDPevel per cap

http://usa.kp.ru/daily/25835/2808815/ ita (Figure 4 ita (Figure n equal competitor being competitor equal n 11

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n T, mn wih 7 ivsos who investors 178 which among RTS, on dnk 2012 Zdenek, ).

- established (USA (USA established ange, London Gold Exchange) Gold London ange, , in , Russian 1 . However, ).

stical. In addition, as a a as addition, In stical. a new player. Rather, Rather, player. new a

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h risk the CBOE, CME; CME; CBOE,

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oil oil CEU eTD Collection 2 stability the increase to Thus, MICEX. on mostly trade to rational is it direction, same the in topr on RTS market directions,USD exchange then andthemove thetrades rate operate inopposite mostly chart pr the demonstrate To countries. developing the among still is shocks external by caused fluctuation of risk the reduce to helped currencies different in and instruments financial of set different exceed amount byandtomore revenue its than 500$ million 2015, may RUB 353.8 reached period mi same the for RTS of profit net the billion, RUB5.5 of profit year RTS for times 2 and MICEX for 4.5 increased 2011 of mill that for fee discounted special a is there extended is investors MICEX) from 28% and RTS from (91% exchanges these both on traded

Kommer llion. Financial market experts believe that the net profit of the integrated exchange may may exchange integrated the of profit net the that believe experts market Financial llion. ion initial capital (MICEX, 2011

that summarizestheargument nlzn te eaie esetvs te xsec o to ifrn ecags wi exchanges different two of existence the perspectives, negative the Analyzing at Looking These data is supported by RTS Analytic Research Center who claims that when the the when that claims who Center Research Analytic RTS by supported is data These sant News (2011), (2011), News sant ovide the market with stability, while when USD exchange rate andexchange marketmove when rate USD while ovide the stability, marketwith

the financial results of the new merged exchange, its profits for the first half first the for profits its exchange, merged new the of results financial the

–

for those RTS investors who did not access MICEX before the merger the beforeMICEX access not did who investors RTS those for http://www.kommersant.ua/doc

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this is extremely important in the context that Russia Russia that context the in important extremely is this –

just 30 USD instead of the requirement of 1 USD 1 of requirement the of instead USD 30 just 12

- rss/1852611 -

oblem more clearly, here is the the is here clearly, more oblem (inRussian) on - year. MICEX reports a net a reports MICEX year.

850$ million

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so, the pool of of pool the so, 2 .

th CEU eTD Collection 3 billion 37 of capitalization total enterprise new 2012) (LSE, billion 3,500 over is capitalization market total the and Market, Main the on trade listings are requirements listing the and performance, high with companies reputable for solely is Market Main The (AIM). Market Investment Alternative the and Market Main the markets: stock different two of comprised certainlygood capitalization result tostartwith. a market in markets emerging and European of exchanges biggest economy. financial our of advantage comparative a such lose to likely is exchanges of merger a Thus, le at be stability. overall for better the have, they securities financial different more the and exchanges should there risks, crisis external against exchange stock Russian the of

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ASDVFN, Financial market website market Financial ASDVFN, London Stock Exchange Stock London In general, as we as general, In odn tc E Stock London

. The Alternative Investment Market on the other hand trades small trades hand other the on MarketInvestment Alternative The . s with high growth potential. Over 1,060 companies list on this market, with a with market, this on list companies 1,060 Over potential. growth high with s

xchange

see on the Table the on see

and its depositary receipts depositary its and

3 , (LSE)

. Currently, LSE is one of the most popular destinations for destinations popular most the of one is LSE Currently, . http://uk.advfn.com/ rather strict. Approximately 1,800 of the LSE's company company LSE's the of 1,800 Approximately strict. rather

s on is

below, o te edn ecags n h wrd I is It world. the in exchanges leading the of e 13

Russian exchange in 2011 was among 10 10 among was 2011 in exchange Russian

- capitalized or capitalized

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s two ast ht is that

CEU eTD Collection depositary American are popular most the DRs Among 2011). York, New of (Bank above con when surprising (Ba as well as base shareholder their of company of side the From market. local t difficulties the avoid and investor, foreign a from English in published materials reporting and analytical depositaries, central international dollars, US in trade to opportunity an gets shareholder prog 2000 for advantage main The 2012). (LSE, shares underlying the from independently traded and listed be can which shares company’s a of number given a of ownership represent which banks the for and them buy who shareholders the for both advantageous are that (DR) receipt depositary issue Londonfor tocompete worldwide. r regulatory strict with together currently position economic economists forecast some as Kong, Hong or Brazil, China, as such markets developing to shift to when environment global new in especially LSE for challenging (PriceWaterHouseCoopers 2011 March of as international listing globa listings foreign many DRs’ icho One of the most common ways for the company to start to be cross listed on LSE, is to to is LSE, on listed cross be to start to company the for ways common most the of One a cause may . oa 2011). rova, shareholders is the opportunity to diversify their portfolios since there are now about now are there since portfolios their diversify opportunityto the is shareholders In addition, there are there addition, In rams of depositary receipts in receipts depositary of rams companies which issue them. DRs are negotiable certificates issued by depositary by issued certificates negotiable are DRs them. issue which companies

the most most the

sidering all of the mutual advantages of advantages mutual the of all sidering Thus, Thus, the lly ik o LE n h future the in LSE for risk

– value fears that UK’s ties to the European Union with its instable its with Union European the to ties UK’s that fears

some experts say that such a such that say experts some

o have to of higher - issuer of DR of issuer

traded 76 countries. By purchasing a depositary a purchasing By countries. 76

iied pi i U dlas and dollars, US in paid dividends iudt and liquidity 14

R wrdie n 01 38 billion, $3.8 2011, in worldwide DRs hey would face i face would hey s , a clear advantage is the diversification diversification the is advantage clear a , – : currently 20.4% of listings were were listings of 20.4% currently :

so, an investor can buy a security security a buy can investor an so, lower lower o get to 2011). , egime, will make it even harder even it make will egime,

DRs

heavy

foreign compan foreign

ot f aia advantages. capital of cost

all for both parties both for

f they bought they f dependence on dependence It may be even more more even be may It h pyet through payments the ies will tend will ies

explained o obtain to receipt, a receipt, it

foreign foreign

on the the on s not is

CEU eTD Collection London in listed a are ADRs time, same the At US. the in buyers institutional qualified at aimed non at aimed is S Reg that is difference main The receipts. more One liquidity. border cross increased for allows which (DTC), Company Trust in Depositary or Bank Euroclear in settled are dividends the and Book Order International London’s private or US public a make to wish issuer’s the on depends that ADR III Level or ADR 144a Rule either element US the and US), the and (London markets more or two access to used usually PSM on traded is Corporation, A Autho Listing UK the by checking to subject are DRs markets, instituti London’s by supported market the from financing additional the get to allowing listing, for regime regulatory flexible more offers alternative This securities. convertible and DRs debt, including securities, specialist of Exchange’ the is PSM The (PSM). Market Securities Professional the except the US. receip depositary Global while US, the within only traded are receipts depositary American traded: with Gl and (ADR) receipts D R

s a s American law, while the difference between them is in the markets where they can be be can they where markets the in is them between difference the while law, American Currently, there are two alternatives of issuing DRs in LSE: on the Main Market or on on or Market Main the on LSE: in DRs issuing of alternatives two are there Currently, ts are securities with limited with securities are ts type of DRs is Reg S depositary receipts that are considered to be global depositary depositary global be to considered are that receipts depositary S Reg is DRs of type re traded on the Main Market (30 out of 31 of out (30 Market Main the on traded re

placement. So, the securities are traded being denominated in US dollars on on dollars US in denominated being traded are securities the So, placement.

(LSE 2012) website, obal depositary receipts (GDR). They are both are They (GDR). receipts depositary obal

( as of April, 2012 April, of as circulation, can be traded in traded be can circulation, .

nl netr’ omnt. hn itn o both on listing When community. investors’ onal 15

) . Global depositary receipts in London are are London in receipts depositary Global ), while only one company, Federal Grid Federal company, one only while ), - Americans whereas rule 144A is 144A rule whereas Americans rity. The majority of Russian Russian of majority The rity.

Europe and other countries other and Europe issued with compliance with issued s market for the listing the for market s lso traded and and traded lso

in it in

is is

CEU eTD Collection 4 years six IPO companies the on share ofRussian thatmade Exchange Stock London above discussed accounts33.4 billion the volumeof for DRs,being Russian 19.42% o and value, world of 13.23% constituting DRs, Russian of value the of billion $505 reports York New of Bank the liquidity, Considering region. the in programs sponsored all of 55.2% Eur Eastern in DRs programs sponsored new all of 92.8% for accounted DRs Russian w the in US, ando They

Bloomberg, Bloomberg,

urnl, n h etn o cetn te nentoa Fnnil etr n Moscow, in Center Financial International the creating of extent the in Currently, Cross 1.3. issue DRs issue orld is $505 billion as of 2011, of as billion $505 is orld nly parallelly or later were listed in European exchanges. The value of Russia’s DRs DRs Russia’s of exchanges. value The inEuropean later were listed parallellyor nly Russian DRs Russian - listing using DRs is very popular way of going abroad for Russian companies. companies. Russian for abroad going of way popular very is DRs using listing http://www.bloomberg.com/markets/

tee s sros rbe o otlw f Ps f usa companies Russian of IPOs of outflow of problem serious a is there , in different markets all over the world. Initially, all DRs were listed in the in listed were DRs all Initially, world. the over all markets different in

–

“issuers’ migration” as Russian econo Russian as migration” “issuers’

making 13.3% of all the DRs in the world. In 2011 In world. the in DRs the all of 13.3% making

LSEwas 57%( about mists f the world volume f the

call it. D it. call uring the last last the uring Figure 5 ope and and ope

4 . ).

to to

CEU eTD Collection if now trading companies’ Russian total of 90.2% constitutes share their No bank, VTB nikel, Norilskij Rosneft, Lukoil, Gazprom, as such companies Londoncompanies Exchange Stock in London to Russian from outflow activity trading underlyingin Russi stockstraded sh the years 368 16, GBP of turnover monthly wit LSE in Book Order International in exchange LSE wa The other side of the problem is the outflow of trading activity from Russian to London to Russian from activity trading of outflow the is problem the of side other The trad average the LSE, from taken data the to According h trading The the to Due

the share will stay at the same high level in the future or or future the in level high same the at stay will share the s rather volatile s

for already cross listed stocks listed cross already for r o tascin i Lno hs been has London in transactions of are

w iprat rbes rsn i Russia in arising problems important two f usa companies Russian of

from 2006to2012 from a

(Moscow IFC(Moscow Strategic Session,2012) million in March, 2012 March, in million

onl : currently, there are 31 are there currently, : total h y , but .

n S i cnetae msl aog few among mostly concentrated is LSE on 17 still

aiaiain f B 2981 ilo with million 289,851 GBP of capitalization the paper will study cross study will paper the increasing

bu 65% about

(LSE, 2012) (LSE,

such as issuers’ migration and and migration issuers’ as such over time

oueo usa R on DRs Russian of volume e Russian companies registered companies Russian

( Figure 7 Figure Russian companies will will companies Russian of

. During the last five five last the During . ( . trading volumes of of volumes trading Figure 6

- listing of Russian Russian of listing ) . vatek, Uralkalij vatek,

We cannot s cannot We ).

ay ; CEU eTD Collection that liquidity is one say So, can factors. being between important criterion other difference most withhuge the place first the on is liquidity market exactly and IPO, exchange/market stock choosing when to according example, Intelligence surveyEconomist (2011) Unit For volatility. price increased to due increases risk falls, activity as changes: price on impact large a has this and traded are securities the which with ease, a matters itself liquidity companies The London. why in factors stocks their decisive allocate most the of one is some liquidity all, high of that First claim points. researchers several to due issue important an is which exchange, Russian t Thus, market. the of liquidity companyIPOmake is planning inSingapore to by2012). 2013 (Forbes, alrea Lukoil example, for but, others, and Singapore, China, as such quickly developing are that markets emerging to trading the shifting of pattern overall follow One of the reasons why Russian companies leave Russian market is insufficient insufficient is market Russian leave companies Russian why reasons the of One the ki ng on themarket.ng ( he particular question of the research is the mark the is research the of question particular he Figure 8 about the most important factors for the companies for the important factors most about the 18

lot because it determines the the determines it because lot dy announced that the the that announced dy

et liquidity of of liquidity et

CEU eTD Collection 5 interflows trade among different world. platforms the in and liquidity, the scarcity of borders, across restricted movement capital as such challenges, crisis financial world the to response of kind a is exchanges of mergers p market prevailing the below or above significantly price at available less is shares movements of number larger price because the drive trades individual that meaning market the of pool internat potential large a faces company each because increases case this in liquidity Stock 2011). 9, March Money, (CNN countries Nordic and Baltic in exchanges different 7 of exchange Fran of exchanges national most the world: merger Euronext the include the activities merger noteworthy over all mergers exchanges’ stock of reasons the of one is liquidity single every of effect because

