Penny wise and pound foolish: capital gains tax and trading volume on the Zagreb Stock Exchange

TOMISLAV GLOBAN, PhD* TIHANA ŠKRINJARIĆ, PhD*

Article** JEL: E44, F38, G10 https://doi.org/10.3326/pse.44.3.2

* The authors want to thank the anonymous reviewers for insightful comments and suggestions. This paper was supported by the Croatian Science Foundation under project no. 6785. ** Received: June 1, 2019 Accepted: February 9, 2020

Tomislav GLOBAN Faculty of Economics & Business, University of Zagreb, Trg J. F. Kennedyja 6, 10000 Zagreb, Croatia e-mail: [email protected] ORCiD: 0000-0001-5716-2113

Tihana ŠKRINJARIĆ Faculty of Economics & Business, University of Zagreb, Trg J. F. Kennedyja 6, 10000 Zagreb, Croatia e-mail: [email protected] ORCiD: 0000-0002-9310-6853 ------ing stocks for too long (Lei, Zhou and Zhu, 2013; Frazzini, 2006). Tax considera Tax 2013; Frazzini, 2006). ing stocks for too long (Lei, Zhou and Zhu, tions, however, can significantly impact investors’ behaviour and may alter the aforementioned findings. The literature recognizes two hypotheses that dates explain announcement specific around changes significantly volume trading the why interpretation differential The 1995). Wang, He and 1989; Varian, 1986; (Karpoff, the after uncertainty of distribution the on disagree investors that states hypothesis hypothe- disagreement hand, the pre-announcement On the other announcement. prior to the announce induced by disagreement sis is based upon trading activity invest- of a new tax that affects and the implementation The announcement ment. ment on the stock market is one such event. stock markets is the capital key tax that impacts the behaviour of investors on A are a major fac- tax considerations income gains tax. Researchers have shown that For instance, stock market. on the volumes trading of abnormal creation the tor in Dyl (1977) found significant abnormal year-end trading volumes in the United or depreciated appreciated with stocks that had substantially States, especially strategies lock-in of tax existence the for evidence serves as This year. the during strate selling tax-loss and tax, gains capital paying avoid to by investors utilized gies to decrease their overall tax burden, respectively. 1 INTRODUCTION drivers of investing. One of the gains is one of the most important capital Earning striking findings of recent empirical research in the field of finance was that indi- hold on to depreciat stocks too soon and appreciating to sell investors tend vidual Abstract This paper analyses the effects of a recently introduced capital gains tax on the trading volume on the Zagreb Stock Exchange. Using three different methodo- logical approaches – event study methodology, regression discontinuity design and panel regressions – we offer evidence that the introduction gains of the tax capital in January 2016 created abnormally shortly the before tax came high into and force abnormally low volume trading patterns after volume patterns the fact, further decreasing the liquidity of an already poorly liquid market. The differ our as term, longer the and short the both in significant are effects negative ence-in-differences estimations suggest that the average trading volume the that Given period. in pre-tax the vis-à-vis 23% by the decreased years post-tax three revenues collected from this tax are almost negligible, but create considerable under with countries for recommendation policy main our externalities, negative developed and not very liquid stock markets is to use less tax restrictive policies as possible. and attract as many new investors to encourage investment Keywords: capital gains tax, event discontinuity, stock study, regression market, trading volume

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

300 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

301 44 (3) 299-329 (2020) on the zagreb stock exchange - - in Croatia 1 The taxation of income from capital gains in Croatia was introduced not as a new tax form, but rather as The taxation of income from capital gains in Croatia was introduced not as a new tax form, but rather as part of the income tax reform contained in the changes in the Law on income tax (NN 115/16). However, for However, (NN 115/16). tax Law on income the in changes in the contained reform tax income of the part of we will refer to the taxation with the existing literature, and compatibility convenience, the sake of clarity, income from capital gains in Croatia as the “capital gains tax” throughout this paper. 1 This paper analyses whether the introduction of a capital gains tax gains of a capital introduction the whether paper analyses This It is important to be aware of the illiquidity of the Croatian stock market (see market stock Croatian of the of the illiquidity to be aware It is important related literature: Vidović, 2013; Aljinović, 2014) and how important the Minović, liquidity of a market is to (international) 2012; Vidović, Poklepović in returns of expected driver is an important liquidity market investors. Stock and Any great Harvey and Lundblad, 2007). markets such as the Croatian (Bekaert, illiquidity and its unpredictability is a source of market risk (Benić and Franić, (Chuhan, market a in interest investor discourages illiquidity Furthermore, 2008). a mini with prompt transactions enables of a stock market liquidity 1994). Better This paper aims to fill this gap and offers innovative insights into the effects of a new tax comes into investor behaviour before and after the capital gains tax on of new tax policies on trad- examine the implications of the introduction We force. three different stock-level and country-level data. Utilizing ing volume, using both regression discon- – event study methodology (ESM), methodological approaches estima- regressions (including difference-in-differences tinuity design and panel of the capital gains tax createdtions) – we test the hypothesis that the introduction shortly before the tax came into force (toabnormally high trading volume patterns and abnormally low volume patternsbuild-up a portfolio of tax-free securities) We burden on newly acquired securities). after the fact (because of the new tax post-tax is not only short-term, but that it hurt hypothesize that the negative effect market in the longer term as well.the liquidity of an already poorly liquid Studies to date have been rather silent on this specific topic,this in literature the to contribute study to as a case Croatia in reform tax recent so we utilize the affected the trading volume on the Zagreb Stock Exchange (ZSE) before and after before and (ZSE) Exchange Zagreb Stock on the volume the trading affected has focused the existing literature 2016. Most of into force on 1 January the tax came in which a of calendar years of investors at the end of the behaviour on analysis lock- tax of evidence for test to was aim Their force. in already was tax gains capital - appreci significantly stocks certain whether on depending strategies, tax-loss and in and Siravegna,Agostini (see e.g. the calendar year throughout ated or depreciated have dealt with few researchers, however, Very 1998). Jr., 2014; Dyl, 1997; Reese on the the overall trading volume of a capital gains tax affects how the introduction such a tax. that have not previously imposed stock market in countries on prices (Bernstein, 1987), and it is agreed among professionals that mal impact determin in factor important an represents costs, liquidity transaction alongside 1998; Naik and Radcliffe, 1986; Datar, ing stock prices (Amihud and Mendelson, is liquidity that Fernandez (1999) explains 2003). Finally, Pástor and Stambaugh, the “lifeblood” of financial markets, as it enables the smooth operation of econo- but also other market, can disrupt not only a single while erosion of liquidity mies, connected markets worldwide. - - This means that all gains from the shares acquired on 1 January on shares acquired the from gains all that means This 2 2015. Similarly, we hypothesize that the new tax created incen created tax new the that hypothesize we Similarly, 2015.

Initially, the exemption was the exemption to gains from the sales of shares owned for more than three years, granted only Initially, tives not to trade (buy or sell) once the tax came into force because gains from because into force or sell) once the tax came (buy tives not to trade immediately of trade the volume decreasing taxable, became such transactions in the longer term. after the introduction of the tax, but also Our results are robust across various methodologies and model We find Results of the event study based on daily data confirmed ourhypotheses. specifications. into force tax came the shortly before patterns volume high trading abnormally based on fact. Our estimations low volume patterns after the and abnormally