- ie (onl, 01. te eprs fr example, for experts, Other 2011). (Pownall, rices

RBC, 2011, 2011, RBC,

From more liquid market is more attractive because the higher the volatility the less the the less the volatility the higher the because attractive more is market liquid more http://top.rbc.ru/finances/29/05/2012/652650.shtml

nte pit f view, of point another ional investors. One more reason for improving liquidity is the deepening of deepening the is liquidity improving for reason more One investors. ional

transaction ce, Belgium, Netherlands, and Portugal; the OMX merger OMX the Portugal; and Netherlands, Belgium, ce,

n pr on rm netr’ esetv, liqui perspective, investors’ from ice changes of other stocks. Moreover, increased increased Moreover, stocks. other of changes ice 19

, in Russian in , Dushin

–

a joint stock exchange of former former of exchange stock joint a 5 ,

of trend recent that propose

control of free capital offree control iy s ky issue key a is dity –

joint joint

CEU eTD Collection marketscross stocks. listed for both on impact an have they until matter not do effects such because market particular a for elimin to allows it because advantageous is listing cross through liquidity market testing of way This London. in and Russia in listed cross are that stocks the during crises. increase both times, good during costs trading to inversely moves activity trading whereas Thus, crisis. the during later only declining fell, prices as increases activity trading instead beg the at markets: emerging in liquidity and episodes crisis between link strong a is there (2007), Yeyati to According issue. liquidity considering crisis the in differently bit a behave Russia, as such markets, Emerging liquidity. financ the stabilize to order in attempts coordinated fast with together policies alternative several implement and create to world the over all authorities and makers 2007 wh in crisis financial the after and during significant more even became liquidity en the lack of liquidity in the funding and foreign exchange markets required all policy all required markets exchange foreign and funding the in liquidity of lack the en Thus, markets’ financial of role central the (2011), al et Mancini by judging Moreover,

to analyze the liquidity of Russian exchange, it is sensible to make an analysis on analysis an make to sensible is it exchange, Russian of liquidity the analyze to

inning of the crisis there is no market slow down, slow market no is there crisis the of inning 20

ate specific effects inherent effects specific ate ial system and restore and system ial - 2009 CEU eTD Collection co the for advantages wella is listing cross the of cap world among integration extensive with together going and 1980s mid the from starting one, 1997valueretreated ofdecline 4,700,a to2,300from 50% its ofover (Karolyi 2006). market financial a things the statistics, world’s the at cross of t USA in companies listed a was there time, same the At trillion. $3.5 total and Product U.S of 1% than less represented countries other and residents U.S. between 1980 in largely: increasing are volumes exchanges 2.1. be presented and evaluated. liter available developingend the In and (MICEX). (LSE) market developed both have we analysis our in because countries t content: Current financial globalization offers plenty of alternatives in financial m financial in alternatives of plenty offers globalization financial Current ital markets, and the second the and markets, ital C The choice of cross listing as a method of me methodof as a listing cross The choice of Historically, there Historically, ross

process of cross listings and even rapid delisting took place took delisting rapid even and listings cross of process , according t - listed firms jumped from 158 in 1990 to more than 2,000 in 2006. However, looking However, 2006. in 2,000 than more to 1990 in 158 from jumped firms listed he chapter is divided into two parts: literature about developed and developing developing and developed about literature parts: two into divided is chapter he - listing in developed in listing economies for

both investors and investors both : in of the end of 2002, the number of internationally cross internationally of number the 2002, of end the of in : o the U.S.Treasury o the - mpany being cross being mpany studied issue in the literature, mostly analyzed from the viewpoint of theof viewpoint literature,the mostlyfromin theanalyzed studiedissue Chapter 2. are two main wa main two are hrough issuing American Depositary Receipts (ADRs) Receipts Depositary American issuing hrough

c Literature review on crossLiterature on listing review ve ompanies who are listed on exchanges. Over time traded time Over exchanges. on listed are who ompanies ature concerning cross listing of Russian companies will will companies Russian of listing cross concerning ature e o a otmsi a te se t be to seem they as optimistic as not re -

(2006) - late 990s, which was characterized by slowing down down slowing by characterized was which 990s, late listed together with more speci more with together listed ves of cross listing cross of ves

h ttl cross total the 21 , while in2006 , while

asuring the liquidity explains this cha this explains liquidityasuring the large increase in the number of cross cross of number the in increase large - odr portfolio border development , they already already

(You, 2008 (You,

fic studies concerning studies fic worldwide: the first the worldwide: consist about 30% consist about30% - . Gross Domestic Gross . listed stocks had stocks listed ﬂ arkets and stock stock and arkets ows of capital capital of ows

o American for ) : the number the : . Generally, .

pter’s pter’s CEU eTD Collection cross being for driver argument) this in Stulz support were who firms those isrepreturn abnormalan such risk exposures. Moreover, capital by market caused report they that the after reaction market on based support that studies (1981) Stulz example, For hypothesis. this against critics reasonable with up came who economists acro risks spreading thus, and, barriers investment removing to due capital of cost its reduce to firm the for opportunity the on concentrates which hypothesis, segmentation market with connected is corporate issues (Doidge place: takes companies, inside relations l in Alternatively, liquidit advantages problems, and other factors, risk increased as such listing to mostly referring benefits, listing’s cross studied there literature recent the in However, markets. both on prices the of convergence and shift volume trade discounts, or premium companies’ One of the most popular bene popular most the of One early explain researches Earlier

y, and global market prestige (Errunza and Losq (1985) Losq and (Errunza prestige market global and y, name s h po o a o o invest of lot a of pool the ss

as market segmentation, increased capital market flows, tax benefits, increased increased benefits, tax flows, market capital increased segmentation, market as d

several difficulties that difficulties several

Mle, 99 i eteey o comparing low extremely is 1999) (Miller, tr tde dif studies ater

market segmmarket risk - listed for a firm is firm a for listed

led itgae i te ol mre (okd n Sizr (2000) Switzer and (Doukad market world the in integrated already

factors conn (2004) , Stulz’ .

entation hypothesis areconcentratedhypothesis entation Doidge et al.Doidge (2004) et eet atr, oncig ih h itra srcue and structure internal the with connecting factors, ferent y w y fits of cross of fits ectedwith global trading of ent of cross listing, and the abnormal return abnormal the and listing, cross of ent corporate governance corporate

go against go

waves of cross cross of waves the ne ors (Karolyi, 1998; Ji, Ji, 1998; (Karolyi, ors

investor protection, agency problems, and other other and problems, agency protection, investor t rtcs aie fo te at ht f h main the if that fact the from arises criticism xt lower cost of capital due to removing investment removing to due capital of cost lower 22 -

listing

s oe is oad h asne f well of absence the toward bias some is the theory. The first one is that a that is one first The theory. the the ,

La Portaet al. among economists developed in 1990s in developed economists among problems raised as a result of cross cross of result a as raised problems itns s drc rsls f such of results direct a as listings

problem

to large changes in the cost of of cost the in changes large to ,

Foerster and Karolyi and Foerster shares. 2005)

, information asymmetry information , (1998 around event around Hwvr tee are there However, .

resented for resented for

- of study tests tests study lmost all lmost

1 to 2% to 1 (1993 ). -

CEU eTD Collection investors domestic companies the in invest to wish certainly ( trading insider from protected export small, for cross significant find authors idea, the support results aggregate Despite 2004). (Halling, listing cro after jump the after later trading of agglomeration the by demonstrated being market, foreign a on activity trading active necessarily not is listing cross for goal main companies’ T trend. declining by followed later but made was listing cross after just activity trading in jump immediate after c so to Accordingcompany. listed see listings associated withcapital hypothesis segmentation cross cross the ther and of diminishing, be should number advantages marginal the growing companies the with years: ten past the over growing is which time the explain to unable is hypothesis the Stulz, to according ev for that demonstrates (2004) cros consider that firms all not that country of cost the cross to due capital of cost the whom for firm each then barriers, ing - - her analysis of analysis her aial, o eiy l te reasons the all verify to Basically, listing. The final argument final The listing. sectional variation in the extent and persistence and extent the in variation sectional

if there is there if on itrainly ol d s. oee, n cn bev i ams each almost in observe can one However, so. do would internationally going - a really a oriented and high and oriented hus, one can observe the presence of agglomeration effect, meaning that that meaning effect, agglomeration of presence the observe can one hus, ) Sc a aggre an Such .

Daimler Chrysler AG cross listing pattern, there is a common case of of case common a is there pattern, listing cross AG Chrysler Daimler to large and persistent trading activity on a foreign market for a cross cross a for market foreign a on activity trading persistent and large explain the smaller decline in post in decline smaller the explain - rising a rising ery one firm cross firm one ery

ic i cris diinl ik fr oeg ivsos the investors, foreign for risks additional carries it since against the common hypothesis is hypothesis common the against alled “flow alled - tech companies, as well as companies, tech ctivity and (Foerster 1999). Karolyi, ain s xlie b pstv etraiis when externalities positive by explained is gation

that n advantages and s - - 23 back” phenomenon proposed by Karoliy (2003) (2003) Karoliy by proposed phenomenon back” listing “profitable” listing they feel contain less disadvantage relative to relative disadvantage less contain feel they

- listed ten fi ten listed

of this agglomeration effect agglomeration this of

behind as rms remain at home. Mor home. at remain rms - listing share listing - for for series pattern of the listings, listings, the of pattern series - do so: for example, Doidge example, for so: do listing would fall more than than more fall would listing

rs lsig, t s worth is it listings, cross

companies that are better are that companies if the inability of market market of inability the if e should be reduction in reduction be should e

- price fraction for for fraction price : it

is higher is - listing eover, ss ss y

CEU eTD Collection ( disclosure corporate improves cross that claim researchers about some literature: conclusion the in precise this no supporting is there However, country. home their in institutions weak cross became markets emerging in firms that possibility a is there protection, investor low with together stability, political and macro with markets. cross be to tend markets emerging from companies why explanations exchanges stock underdeveloped factors points. severalimportant distinguish to 2.2. makemarket theirthelargest inthe numberof orders with non non and discretionary into traders separate (1991) Nanda and Chowdry pattern: trade of suppor aggregation to likely is above discussed information asymmetric of concept the addition, In microstructures. different having only coexist can markets two that claims (1994) Glosten betwe occurs possible: costs, trading similar the with markets distinct two of presence to reduce adverse orderflow effecttrading one’s 1989).(Pagano, price onstock’s help investors of number larger simultaneously: markets two on traded are stocks company’s C

ross osqety te aggregation the Consequently,

Shifting -

such as financial fragility, instability of domestic currency, and usually usually and currency, domestic of instability fragility, financial as such discretionary, saying that all traders with discretion over their trades’ location will will location trades’ their over discretion with traders all that saying discretionary, The most intuitive one is that since emerging economies frequently have the problem emerging problem intuitive most economiesfrequently onethe have The isthatsince all investors’ trade concentrates on one market or some “knife some or market one on concentrates trade investors’ all - listing in emerging in listing economies en these markets and due to that they become become they that to due and markets these en

the issue of cross of issue the Doidge, - listing

Sinv, 2004) (Smirnova,

f rdn atvte i cue b te at ht n the in that fact the by caused is activities trading of First of all, emerging markets have in common severalcommon in have emergingmarketsall, of First

et al et from developed from

(2005 24 -

itd eas te wud lik would they because listed ) , while others suggest that cross listing is is listing cross that suggest others while , . n h ltrtr, hr ae several are there literature, the In to emerging markets, it is important is it markets, emerging to fully - discretionary traders. either of the of either indifferent from each other. other. each from indifferent - itn o U obviously US on listing - - itd n developed on listed edged” equilibrium edged”

equilibrium t overcome to e

t the the t s is s CEU eTD Collection (Mexican 1990s the in crises currency of times the at listed cross were that markets emerging in firms Chandar, to according times: crisis’ the at advantage significant a be can this that observe the level ofconditional volatility stock. ofthe cross after value beta in change significant statistically no find authors i unchanged: cross by affected necessarily (2010) Umutlu to according addition, In t between competition market, ADR and home between linkages information sufficient of condition the under listed: cross when faces country and firm each that competition intermarket and another to market one from effects liquidity that reported who (1998) al. et investors’ to contribution Domowitz with together comes research Their firms. small less for than firms large for protection gives market ADR asymmetry, information reduce that informati more is there since that found they specifically, More size. and origin of country firm’s the among varies greatly effect liquidity that concluded markets American Latin main four from ADRs and stocks studying after (2008) Chavez and ex For case. the always not is this that evidences research are there reasonable, rather be to seems argument this Despite stocks. their of liquidity the increasing by justified low liquidityfor significantlyhome institutions for matter NYSE that evidence the finding institutions, country home of replacement effective necessarily not Furthermore, since emerging economies’ exchanges have several limitations, risks, and risks, limitations, several have exchanges economies’ emerging since Furthermore, ept tee one facts counter these Despite crisis in 1994, the East Asian crisis in 1997 and the Russian default in 1998) 1998) in default Russian the and 1997 in crisis Asian East the 1994, in crisis n their time their n investors, then the wish of firms domestically located in these markets can be domestically be marketscan firms inthese thenthe located wishof investors, - series conditional heteroscedasticity model of 14 emerging markets, emerging 14 of model heteroscedasticity conditional series - listing, but also risk characteristics of underlying shares stay stay shares underlying of characteristics risk also but listing,

gis ovos oiie fet o cross of effects positive obvious against he markets enhances liquidity of cross listed companies. listed cross of liquidity enhances markets he

not only liquidity of emerging market’s firm is not is firm market’s emerging of liquidity only not 25

listed non listed heavily depend on the order flow migration migration flow order the on depend heavily - US stocks( on exists for large companies companies large for exists on Eleswarapu - listing together with together listing - itn, n can one listing, ample, Silva ample, , 1997 ) .

CEU eTD Collection their basing (2003), Chung and Brockman example, For role. crucial plays economists, the supporting evidence The protection. investor low their with connected 2007) whe years 5 after only rather but immediately, materialize not does listed cross being from gains more, is What 2002. in Act Securitie co of reasons main the of one that surprise of (cost listed cross the of implementation be to required costs cover always not do listing cross from benefits valuation Particularly, case the always not is there incrosspoints listing when are several analyzing emerging diverse markets. t byoutweighedare expenses these but cross Tobin’s of methodology the using time, same more even emergi for are crucial previously mentioned were that arguments same the growth; companies’ markets emerging compared thatwere (2009). firms withother notcross listed crisis the of consequences the during especially effects, negative less significantly suffered ee of level - . However reason the Generally, The next factor for describing special features of cross listing in emerging markets is markets emerging in listing cross of features special describing for factor next The listing for emerging markets is higher than for the countries from developed countries developed from countries the for than higher is markets emerging for listing

s and Exchange Commission Commission Exchange and s

effect

Hope et al. et Hope investor , there are several economists who claim that the issue of cross of issue the that claim who economists several are there , wie im fo high from firms while , : in order to find a solution for their home constraints and to enhance their their enhance to and constraints home their for solution a find to order in : ng markets because of their financial markets’ underdevelopments. At the the At underdevelopments. markets’ financial their of because markets ng s GAAP accounting standards, for example). Consequently, there is little is there Consequently, example). for standards, accounting GAAP

’ n cos itd opne nt las e te xetd advantages expected the get always not companies listed cross and

(2007) says that the firms from low from firms the that says (2007) rtcin n fnnil akt eeomn, oe b several by posed development, market financial and protection

h frs eie o e rs lse i esl explained easily is listed cross be to decide firms why n a firm from em from firm a n he premium caused by cross listing. listing. cross bycaused premium he compliance that was expanded after Sarbanes after expanded was that compliance - icoue ytm rec system disclosure 26 mpanies’ delisting in the US is high costs of of costs high is US the in delisting mpanies’ q

, Doidge et al. et Doidge erging markets is traded in traded is markets erging

- disclosure regime receive lower lower receive regime disclosure (2004) showed that showed (2004) ie ihr auto. Thus, valuation. higher eive a strong link between between link strong a In addition to that, to Inaddition - lis US ted premium ted

A the cost of of cost the

(Connor, -

Oxley Oxley

for . , CEU eTD Collection (2002) Medvedev and Kolodyazhny is studies them few of are One there it. market, analyzing security Russian the of importance strategic and size the relevant are economies market emerging others, of features as and above mentioned protection investor low fragility, system financial liquidity, low of problems ofRussian listing 2.3. Cross order todecrease outeffects crowding in information private in investments encourage to standards disclosure create instead, but, market, the from information private out crowd can that transparency information accounting deepe to intend that policies that meaning for implication policy matter economic markets’ emerging important an be can which coverage, analysts’ additional of conditions under negat find also firm is that information the collecting from investors divert may information public extensive more and coverage analyst cau disclosure informational and scrutiny firms’ Mexican analyzing research, (2008) Ferriera and Fernandes As markets. emerging for important particularly is this and effect, adverse Hvidkjaer, researches other with consistent ju and stability, political standards, accounting for ratings higher with countries for lower be to appear costs trading markets: equity in liquidity of cost (2006 Moreover, asymmetry. information by posed costs liquidity in strong China on research ) extended this theory by claiming that macro institutions also significantly affect the the affect significantly also institutions macro that claiming by theory this extended ) Since Russia is considered as as considered is Russia Since etr rtcin rgltos market (regulations, protection vestor

’aa 20) Bt fo te te side other the from But, (2002). O’Hara ive relation ive - based firms cross firms based ship - specific and also reduce trading of informed traders. informed of trading reduce also and specific

stocks

between firm between who analyzed who an - listed on Hong Kong exchange market, concluded that that concluded market, exchange Kong Hong on listed .

emerging (or developing) country (IMF, 2012), all the the all 2012), (IMF, country developing) (or emerging sed by cross by sed - 27 specific and cross and specific

the problem ( problem the

- supportive laws, enforcement) reduces the the reduces enforcement) laws, supportive - listing can have different effects. More More effects. different have can listing , information disclosure can have have can disclosure information , rs lsig concluded, listing, cross iil fiiny Ti cnet is concept This efficiency. dicial Eleswarapu (1997) Eleswarapu lsaau n Venkatara and Eleswarapu - listing stock return variation variation return stock listing ,

who who

for Russia. Despite Russia. for are out carried , and Easley, and , The a The

additional additional uthors uthors

their man an an n CEU eTD Collection opn t mk cnlsos bu cos itn. hs oe hud e aeu t use to careful be should one Thus, listing. cross about conclusions make to company traded actively it because Gazprom, 2003, and 1994 betweenperiod time for U.S. the in stocks listed cross Russian 2006). (Jithendranathan, traded are ADRs where ones foreign Ru between volume trading of distribution even overall with together Russia in stock underlying and America in ADRs Russian between difference significant st markets the for effect listing cross beneficial of cross hypothesis the the after contradicts returns of variance in increase and day listing the on loca was model her in used of sample li ADR of impact period of time. same the during price the for adjusts volume trading versa, vice and, week one during volume p bi and is them, there between that causality concluded directional and Exchange Stock Russian on volume and price between time. over efficiencyRussia marketthe in in improvement GA using (2002) Urga and Hall performance, stock on structure ownership of impact the studied (2001) Muravyov and Kuznecov associated. risks lower with benchmarks to compared than returns higher earning allows that making market microstructur market exchange stock Russian concerning research l returns around the listing date listing the aroundreturns l ee suis r dvtd o cross to devoted are studies Fewer n mr study more One

16 Russian

R ara wt te ags cptlzto, e hud con fr this for account should we capitalization, largest the with abroad DRs sting for Russian stocks was examined by Smirnova (2004). She collected She (2004). Smirnova by examined was stocks Russian for sting

issued its stocks in Russia only Russia in stocks its issued

cross listed cross OLS of instead GARCH bu Rsin ADRs Russian about

firms that issued ADRs issued that firms . She found the significant negative abnormal stock returns returns stock significant negativeabnormal the found She . - itn o te opne lctd n usa the Russia: in located companies the of listing rice changes of stock adjust to lagged trading trading lagged to adjust stock of changes rice 28 , and the model accounted only for changes in changes for only accounted model the and , from

in 2006. Since Gaprom n Gaprom Since 2006. in 1995 RSH testing concluded that there is an an is there that concluded testing RSH

during 1996 and 2001 and 1996 during Tov to

(2007) studied the relationship studiedthe (2007) 2004 found that there is no no is there that found 2004 In this study the author used used author the study this In e and found the presence of of presence the found and e ock from emerging emerging from ock - ssian exchange and and exchange ssian itn date listing ow is the most most the is ow thus excluding thus . The method The , which which , a - CEU eTD Collection and more r fir the in explained were that exchange stock Russian current for basis a as paper Jithendranathan’s ecent be should period analyzed. data 29 policy implications because current changes on on changes current because implications policy

s t

chapter, should be taken into account into taken be should chapter, CEU eTD Collection patt this of source a be could that explanations several propose they patterns, comovement the intensively. most trades it locat the Generally, where markets the like more move pair” “twin in stocks two the of one that shows model the Moreover, horizons. long and short both for indexes market ratesguilder dollar, pound, and between of given thepairs as variables. exchange in change the and Indices, Dutch and FTSE S&P, of returns variable, dependent a th of returns log the between difference the contained model The Netherlands. and UK, US, the in exchanges different on traded being Unilever, and Shell, Dutch, Royal analyzed: were companies Three traded. are they where markets beca together move should countries different in traded company strongly are companies multinational liquid influenced most and largest three the of prices stock 3.1. dynamics The the chapter ends liquidity. results. policy of with ofthe implications currency and research the of purpose paper Debora’s and Froot on based is model This exchange. r A  eerhr fud ht there that found Researchers B authors admit that none can explain a meaningful fraction of the price differentials or or differentials price the of fraction meaningful a explain can none that admit authors , The baseline model t The model is based on Froot and Dabora’s research andDabora’s (1998) thatdone The t onFroot was based model is  our presents chapter This   y oainl atr. h a The factors. locational by i   1  1 exchange. We extend the model by adding VIX index and looking at the the at looking and index VIX adding by model the extend We exchange.  i * S ion of trade matters for pricing according to the authors’ model. Despite model. authors’ the to according pricing for matters trade of ion &

because it controls for such local effects as domestic as effects local such for controls it because t  i   j  1  1

 is an evidence of comovement between relative prices and and prices relative between comovement of evidence an is

model j Chapter * FTSE which , tos iiil hypot initial uthors’ t  3. j 30  The model The k

  measure 1  1  k e same company in different markets as markets different in company same e * DI s

t  h lqiiy of liquidity the k

 (1998) ei ws ht h sok o a of stocks the that was hesis l   1  1  use of integrated financial integrated of use l

gl which is relevant is which /

$ t  1 the  m market   1 usa stock Russian o testwhether o  1  m

indexes

/ for the the for GBP ern. ern. t  m

  t CEU eTD Collection effects extended independent have both variables VIX and rate Exchange that and Index, VIX including by model the extend we Also, GDRs. issuing through LSE price minor only explain differential. can factors these dividends, current the for only and dates the between window time the in only matters it Since stocks. both to relative payments dividend paymentfluctuadays, and betweenannouncement period time the during rate, current spot the at pounds guildersor into areconverted dividends since currencies:and dividends is authors offeredthe by explanation last The control. ofvalue economy of case in only issue the explain can premium control also and m was Shell when periods the explain cannot shar Shell hurt to power this use really could it thus power, voting as well as flows cash in share 60% has who Dutch Royal of premium” “control a be to seems there disparities: price for t explain to small too are they explanation, previous the in as However, deviate. also would shareholders of receipts net in because expenditures t ratio: the concerning explanation similar a is There differential. price of volatility the explain cannot which magnitude, insignificant div the off paying of ratio the Moreover, countr two the in asymmetry this offset to intervening even policy, split income net 60:40 its maintains actively company the company: the inside flows cash Dutch/Shell), (Royal pair twin largest the Taking eholders’ interests. However, this reason also falls short of the full explanation because it because explanation full the of short falls also reason this However, interests. eholders’ Our model is dif is model Our versionmodel as ofabase the

ferent in several aspects: we use Russian stocks that are cross listed on listed cross are that stocks Russian use we aspects: several in ferent the he findings. Differences in corporate control is another explanation explanation another is control corporate in Differences findings. he case when the expenditure deviate expenditure the when case .

dns eitd rm hs ratio this from deviated idends he difference between the parent companies’ companies’ parent the between difference he 31 ore expensive in comparison to comparison in expensive ore

tions in exchange rates change the values of values exchangeinthe changerates tions the researchers analyze the splitting of the the of splitting the analyze researchers s

much from 60:40 ratio, then ratio, 60:40 from much ies’ corporate ies’ - wide tu, e s the use we thus, ; bt ny o an for only but ,

changes in the in changes Royal Dutch, Dutch, Royal - tax regimes. tax we find we

CEU eTD Collection 6 2012 and ending onMarch 30, average 9 GBP with Severstal capitalization, 98 GBP of capitalization market its with Gazprom big presence companies exchange were index exchange last taken were returns of logarithms from taken also was rate exchange Rule 144A of because currency American website Russia of Bank Central from taken rates exchange to converted were prices LSE LSE stocksRussian to supp is that Exchange Stock London in traded and therelated industry stock Russian underlying code, ISIN date, issuing the about information the with together 3.2.

http://www.adrbnymellon.com/dr_directory.jsp h ls o al h Rsin R ws ae fo te ak f e York New of Bank the from taken was DRs Russian the all of list The

akt capi market Data eid ad hs d these and period, h diy lsn pie wr otie fo LE n MICEX and LSE from obtained were prices closing daily The about 135 about

on both markets during2006and 2012. on bothmarkets

were chosen for the the for chosen were rm finance.yahoo from , 1m aiaiain dt a o Fbur 2012 February of as (data capitalization 018m t lzto ad h ohr two other the and alization 0 daily observations daily 0

discussed above. ae fo MCX est ( website MICEX from taken 6 . Based on IS. Based on – t were ata

with GBP 9 GBP with

( Table 5

after stimation ( usa rbe i a in rubles Russian

TE ne) epesd n hi ntv currencies. native their in expressed Index), FTSE sd n h regression. the in used IN code provided, weIN code found provided,

dividing the price in the next the in price the dividing , for each co each for )

741m, and Novolipetsk Iron and Steel Corporation Steel and Iron Novolipetsk and 741m, the the .

based on the criteria of m of criteria the on based eta Bn o Rsi ofca website official Russia of Bank Central regulation 32 orted by the problem of “issuers’ of problem the by orted -

with Thus mpany , 456

MICEX Index) and and Index) MICEX , we relatively a ws icse above) discussed was as , crac wt te al RUR/USD daily the with ccordance . 01

starting from the beginning the from starting

m, Lukoil m, took Daily

LSE , GR ae rdd n S in LSE on traded are (GDRs

two ml market small that the majority of DRs arethat themajority of

companies withrelativelycompanies values values period by the price in the the in price the by period . h dt includes data The ). – arket

with GBP 66 GBP with official official ne fr London for Index capitalization and and capitalization o

f fiil website official

Russian Russian

capitalization we migration” ; sts and bsites, RUR , 263

of T . /GBP /GBP stock . 2006 2006 F 13m our our

o he he of n – : ,

CEU eTD Collection company’sLSE depositaryreceipts on billion $43.6 versus billion $20.9 Gazprom: gas. Gazprom after year a 1997, in LSE on trade to started It 13.87%. is company the of structure equity in share government Russian vertically company’sLSE depositaryreceipts on billion $61.9 MICEX: later much MICEX the that notable Management Property 38.373 State for Agency Federal the through indirectly, and 50.002% government Russian The of are

gas, gascondensate gas,

based in based Gazprom’ Gazprom is one of the largest energy com energy largest the of one is Gazprom uol s h ohr opn related company other the is Lukoil %. - integrated oil and gas comp gas and oil integrated urnl, Gaz Currently,

geological exploration, exploration, geological tae oue n S i as mr ta o MCX a ws h cs with case the was as MICEX, on than more also is LSE on volume trade s

listing date of the company on company the of date listing –

and oil, as oil, and versus $85.8 billion. billion. $85.8 versus aur, 2006. January, rm s itd nRsin Lno, n Fakut exchanges. Frankfurt and London, Russian, on listed is prom owns the control the owns

wel .

Lukoil relates to the same industry as Gazprom as industry same the to relates Lukoil production l as l any, accounting for 2.2% of global output of crude oil. oil. crude of output global of 2.2% for accounting any,

(Lukoil Annual report(Lukoil Annual 2011) Annual(Gazprom report, 2011)

apo’ tae oue n S i mr ta on than more is LSE on volume trade Gazprom’s

generation and marketing of marketingand generation

share in the structure of equity capital equity of structure the in share .

In the model we use we model the In o lret aiaiain group capitalization” “largest to 33 In the model we use DR 144A standard GDRs standard 144A DR use we model the In

LSE was October 29, 1996 while in Russian in while 1996 29, October was LSE panies in Russia and Russia in panies transportation , storage, ,

. DR 144A 144A DR

heat and electric power. electricpower. and heat its major business lines business major its

processing standard GDRs standard international ,

– and sales and -

directly directly

oil and oil t is It –

CEU eTD Collection Londonare in all the for higher whyisThat Russia. in London than in more lose or more likelyearn to is Russia. in traded stocks underlying for higher is deviation standard the thus, t companies, risk more contain they because expected is it as companies small for higher is standard GDRsdepositaryLSE company’s receipts on $ LSEis on exchanges: MICEX on 2006, shareholders. its among government have not does Brazil. and Liberia Italy, Poland, Latvia, Ukraine, in USA, the and Russia 2011) LSE on receipts company’sdepositary $3 is MICEX on 2005, December in LSE on trade have not does company the Notably, inc products steel flat NLMK Severstal. in exchanges both on traded , 214 . Severstal is a vertically integrated steel and steel related mining company, with company, mining related steel and steel verticallyintegrated a is Severstal are pair other The Looking at the descriptive statistics statistics descriptive the at Looking

million, and on MICEX on and million, is –

amplitude an integrated steel integrated an luding slabs, coated and electrical steel electrical and coated slabs, luding n ue 05 Svrtls rd vlm i ams th almost is volume trade Severstal’s 2005. June in 6

, the compa the 373

million, and on MICEXon and million, 2006 s of their returns their of s companiesGazprom beside -

nies with the lowest capitalization lowest the with nies It means that means It Ds ht r t are that ADRs $567,585. –

Novolipetsk Iron and Steel Corporation (NLMK) and and (NLMK) Corporation Steel and Iron Novolipetsk (Novolipetsk Steel and Iron Corporation Annual report report AnnualIron Corporation and Steel (Novolipetsk the - making company, which produces produces which company, making of the data (Table 6 (Table data the of oenet mn is shareholders. its among government – 34

In the model we use DR 144A standard GDRs GDRs standard 144A DR use we model the In

in April 2006. NLMK’s trade volume on LSE on volume trade NLMK’s 2006. April in

should be broader. be should

holding ADRs is more risky, but an investor an but risky, more is ADRs holding

It started to trade on LSE in November November in LSE on trade to started It - ae on raded

(Severstal Annual2011). report

$ 6 , 689

for analyzed theperiod ), we see t see we ),

. In the model we use DR 144ADR use we In model the . as well as long steel products. products. steel long as well as odn xhne hn for than exchange London Notable to mention is that is mention to Notable

cross hat standard deviation deviation standard hat the the - a listed companies listed means sm o two on same e ie NLMK, Like large variety of of variety large

t tre to started It .

of returnsof a large han

assets in assets

CEU eTD Collection values the with automaticall to corresponding is jump this behind we LSE, on decrease between and 2012). 2006 share (the Index f index index the index’ the For correlate with anything changes currency log relevant LSE significant r A 

B and Russian and Lond and Russian and , So, Since t

returns r h regression the or  selected large selected

 with significant weights significant with o esr te iudt o Rsin market Russian of liquidity the measure to

for these stocks these for

 Gazprom cnetd usat to pursuant converted y i  , the results would results the ,  1 

1 of zero before the jump ( jump the before zero of



one ADR one f opne i te Index the in companies of i * the MICEX

- tried to include include to tried had capitalized capitalized :

we : official

a , we , , which , on market index log returns plus returns log index market on price difference j difference price t

 e ot 4 fr apo ad 16 and Gazprom for 14% out net i

Or nta hptei i ta pie ifrnil sol not should differentials price that is hypothesis initial Our . regress cross regress  announcement of announcement

 companies it is i is it companies j be biased because these companies are already included in included already are companies these because biased be . That is why we why is That . 

1 was decreased from ten to ten from decreased was  1 

h announced the a j * dummy variable controlling for for controlling variable dummy from February 8, 2006 to April 26, 2011) and 2011) 26, April to 2006 8, February from FTSE -

listed stocks’ retur stocks’ listed 35 ump on April 26, 2006 caused 2006 26, April on ump i nt hne infcnl drn te period the during significantly change not did t 

j  mportant to note that note to mportant

the number the net out the company’ the out net k 

 1  ratio. 1 

k and *

RUR We

four; ADR, floa ADR, four; to VIX log changes and plus and changes log VIX

of n differential n introduce / fr Lukoil for % e i th if see

GBP Gazprom’s ordinary shares shares ordinary Gazprom’s t 

k if to if t his jump. his s share s 

e dmy variable dummy a l 



s o s  take just just take oa effects local by 1 ted earlier were earlier ted 

n MICEX and MICEX n l

rm MICEX from to get t get to a *

VIX sharp The reason The Russian Russian t  values he net he 1 pric 

 the are t e

CEU eTD Collection Londongain suchgetting moreand in a domestic returns investorscase in than investors ratio words, other (in 0.1638% smaller becomes appreciates currency ( coefficients negative and increases London in return the because decreases returns London rati the rises, Index London when explained: logically Index FTSE for interval twi traded are Gazprom shows trade andcomovement returns volume,index the ofthis are larger larger has company a where companies: large for model our in supported are results Debora’s and Lukoil at significant signific time s statistically the 3.3. variable is of ( jump the after one baseline model. model. baseline Results vice t First of all, we all, of First

, and the index is more significant than the other. other. the than significant more is index the and , for Gazprom for ant

versa

not - when when

0.06678 ignificant coefficients ignificant

lead time time lead sta .

), xhne ae s s is rate Exchange tisticallys h mdl s ihu la ad la and lead without is model the then the the then

The re The

(Appendix 1, Tables A1.2, and A1.5) and A1.2, Tables 1, (Appendix

for Gazprom. for pay attention to the results of the model the of results the to attention pay y % against 1% by pedx 1 Appendix at 5% confidence level level confidence 5% at rm pi 2, 01 o ac 3, 201 30, March to 2011 27, April from ce as much as ce

with sults for the the for sults ignificant relative price of Lukoil in Russia over London increases by about by increases London over Russia in Lukoil of price relative

h ngtv co negative the of returns MICEX/LSE will become larger by this amount) this by larger become will MICEX/LSE returns of Tables , According to these results, we can conclude that conclude can we results, these to According

f in London than in Russia and they have have they and Russia in than London in or aitcly infcn a 10 at significant tatistically , so,we the

FTSE largely capitalized largely on (n te wrs when words, other (in pound

11 n A1. and A1.1

do not include it do not 36 Index with Index with the negative coefficient negative the with

fiins agr hn MICEX than larger efficients seiiain, hl i i becomin is it while specifications, g - o of Russian stock’s returns over over returns stock’s Russian of o 0.32464 4

. . hs means This ). companies show the negative the show companies

The other index, MICEX index, other The

For example, both Lukoil and and Lukoil both example, For without VIX coefficient, like in like coefficient, VIX without (see Appendix 1 (see Appendix 2). % confidence interval interval confidence %

as the as the

for Lukoil and Lukoil for , making the ratio the making , W e

a that saw respective h rto RUR/GBP ratio the

ht f h Russian the if that s 99

, Table A1.3 of This . % confidence confidence %

- hs dummy this 0.06939 for 0.06939 - coefficient coefficient 0.22837

Froot and and Froot

smaller , is , can be be can .

with with and and

not not )

g ,

CEU eTD Collection returns stocks these that indicate exch of importance relative e a more being large for either market the on traded more is stock considering findings exchange. Moscow of London.in andRussia in both shocksmarket local hypothesis baseline modelshows a demonstrating London, in than more there traded being Russia, positiv a has NLMK while London, for coefficient higher times three has markets, both in equally traded being Severstal, model: baseline the support not do companies and NLMK companies both for is coefficient 0.31357 respectively is results. different xchange r xchange

significant at time time at significant eeal, t a b conc be can it Generally, small for results the Analyzing become larger in Russia. Russia. become largerin

o Severstal for ate is more significant for small companies with negative coefficient. coefficient. negative with companies small for significant more is ate -

(Appendix 1, Tables A1.7, and A1.9) and A1.7, Tables 1, (Appendix “local effect “local - tvl tae o LE hy have they LSE on traded ctively more 0.461018 For these companies, both indexes’ coefficients are coefficients indexes’ both companies, Forthese statistically s statistically ee we w ue h mdl ihu las n lags and leads without model the use we when even ,

. agr ooeet ewe rtrs ifrne n mre idx f a if index market and difference returns between comovement larger t

and and with

U s Severstal for ig h poy mode proxy the sing ”

olw usa crec mvmns we i appreciates, it when movements: currency Russian follow have an impa an have

- the coefficients the ne rate ange 0.2704 ue ta w find we that luded

ignificant 2

- o NLMK for

capitalized compani capitalized negative Apni 1 Tbe A. ad A1.8 and A1.6 Tables 1, (Appendix ct on returns on ct

than for large companies large for than - 37 0.099 o Fot n Dbr, e can we Debora, and Froot of l

stronger ofiin for coefficient Also, . . Coeffic .

This is an evidence of insufficient liquidityinsufficientevidenceanof is This 09

- capitalized stocks: Lukoil and Gazprom, and Lukoil stocks: capitalized evidence : price return differential differential return price :

and 0.10899 and

for small companies companies small for ofiins hn IE has. MICEX than coefficients es, NLMK and Severstal, we find we Severstal, and NLMK es, ients f ients ht o o spot u initial our support not do that

small or London FTSE Index are Index FTSE London or

for Severstal for

reverse also and with negative with and - aiaie stocks capitalized

significant: MICEX MICEX significant:

e coefficient for for coefficient e pattern : ) depends on the on depends . exchange rate rate exchange -

0.1 upr their support

Thus, small small Thus, and NLMK and The l The 96381

than the the than

signs signs arger their

The The can for for -

CEU eTD Collection 7 significant stocks large and small both for variable VIX and variable rate c lower are MICEX with correlated negatively be averse. risk more becoming prices, future if because index” “fear called is index options S&P500 of range volatility. of measure stocks, companies. less stocks large of difference 7) high

orrelation between and VIX MICEX is -

. In . Investopedia, 2011 Investopedia,

for all for To include the stationary effect in the model we added VIX index index VIX added we model the in effect stationary the include To 3.3 As a As One more important finding in the results is results the in finding important more One other words, the words, other allowing frictions more oflarge for stocks . 1. , at 99% confidence confidence 99% at ,

resul u to due

the Thus, there is more randomne more is there Thus, Extension to the Extension model companies t of including VIX including of t

the

This index is constructed on the basis of the implied v implied the of basis the on constructed is index This movements of the the of movements o atvt o i of activity low

, and frequently used as a measure of a market risk market a of measure a as used frequently and

for large stocks large for

interval, neither at lead or lag time specifications, but at at but specifications, time lag or lead at neither interval,

hn oeet bten cross between movements than

in the model the in and FTSE and the - 0.30 vsos wh nvestors That is wh is That ss in the price returns of large stocks than of s of than stocks large of returns price the in ss model the of variables index is high is index it is surprisingly lower than lower surprisingly is it 22 38 67, and between VIX FTSE67, is and

, we we , .

index the analysis of analysis the

y it is expected that VIX changes should changes VIX that expected is it y see the independent effects of exchange exchange of effects independent the see n h VX s ihr I te model, the In higher. is VIX the en es then investors feel uncertainty about uncertainty feel investors then

because daily changes of the index index the of changes daily because .

or small stocks VIX is more is VIX stocks small or explain movements of price of movements explain R 2 : -

listed stocks of small small of stocks listed although

for small ones small for daily 7 . wide of olatility

Sometimes the Sometimes its value is value its changes as a as changes

- 0.490117.

(Table mall

not not t ,

CEU eTD Collection all four companies Brot Lehman of in over liquid more or less becomes exchange is thenegative autocor first order lags and leads in signs their change variables returns bring. stocks Russia in sha down or up either go will market the that future the in expect investors risk Gazprom. andLukoil stoc A2.4 and A2.3 Tables internal confidence 10% at only significant is it companies large for while to

ks: two subsamples, two I 3.3 FTSE and MICEX that observe can we one, main a as model modified this Using t was interesting to observe the dynamics of the observations the of dynamics the observe to interesting was t 0.062111 and 0.055414 for Severstal and NLMK versus 0.007036 and 0.021790 for 0.021790 and 0.007036 versus NLMK and Severstal for 0.055414 and 0.062111 . 2.

Dynamics hers, the official day when when day official the hers,

arerepresented (see Appendix the )

Judging by the positive VIX coefficient VIX positive the Judgingby .

Also, small stocks have largerhave stocks small Also, threshold of which was September 15, 2008 15, September was which of threshold

relation in dependent in variablerelation the the

time.

time specifications time 39 financial

3 In order to do that, the sample was divided was sample the that, do to order In ).

positive positive crisis began. crisis

for all the companies the all for (Appendix 3,Table(Appendix A3.1.) coefficients for VIX than large than VIXfor coefficients . The probable reason for that for reason probable The

Below to see if see to –

the day of bankruptcy bankruptcy of day the

( the outcomes for for outcomes the see Appendix 2 Appendix see Moscow stock Moscow rply , the more more the , , the ,

more more

CEU eTD Collection liquidity. the lost everything thus, and, crisis, the in losses big suffered they arbitrageurs: of side the from explained be can this Moreover, indicate stocks than was expected. so or situations, crisis well, look to seem exchange stock on things times good at although that mean may it implications policy For stocks. of movement price in matter to started they and important more became expectations signifi VIX in increase returns price listed cross of movements change squared) R decreased was it as level same sw a e n al in see can we As Also, w ,

over time that means that local effects persistently or even more explain the the explain more even or persistently effects local that means that time over piitc res optimistic hile FTSE did not change a lot. lot. a change not did FTSE hile

the

Russian index index Russian

. In other words, R squared of the model the of squared R words, other In . eoe h crisis the before ls eas i mas ht oa efcs atr vn oe ih time. with more even matter effects local that means it because ults cance for all the companies, which companies, the all for cance css represented cases l MICEX increased increased

during and and during ol Gzrm hw sihl dfeet eut with results different slightly shows Gazprom (only - called “bad time “bad called F r h mre efcec such efficiency market the or 40 –

either the liquidity decreases or stay or decreases liquidity the either its its

after the crisis. The most notable change is is change notable most The crisis. the after lo sne surd s increasing, is squared R since Also, significance in the latter period latter the in significance

show s” can do the situation much worse worse much situation the do can s” s

that after the cr the after that either nrae o os not does or increases

yais can dynamics isis investors’ investors’ isis

for all the all for

a the at s

not the

CEU eTD Collection fun demand stocks. internationally listed cross of premium/discounts and restrictions ownership foreign the is theory this on claims main dif about preposition our with prices different at traded be can securities listed cross then segmented, model. financial markets. with wrong something be should there that means it 2012, to 2006 from period the during case our in as exist, do opportunities arbitrage persistent when Thus, impossible. arbitrage is theory financial of Much prices matter possible is results. the bypresented as Russia and London for enough whe difference price the for looking people are there side, other the From returns. bigger get can behavior; different present Russi in different are Investors agents. global of view the from from studied be can role the of stocks’ prices returns of predictability To conclude To There are several researches in financial eco financial in researches several are There .

because o because Arbitrage should not be possible because otherwise market forces should elimina should forces market otherwise because possible be not should Arbitrage

n ter i mre sgetto ter ta tls that tells that theory segmentation market is theory One in determining the returns the determining in

ction of both local and foreign investors. In such a country, foreign investors are investors foreign country, a such In investors. foreign and local both of ction ept te at ht accor that fact the despite

and allowing more chance to predict thereturnsand chance allowing more topredict f integration of financial markets and markets financial of integration f ,

Moscow Stock exchange is exchange Stock Moscow

different perspectives different ’

difference in London they seem to be less risk averse, and that is why they they why is that and averse, risk less be to seem they London in

built on the on built eet netr’ eair r ifrn lcl regulations local different or behavior investors’ ferent . This situation situation This . Foreign becomes n it it n ig o h eooi research economic the to ding

assumption that securities that assumption : from the point of view of local market agents and and agents market local of view of point the from : s es r oe trcie bt hi atvt i not is activity their but attractive, more or less is

ownership restrictions are likely to change the the change to likely are restrictions ownership 41 easier during easier

not perfectly liquid because local effects play effects local because liquid perfectly not

is crucially important for policy makers and makers policy for important crucially is nomics that can explain the findings of the of findings the explain can that nomics , as a consequence, the consequence, a as ,

In other words, Inother time, leaving less for randomness randomness for less leaving time, a and in London, in and a globally .

trade at prices at trade

if capital markets are are markets capital if ,

, which is consistent is which , arbitrage who are persistently persistently are who persistent

equalization of equalization

and they can can they and

hud not should that make make that

arbitrage . The The . te it. te

CEU eTD Collection money their lose they how observe they money, his/her with doing is he/she what understand problems, agency I money. bring could that positions volatile liquidate to them force who money people’s other l real arbitragein that showed and model impossible arbitrage persistence prices securities’ fina of analysis prevail should of efficiency market. the converg and happen can arbitrage persistent why of models because market barriers. of factors foreign and local both by influenced are GDRs their while factors, local by affected are securitiesIndian underlying andequal, not are prices GDRs’ Indian that found also(2000) mat not did prices daily companies’ British of ADRs that found also (1996) Miller difficult. arbitrage the made barriers the and stocks, underlying the to relative discount at sold were GDRs Taiwanese that found (1999) Bailey example, fin similar with studies the is segmentation market if point second The liquidity. higher and coverage, informational larger stocks, such for demand international restricted, is ownership whose shares matching ownership unrestricted that demonstrate that studies several also are There 1995). (Stulz, investors home than stocks local for price higher pay to ready sc css arbitrageurs cases, such n okn a te rbe fo the from problem the at Looking n o te ot aos is famous most the of One financial .

Financial economics literature claims that arbitrage plays a crucial role in the in role crucial a plays arbitrage that claims literature economics Financial ca mres eas eaty olcie acti collective exactly because markets ncial

o euiys udmna vle keig h mre efficient market the keeping value, fundamental security’s to managing money possessed by other people who do not exactly know and and know exactly not do who people other by possessed money managing akt cnieig o ovrec o pie a txbos suggest textbooks as prices of convergence no considering markets

hud e mr capital more get should .

S hleifer and Vishny developed performance developed Vishny and hleifer ife is very limited especially if arbitrageurs play with with playarbitrageurs if especially very limited is ife on o ve of view of point hefr n Vishny and Shleifer 42

are traded with premiums because of of because premiums with traded are rm netr ad i te rsne of presence the in and, investors from ch matching securities. Jithendranathan securities. matching ch global ence of prices does not happen o happen not does prices of ence s oe (97. They (1997). model ’s n o arbitrageurs of ons

f tcs relativ stocks, of arbitrage dings as we have: for for have: we as dings tee r several are there , - based arbitrage arbitrage based

and making making and bring e to those those to e

studied studied

back back n

CEU eTD Collection bring fundsas “long new tothe market money” players pension andprivate refo pension Exchange. Stock Moscow the on investors financ l a such for reasons the are and population the of knowledge financial low Russia, Central in services financial of concentration territorial heavy population, of income average – inBrazil is14%, comparison, shareinChina this investors.For active individual populationis economically of 1.7% only generally, exchange: Russian for problems crucial the of one is of level low a such that claim Moscow in Center Financial International banks. investment and funds, pension decreasing over investors professional arbi prices. of “full” equalization theoretical prevents more even life, real in happening is which investors, few just of hands the in transactions arbitrage concentrating that emphasize authors extreme capital. extra with him/her provide to refuse and

19%, inGermany rfsinl netr ae ersne msl by mostly represented are investors Professional a mres uhrte for authorities markets ial

oaiiy ep t udrtn pritn ecs rtrs n tc prices. stock in returns excess persistent understand to helps volatility rm, encouraging people to participate in voluntary pension programs pension voluntary in participate to people encouraging rm, recent yearsrecent –

30% together with individual investors individual with together codn t te statistics the to According , in ow level of individual investors individual of level ow , which arbitrage makes diffi more

pay –

48%, a 48%, ing

attention to the necessity to attract more domestic domestic more attract to necessity the to attention Russian working group responsible for creating creating for responsible group working Russian nd inthe

One of the options to achieve this goal can be be can goal this achieve to options the of One 43

rm ocw exchange Moscow from US xcl sc a aodne n fa of fear and avoidance an such Exactly

no trust to domestic financial markets markets financial domestic to trust no – on Moscow Stock Exchange Stock Moscow on

60%. According to 60%. According uul ud, non funds, mutual

(Moscow IFC, 2012) IFC, (Moscow cult

(Table 10 (Table individual investors individual .

)

. of number the , economists, low

- trage and full full and trage governmental , which will which , .

This calls This lo the Also,

is even is

CEU eTD Collection which isUSD43 2 these so, calculations), governm average weighted information official the on Based prices. the equalize to them enable a not does obviously that 50%) than (more companies Russian largest the of ownership the in share government excessive be can USD to years 6 last Database, 2012). IR for One (Thomson 2011 of beginning the to comparison in 12.8% by rise a is which 2410, i residents. non of number total of dynamics than pattern volatile more shows Exchange Stock Moscow decreasi dynamics its on and Exchange Loo exchanges. both on prices in Exchange nvest in local stocks and depositary receipts, has been increasing in 2010 in increasing been has receipts, depositary and stocks local in nvest One more more One However, their investments in Russian stocks in Russian investments their However, g n 2011. in ng oee, hr i sm otmsi tnec: h nme o frin ud who funds foreign of number the tendency: optimistic some is there However, the 2 millions monthly( policy implication policy

ol fnnil market, financial world 15.6 billion, which is the is which billion, 15.6

uh dnmc o atv cins h ae non are who clients active of dynamics a Such 7 % out of the whole MICEX index is so is index MICEX whole the of out % n sae f usa idx s 27 is index Russian of share ent

ig t h nme o frin clients foreign of number the at king Fgr 9) (Figure

of the results is results the of 27 llow participating of enough number of arbitrageurs arbitrageurs of number enough of participating llow % out of USD1,6 billion monthly;USD1,6 billion % outof MICEX, 2011) hc i lkl t lmt rirg ad qaie the equalize and arbitrage limit to likely is which w cn e that see can we ,

fall of 17.2%. of fall 44

decreased insufficient integration of integration insufficient

One probable explanation for this for explanation probable One

in 2011 in (see % h nme o frinr is foreigners of number the - called “non called

and our calculations our and

- for the firs the for eiet o Rsi on Russia of residents Appendix

on Moscow Stock Stock Moscow on - 2011 and reached and 2011

- Moscow Stock Stock Moscow tradable” part tradable” t time for the for time t

for . , the the ,

the - ,

CEU eTD Collection and traded are and London in companies listed capitaliza lowest with For two randomly. selected and capitalization highest the with two companies: four showing theincreasedimportance o since market world do the coefficients difference other The theory. markets of priceswhich exchanges, onboth isconsistent in integrated the emphasize to authorities policy of attention the for calls which index volatility stocks underlying one capitalized small for and capitalized largely re the of result London in and Russia in traded stocks liquid sufficiently es not seem to be optimistic optimistic be to seem not es price of Russian stock relative to London’s price London’s to relative stock Russian of price Certainly, the liquidity varies across stocks: across liquidityCertainly,varies the is Exchange Stock Moscow whether determine to was paper the of purpose The Despite where the stock is traded more actively; however, small stocks do not support the support not do stocks small however, actively; more traded is stock the where

for small stocks than for large stocks large for than stocks small for the the to do the panel data for this model and compare the results the compare and model this for data panelthe do to search, we found several outcomes several found we search,

also matters. This demonstrates This matters. also

world financial market in order to allow for more arbitrage for equalization equalization for arbitrage more for allow to order in market financial world important results of the model, the of results important . To achieve this goal, we used the used we goal, this achieve To .

r sbet to subject are

the crisis. As was expected, VIX became more significant over time, time, over significant more became VIX expected, was As crisis. the f uture research it would be better be would it research uture is – the on other foreign markets where Russian depository receipts depository Russian where markets foreign other on

Russian stock exchange stock Russian l as such effects local f investors’ expectations on agr infcne of significance larger

Conclusion ih al osrain fr six a for observations daily with 45 the insufficient liquidit insufficientthe

with Schleifer and Vishny’s model : appreciation of Russian currency increases increases currency Russian of appreciation : there are some limitations some are there the

s that are valid for both types of stocks: fo stocks: of types both for valid are that . Firstly, returns returns Firstly, . .

During time, the situation on the market market the on situation the time, During indexes’coefficient OLS estimation OLS cl nee, xhne ae while rate, exchange indexes, ocal

to collect the data for all 31 all for data the collect to has become has the

returns. xhne rate exchange of of yof

ed o being for need model of cross listed cross of model less integrated in integrated less s are larger for those those forlarger are s

Russian ADRs and and ADRs Russian with Russian stocks Russian with

- Russian exchange, Russian er period year . We address only only address We .

ih negative with

(1997) . As a a As .

more more cross cross tion tion . the the

CEU eTD Collection liquiditydevelop. continue will to merged one creating of possible situation is it exchange, current the in Now, month. a million 432 USD about constitutes that government the of hand the in is market, the on traded be could otherwise p be can measure of relevant A equalization prices. and arbitrage, extensive players, market more for allow will which ones, investors domestic attracting thecurre greatly for option One significanceincreasing). is variables’ MICEX and VIX (since expected than more even decrease can liquidity the losses, big suffer arbitrageurs when times, bad at that shows which worse, even became liquidity aftert Moreover, integration. sufficient for place take to arbitrage preventenough liquidity underly and London in traded stocks Russian of receipts depositary between differentials return price of economies close after market financial Russian of specifications future for used extensively impact would Russia. in regulations investors in change how find to returns stock Russian influence factors l the cross iquidity among other among iquidity listed on other foreign markets foreign other on listed The results of the paper shows that there are local effects that influence the movements movements the influence that effects local are there that shows paper the of results The Policy context and low integration integration low and ing Russian stocks traded on Russian exchange MICEX. It indicates insufficient insufficient indicates It MICEX. exchange Russian on traded stocks Russian ing

oee, h mdl contai model the However, considerations, wh to follow the necessary reforms, otherwise, the trend of lowering the the lowering of trend the otherwise, reforms, necessary the follow to

methods.

of Moscow stock exchange stock Moscow of (possibly by reforms considering voluntary pension) voluntaryconsidering reforms by(possibly financial market market financial

Also, it would be interesting to see which macroeconomic which see to interesting be would it Also, . rivatization, since currently 27% of Russian Index that that Index Russian of 27% currently since rivatization,

Moreover, cross listing is listing cross Moreover,

ich limits , the results should be used for other emerging emerging other for used be should results the , 46

s bu 10 osrain; hs i cn be can it thus, observations; 1400 about ns

the external validitythepaper. of oiy reforms policy in the global financial market, which which market, financial global the in nt situation is to pursue reforms pursue for to is situation nt

only one aspect of looking at looking of aspect one only

n Russia in De o the to Due . he crisis, the crisis, he

and foreign and

CEU eTD Collection

Table A1. Table A1. Appendix 1 Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R after adjustments 1228 observations: Included 1229 2 Sample(adjusted): Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R In 1230 1 Sample(adjusted): L_RET Variable: Dependent - - - - cluded observations: 1230 after adjustments 1230 observations: cluded statistic statistic squared squared L_NMICEX( L_NMICEX(1) L_EXCH( L_NMICEX L_NMICEX L_EXCH(1) L_FTSE( L_FTSE(1) - - L_EXCH L_EXCH statistic) statistic) L_FTSE Variable L_FTSE V ariable

C C - - 2 1.

squared squared

Results on Lukoil baselineResults onLukoil model’s regression baselineResults onLukoil model’s regression

- - 1)

Coefficient Coefficient ------0.057487 0.082210 0.088243 0.163787 0.091218 0.324646 0.092252 0.069390 0.029719 0.024136 0.000000 19.03230 4087.521 0.093529 0.008734 0.042161 0.044499 0.118937 0.324723 0.025617 0.000000 8.254484 4088.350 0.092247 0.00 0.050523 5.56E 8.26E

8703 - - 06 06

Mean dependent var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. Std. Error Std. Error Std. 0.000249 0.074831 0.0 0.075302 0.052695 0.052765 0.052653 0.026297 0.026417 0.026402 0.000249 0.074665 0.052209 0.026237

74892 Appendixes - - - - Watson stat Watson Watson stat Watson Quinn criter. Quinn Quinn criter. Quinn

------t t 0.022309 1.592932 6.219690 0.976378 0.033239 1.098618 1.178266 2.175062 1.731039 6.152681 1.752079 2.638665 1.124996 0.914172

- - Statistic Statistic

------

with lea with 2.793293 6.633613 6.623238 6.639871 0.008924 2.772779 6.626597 6.600626 6.642264 0.008931 2.86E 3.94E 0.9822 0.1114 0.0000 0.3291 0.9735 0.2722 0.2389 0.0298 0.0837 0.0000 0.0800 0.0084 0.26 0.3608 Prob. Prob.

- - 06 07 08

ds andlags

CEU eTD Collection

Table A Table A Table A Included observations: 1480 after adjustments 1480 observations: Included 1481 2 Sample(adjusted): Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R I 1482 1 Sample(adjusted): L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R after adjustments 1482 observations: Included 1482 1 Sample(adjusted): L_RET Variable: Dependent ncluded observations: 1482 after adjustments 1482 observations: ncluded - - - - statistic statistic squared squared L_NMICEX( L_NMICEX L_NMICEX L_NMICEX L_EXCH - - L_FTSE Variable L_EXCH statistic) statistic) Variable L_FTSE Variable D2011 1 1 1

C . . . C - -

5 4 3

squared squared

. . .

Results on Results on Results on

Coefficient - -

Coefficient Coefficient

5.733521 4443.738 0.215741 0.012082 0.009497 0.011504 0.000224 0.178287 0.218601 0.028656 0.000672 - - - Gazprom Gazprom Gazprom 0.000672 4.865214 4444.864 0.215413 0.012077 0.010332 0.013005 0.001294 0.179115 0.219103 0.029424 0.035076 0.065858 2.12E

- 05

baseline model’s baseline model’s baseline model’s Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. M Std. Error Std. 0.000314 0.096856 0.066375 0.035148 Std. Error Std. Std. Error Std. 0.000342 0.000863 0.096817 0.066348 0.035137 0.035679 0.035728 ean dependent var eandependent

- - Watson stat Watson - Quinn criter. Quinn - Watson stat Watson Quinn c Quinn

48 - - t 0.713222 1.840746 3.293416 0.815298 - Statistic

- - - riter. t t 0.062072 1.498598 1.850040 3.302323 0.837408 0.983081 1.843316

- -

Statistic Statistic

regression without dummyregression without variable dummyregression with variable regression with lead regression with

2.505991 5.986216 5.977241 5.991550 0.012140 0.000230

0.4758 0.0659 0.0010 0.4150 Prob. - - -

2.506065 5.985053 5.973834 5.991719 0.012140 0.000230 0.9505 0.1342 0.0645 0.0010 0.4025 0.325 0.0655

Prob. Prob. - - -

s andlags

CEU eTD Collection

Table A Table A Included observations: 1289 after adjustments 1289 observations: Included 1290 2 Sample(adjusted): L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R after adjustments 1290 observations: Included 1290 1 Sample(adjusted): L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R - - - - statistic statistic squared squared L_NMICEX( L_NMICEX(1) L_NMICEX(1) L_EXCH( L_EXCH( L_NMICE L_NMICEX L_EXCH(1) L_EXCH(1) L_FTSE( L_FTSE( L_FTSE(1) L_FTSE(1) - - L_EXCH L_EXCH L_EXCH statistic) statistic) L_FTSE Variable L_FTSE Variable L_FTSE 1 1

. . C C C - - 7 6

squared squared

. .

Results on Results on

- - - - 1) 1)

X 1) 1)

Coefficient Coefficient

------Severstal Severstal - - 0.164203 0.069484 0.038565 0.228368 0.060363 0.066781 0.000000 30.54645 3801.292 0.208263 0.012726 0.0643 0.066519 0.461018 0.330116 0.089109 0.000352 3.423350 4443.638 0.213740 0.0 0.014532 0.020529 0.000229 0.054941 0.040583 0.452346 0.215048 0.131486 0.313575 0.054220 0.042891 0.099092 0.039767 3.42E 2.28E

12058 - - 05 05 41

baseline model’s baseline model’s Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Std. Error Std. Std. Error Std. 0. 0.098249 0.067284 0.067142 0.067174 0.035284 0.000354 0.103449 0.072112 0.040382 0.000313 0.097292 0.000354 0.103947 0.103764 0.104971 0.073154 0.072697 0.072764 0.040537 0.040595 0.040702 097138

- - - - Watson stat Watson Wat Quinn criter. Quinn Quinn criter. Quinn

son stat son 49

------t t 0.731000 0.564705 1.690417 0.707225 0.573159 3.401270 0.898608 1.892664 0.064 0.390416 4.359374 2.048636 1.797386 4.313464 0.745148 1.058067 2.441015 0.977029 0.096564 4.456489 4.577849 2.206650

- -

Statistic Statistic regression regression with leadsandlags regression with

419

------2.485167 5.978054 5.955594 5.991403 0.012147 0.000226 2.914902 5.881266 5.871267 5.887275 0.013156 1.21E 0.4649 0.5724 0.0912 0.4795 0.5666 0.0007 0.3690 0.0586 0.9486 0.6963 0.0000 0.0407 0.0725 0.0000 0.456 0.2902 0.0148 0.3287 0.9231 0.0000 0.0000 0.0275

Prob. Prob.

- 05

CEU eTD Collection

Table A Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R after adjustments 1431 observations: Included 1432 2 Sample(adjusted): Prob(F F Loglikelihood Sum ofregression S.E. R Adjusted R after adjustments 1432 observations: Included Sample L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R Prob(F F Table A ------statistic statistic statistic squared squared squared L_NMICEX( L_NMICEX(1) squared resid squared L_EXCH( L_NMICEX L_NMICEX L_EXCH(1) L_FTSE( L_FTSE(1) - - - L_EXCH L_EXCH statistic) statistic) statistic L_FTSE Variable L_FTSE Variable (adjusted): 1 1432 1 (adjusted): 1

. C C - - - . 8

squared squared squared 9

. . Results on

) - Results on - 1)

Coefficient Coefficient

------NLMK - - 3803.835 0.206336 0.012701 0.068597 0.075105 0.050614 0.270427 0.101800 0.044971 0.188637 0.033423 0.000169 6.713795 4307.786 0.204434 0.011965 0.011837 0.013908 0.110967 0.265576 0.196381 0.000000 11.53995 0.004151 2.693546 4306.369 0.203837 0.011977 0.010546 0.016774 0.035184 0.108993 0.017297 NLMK NLMK 6.97E 1.04E

- - 06 05 baseline model’s baseline model

Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Durbin Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Std. Error Std. Error Std. 0.067796 0.067281 0.067298 0.096835 0.0 0.097907 0.000316 0.0 0.066637 0.096104 0.000317 0.035786 0.035842 0.035873

35528 96712 ------Watson stat Watson Watson stat Watson stat Watson Quinn criter. Quinn Quinn criter. Quinn criter. Quinn

50 ’s

regression

------regression with leadsa regression with t t 0.022037 3.123381 3.985429 2.043421 0.032760 0.983191 3.040922 0.482170 0.746562 4.019368 1.512667 0.464415 1.950497 0.341372

- - Statistic Statistic

------

- 6.010875 0.012036 2.928456 5.871448 5.8 5.886478 0.013161 2.810587 5.990967 5.967909 6.004709 0.012041 2.814446 6.005382 5.996163 9.45E 1.79E 6.71E 0.9824 0.0018 0.0001 0.0412 0.9739 0.3257 0.0024 0.6298 0.4555 0.0001 0.1306 0.6424 0.0513 0.7329 Prob. Prob. 46435

- - - 06 06 07

n d lags

CEU eTD Collection

Table A Table A Appendix 2 Included observations: 1480 after adjustments 1480 observations: Included 1481 2 Sample(adjusted): L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregres S.E. R Adjusted R after adjustments 1228 observations: Included 1229 2 Sample(adjusted): L_RET Variable: Dependent - - statistic squared L_NMICEX( L_NMICEX( L_NMICEX(1) L_NMICEX(1) L_EXCH( L_EXCH( L_NMICEX L_NMICEX L_EXCH(1) L_EXCH(1) L_FTSE( L_FTSE( L_FTS L_FTSE(1) L_VIX( L_VIX( - L_VIX(1) L_VIX(1) L_EXCH L_EXCH statistic) L_FTSE Variable L_FTSE Variable L_VIX L_VIX 2 2

. . C C - 2 1

squared

. .

E(1) sion

Results on Results on - -

- - 1) 1)

1) 1)

- -

1) 1)

Coefficient Coefficient

------Lukoil extendedLukoil Gazprom extended 0.061542 0.000000 6.530299 4090.374 0.091943 0.008699 0.051311 0.060589 0.000550 0.002228 0.007036 0.076420 0.097166 0.154639 0.102535 0.312385 0.058638 0.071959 0.030458 0.023484 0.000228 0.021790 0.015234 0.014983 0.053121 0.179239 0.058970 0.025585 0.170106 0.031403 0.070594 0.036526 1.03E

- 05

Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Std. Error Std. Error Std. 0.035730 0.000248 0.004252 0.004376 0.004144 0.074973 0.075060 0.075576 0.057577 0.0594 0.058381 0.026323 0.026439 0.026450 0.000313 0.012181 0.012591 0.011930 0.097347 0.097217 0.098351 0.074241 0.076714 0.075744 0.035303 0.035645

model’s - - Watson stat Watson Quinn criter. Quinn

31 model’s

regression with leadsandlags with regression ------t t 0.041613 0.129312 0.509022 1.698034 1.019299 1.294505 2.046132 1.780828 5.256234 1.004389 2.733684 1.152035 0.887840 0.727934 1.788754 1.2099 1.255943 0.545691 1.843708 0.599590 0.344624 2.217418 0.414596 1.999656 1.024737 1.722419

- - Statistic Statistic

regression with leadsandlags regression with

- - - 2.768537 6.620307 6.586545 6.640674 0.008931 3.94E 0.9668 0.8971 0.6108 0.0898 0.3083 0.1957 0.0410 0.0752 0.0000 0.3154 0.0064 0.2495 0.3748 0.4668 0.0739 0.2265 0.2093 0.5854 0.0654 0.5489 0.7304 0.0267 0.6785 0.0457 0.3057 0.0852 Prob. Pro

- b. 07

CEU eTD Collection

Table A Table A Included observations: 1431 after adjustments 1431 observations: Included 1432 2 Sample(adjusted): L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R after adjustments 1289 observations: Included 1290 2 Sample(adjusted): L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R - - - - statistic statistic squared squared L_NMICEX( L_NMICEX( L_NMICEX(1) L_NMICEX(1) L_EXCH( L_EXC L_NMICEX L_NMICEX L_EXCH(1) L_EXCH(1) L_FTSE( L_FTSE( L_FTSE(1) L_FTSE(1) L_VIX( L_VIX( - - L_VIX(1) L_EXCH L_EXCH statistic) statistic) L_FTSE Variable L_FTSE Variable L_VIX 2 2

. . C - - 4 3

squared squared

. . H(

Results on R - -

- - 1) 1)

esults on 1) 1)

- -

1) 1)

Coefficient Coefficient

------NLMK extendedNLMK Severstal extended - 3.143438 4447.076 0.212749 0.012043 0.017094 0.025069 0.000000 11.24374 3818.298 0.201757 0.012574 0.087124 0.095629 0.06211 0.004842 0.034418 0.042601 0.097703 0.044748 0.282915 0.249964 0.138969 0.067496 0.444744 0.206736 0.000194 0.002653 0.037872 0.112156 0 0.197722 0.166584 0.100169 0.053905 0.207475 0.020712 2.86E

.024981

- 05 1

Durbin Hannan criterion Schwarz Akaike var dependent S.D. var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Std. Error Std. Std. Error Std. 0.000350 0.013366 0.013891 0.013094 0.040251 0.040225 0.040367 0.080791 0.083344 0.081994 0.103117 0.102962 0.104190 0.011865 0.035609 0.035615 0.035679 0.074369 0.076484 0.075507 0.096364 0.096279 0.097496

model’s - - - - info criterion info Watson stat Watson Watson stat Watson Quinn criter. Quinn Quinn criter. Quinn

model’s

------regression with leadsandlags with regression t t 1.058376 2.428916 1.108526 3.5018 2.999204 1.694857 0.654562 4.319488 1.984226 0.223561 1.063551 3.149174 0.700153 2.658671 2.178023 1.326615 0.559382 2.154932 0.2 0.081567 4.647037 0.348529 2.628494

- - Statistic Statistic

regression with leadsandlags regression with 12436

------2.484036 5.974641 5.945442 5.991995 0.012147 0.000226 2.906545 5.884724 5.852207 5.904264 0.013161 9.45E 0.2901 0.0153 0.2678 0.0005 0.0028 0.0903 0.5129 0.0000 0.0474 0.8231 0.2877 0.0017 0.4839 0.0079 0.0296 0.1848 0.5760 0.0313 0.8318 0.9350 0.0000 0.7275 0.0087 Prob. Prob.

- 06

CEU eTD Collection

Table A3.1. Appendix 3 Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R - - statistic squared - L_VIX(1) statistic) L_VIX

C -

squared

Autocorrelation

- 0.023683 0.031876 0.055414 0.021316 0.000007 3.890744 4317.445 0.2007 0.011897 1.38E

of the dependent variabl - 05 06

S.D. dependent var dependent S.D. var dependent Mean Durbin Hannan criterion Schwarz Akaikecriterion info 0.000315 0.012126 0.012517

- - Watson stat Watson Quinn criter. Quinn

- 0.043984 4.569934 1.703057

e (log differences) return

- - - 2.809243 5.998131 5.968155 6.015996 0.012041 6.71E 0.9649 0.000 0.0888

- 07 0

CEU eTD Collection 

Earlier period Table A4 Appendix 4 Table A3.2 Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R afteradjustments 626 observations: Included Squares Least Method: L_RE Variable: Dependent - - statistic squared L_NMICEX( L_NMICEX L_EXCH( L_NMICEX L_EXCH(1) L_FTSE( L_FTSE(1) L_VIX( - L_VIX(1) L_EXCH statistic) L_FTSE Variable L_VIX

. C - 1

squared

. .

The results ontheregressionThe results Gazprom different in periodsfor Autocorrelation -

- 1)

- (10/02/1006 1)

(1)

Coefficient T ------0.011362 0.005353 0.003987 0.041738 0.085059 0.115879 0.027480 0.088349 0.127896 0.021464 0.016730 0.010630 0.003644 2.474158 2493.204 0.012727 0.004556 0.027525 0.0401 2.79E

–

15/09/2008)

of the - 96 05

Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean given Std. Error Std. 0.007446 0.007785 0.006970 0.106119 0.104661 0.104503 0.046389 0.050471 0.049011 0.022602 0.023462 0.022234 0.000183

- - variable ( variable Watson stat Watson Quinn criter. Quinn

------t 0.152640 1.525877 0.687616 0.571959 0.393316 0.812 1.108857 0.592382 1.750474 2.609530 0.949635 0.713069 0.478111

- Statistic

local indexes

708

- - - 2.869931 7.888156 7.831785 7.923976 0.004621 4.03E 0.8787 0.1276 0.4920 0.5676 0.6942 0.4167 0.2679 0.5538 0.0805 0.0093 0.3427 0.4761 0.6327 Prob.

- ) 05

CEU eTD Collection  

Earlier period Later period Table A4 R afte 645 observations: Included Squares Least Method: L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R afteradjustm 854 observations: Included Squares Least Method: L_RET Variable: Dependent Sum squared resid Sumsquared ofregression S.E. R Adjusted - - - statistic squared squared L_NMICEX( L_NMICEX( L_NMICEX(1) L_NMICEX(1) L_EXCH( L_EXCH( L_NMICEX L_NMICEX L_EXCH(1) L_EXCH(1) L_FTSE( L_FTSE( L_FTSE(1) L_FTSE(1) L_VIX( L_VI - L_VIX(1) L_VIX(1) L_EXCH L_EXCH statistic) L_FTSE Variable L_FTSE Variable L_VIX L_VIX

.2 C C - - X(

squared squared

(16/09/2008 The results ontheregressionThe results Lukoil different in periodsfor - -

- - 1) 1)

- - (10/02/2006 1) 1)

1) 1)

- -

1) 1)

Coefficient Coefficient ------0.120488 0.086930 0.036596 0.027546 0.011285 0.007818 2.269824 2361.080 0.198413 0.015360 0.017550 0.031371 0.000414 0.032384 0.027459 0.025716 0.046599 0.204573 0.042899 0.064874 0.185770 0.006894 0.101468 0.053620 0.092115 0.011686 0.004300 0.050 0.067906 0.005861 0.002209 0.003062 0.033224 0.083802 0.172018 0.096235 3.61E

–

– r adjustments r

30/03/2012)

15/09/2008) 208 - 05

ents Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Schwarz criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Std. Error Std. Error Std. 0.047306 0. 0.021408 0.021684 0.021708 0.000526 0.020420 0.020989 0.020309 0.133225 0.133201 0.135561 0.122125 0.123394 0.123399 0.056823 0.056530 0.058482 0.000170 0.003008 0.003142 0.002826 0.098952 0.097869 0.097828 0.043807

045849

- - Watson sta Watson Quinn criter. Quinn

------t t 0.787891 1.585909 1.308221 1.266263 0.349774 1.535816 0.316456 0.531205 1.505495 0.055865 1.785695 0.948525 1.575094 0.212375 1.948455 0.702884 1.083440 0.335762 0.856271 1.758381 2.196806 2.547006 1.896029 1.709433 1.270364 0.519871

- - Statistic Statistic t

------5.426710 5.499016 0.015496 0.000363 7.950358 8.040436 0.004412 2.455259 5.471325 1.66E 0.4310 0.1131 0.1912 0.2058 0.7266 0.1250 0.7517 0.5954 0.1326 0.0055 0.0745 0.3431 0.1156 0.8319 0.0518 0.4824 0.2790 0.7372 0.3922 0.0792 0.0284 0.0111 0.0584 0.0879 0.2044 0.6033 Prob. Prob.

- 05

CEU eTD Collection  

Earlier period Later period Tabl Included observations: 578 afteradjustments 578 observations: Included Squares Least Method: L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R afteradjustments 583 observations: Included Squares Least Method: L_RET Variable: Dependent Prob(F F Loglikelihood - - - statistic statistic squared L_NMICEX( L_NMICEX( L_NMICEX(1) L_NMICEX(1) e A4 L_EXCH( L_EXCH( L_NMICEX L_NMICEX L_EXCH(1) L_EXCH(1) L_FTSE( L_FTSE( L_FTSE(1) L_FTSE(1) L_VIX( L_VIX( - - L_VIX(1) L_VIX(1) L_EXCH L_EXCH statistic) statistic) L_FTSE Variable L_FTSE Variable L_VIX L_VIX

. C C - 3

squared

(16/09/2008 The results ontheregressionThe results NLMK different in periodsfor - -

- - 1) 1)

- - (20/04/2006 1) 1)

1) 1)

- -

1) 1)

Coefficient Coefficient ------0.000011 3.836948 2606.041 0.058340 0.000020 3.721566 1768.502 0.079136 0.011783 0.053133 0.072656 0.001674 0.005312 0.011284 0.087662 0.094964 0.145513 0.145991 0.419663 0.068047 0.103914 0.058205 0.048219 0.009977 0.005144 0.012965 0.291306 0.180295 0.013554 0.000337 0.301659 0.102000 0.000489 0.148618 5.61E 7.26E

–

28/02/2011)

15/09/2008) - - 05 05

Durbin Hannan Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Std. Error Std. Error Std. 0.049806 0.000489 0.008414 0.008598 0.008354 0.110436 0.110780 0.111712 0.105375 0.106518 0.105759 0.046362 0.046204 0.046478 0.000393 0.014620 0.01631 0.015680 0.220584 0.220561 0.223281 0.102427 0.105441 0.097739 0.047515 0.050385

- - - - Wa Watson stat Watson Quinn criter. Quinn Quinn criter. Quinn 8 tson stat tson

------t t 0.148495 0.199019 0.617830 1.350630 0.793783 0.857233 1.302572 1.385440 3.939826 0.643415 2.241373 1.259730 1.037462 0.142817 0.682392 0.315269 0.826847 1.320612 0.817439 0.060704 0.003290 2.860915 1.043590 0.010286 2.949660 1.171342

- - Statist Statistic

- - - - 2.967337 8.005485 2.729453 5.984339 5.924901 6.022305 0.012109 1.92E 0.8820 0.0823 0.5369 0.1774 0.4277 0.3917 0.1932 0.1665 0.0001 0.5202 0.0254 0.2083 0.3000 0.8865 0.4953 0.7527 0.4087 0.1872 0.4140 0.9516 0.9974 0 0.2971 0.9918 0.0033 0.2420 Prob. Prob.

.0044 - 05

CEU eTD Collection  

Earlier period La Table A4 Included observations: 437 observations: Included Squares Least Method: L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R afteradjustments 853 observations: Included Squares Least Method: L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R - - - - ter period (16/09/2008 period ter statistic statistic squared squared L_NMICEX( L_NMICEX( L_NMICEX(1) L_NMICEX(1) L_EXCH( L_EXCH( L_NMICEX L_ L_EXCH(1) L_FTSE( L_FTSE( L_FTSE(1) L_FTSE(1) L_VIX( - - L_VIX(1) L_EXCH L_EXCH statistic) statistic) L_FTSE Variable L_FTSE Variable L_VIX NMICEX

. C - - 4

squared squared

The results ontheregressionThe results different in periodsfor -

- - 1)

- - (09/10/2006 1) 1)

1) 1)

- -

1) 1)

Coefficient Coefficient

------1883.468 0.050012 0.009408 0.015465 0.035941 0.000172 3.194263 2480.956 0.148655 0.013303 0.029979 0.043641 0.016551 0.032095 0.085381 0.015255 0.225984 0.05527 0.194283 0.078210 0.265640 0.047407 0.079741 0.031518 0.052429 1.755306 0.420403 0.283699 0.142125 0.273457 0.081069 0.012010 0.147224 0.020222 2.44

–

31/03/2012)

E 15/09/2008) - 05 9

Hannan criterion Schwarz Akaikecriterion info var dependent S.D. var dependent Mean Durbin Hannan Schw Akaikecriterion info var dependent S.D. var dependent Mean Durbin Std. Error Std. Std. Error Std. 0.000456 0.017602 0.018199 0.017700 0.117531 0.115358 0.115346 0.107495 0.107600 0.106436 0.050588 0.048975 0.049208 0.170735 0.170643 0.074404 0.080817 0.078895 0.045812 0.045830 0.045831

arz criterion arz

- - - - Watson stat Watson Watson stat Watson Quinn criter. Quinn Quinn criter. Quinn

------t t 0.129795 1.958980 0.479247 1.807363 0.726857 2.495781 0.937131 1.628189 0.640503 2.462311 1.662530 1.910172 3.383659 1.027559 0.262161 3.212374 0.441228 0.053452 0.940275 1.763559 4.823785

- - Statistic Statistic

------2.816070 6.433973 6.374153 6.472206 0.009482 2.802111 5.758814 5.714159 5.786532 0.013507 9.67E 7.68E 0.8968 0.0504 0.6319 0.0711 0.4675 0.0128 0.3490 0.0 0.5220 0.0142 0.0971 0.0568 0.0008 0.3047 0.7933 0.0014 0.6593 0.9574 0.3473 0.0782 0.0000 Prob. Prob.

039 - -

06 06 Severs

tal

CEU eTD Collection 

Later period Table A5 Appendix 5 Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R afteradjustments 852 observations: Included Least Method: L_RET Variable: Dependent Prob(F F Loglikelihood resid Sumsquared ofregression S.E. R Adjusted R MTLR RASP MSNG OGKC MAGN TICKER - - - - statistic statistic squared squared L_NMICEX( L_NMICEX(1) L_EXCH( L_NMICEX L_EXCH(1) L_EXCH(1) L_FTSE( L_FTSE(1) L_VIX( L_VIX( - - L_VIX(1) L_VIX(1) L_EXCH

statistic) statistic) L_FTSE Variable

L_VIX L_VIX

. C C - - 1

squared squared

(16/09/2008 Calculations ofweighedaverage share inMICEX Indexgovernment inRussia - -

Squares - 1) 1)

- 1)

W 1)

Index eight

0,37% 0,31% 0,20% 0,18% 0,14% Coefficient

in ------0.000127 0.013460 0.007377 0.006128 0.052978 0.000000 9.960370 2400.970 0.177929 0.014563 0.112177 0.124696 0.098615 0.005686 0.052284 0.071060 0.429181 0.267635 0.414857 0.264915 0.180155 0.055257 0.153537 0.058531 0.000187 3.226151 1584.311 0.018155 0.006544 0.057733 0.083667 5.90E

–

30/03/2012)

- 05

Government

Durbin Hannan criterion Schwarz Akaikecriterion info var dependent S.D. dependent Mean Durbin Hannan crit Schwarz Akaikecriterion info var dependent S.D. var dependent Mean share Std. Error Std. 0.000 0.012370 0.013144 0.011429 0.173354 0.000499 0.019359 0.019898 0.019239 0.126261 0.126260 0.128350 0.114693 0.116276 0.115235 0.053 0.053294 0.053632

- 0,2735 0,1211 - 467 - 316 - Watson stat Watson Watson stat Watson

Quinn criter. Quinn Quinn criter. Quinn 0,17

58 erion 0 0

------

t 1.033480 2.880957 1.091335 0.399917 1.088125 0.561219 0.536143 0.305608 var 0.118230 5.094045 0.285769 2.717514 0.562798 3.399181 2.085190 3.617104 2.278329 1.563378

- 0,00021798 Statistic Weighted

0,000547 0,000238

------2.833258 7.143458 7.069982 7.191353 0.006741 2.903329 5.577 5.533125 5.605564 0.015455 5.73E 1.51E 0 0

0.3017 0.0041 0.2754 0.6894 0.2772 0.5749 0.5921 0.7601 0.9059 0.0000 0.7751 0.0067 0.5737 0.0007 0.0374 0.0003 0.0230 0.1183 Prob.

819 - - 05 05

CEU eTD Collection

SBER LKOH GAZP ROSN NVTK URKA SNGS GMKN RTKM VTBR TATN SNGSP TRNFP HYDR MGNT FEES SBERP CHMF MTS NLMK MRKH SIBN IRAO RUALR AFLT

99,99% 15,28% 14,87% 13,88% 0,72% 0,71% 0,71% 0,66% 0,40% 0,07 0,07 0,06 0,05 0,05 0,03 0,03 0,02 0,02 0,02 0,02 0,02 0,01 0,01 0,01 0,01 0,01

0,0001 0,7811 0,5811 0,7948 0,5369 0,1479 0,5117 0,3837 0,7516 0,755 0,576 0,576 0,04 59 0 0 0 0 0 0 0 0 0 0 0 0

0,0000046 0,01437224 0,01051791 0,01176304 0,00386568 0,00105009 0,05325756 0,04938012 0,0079488 0,0020468 0,0880128 0,024764 0,002612 27,06% 0 0 0 0 0 0 0 0 0 0 0 0 6

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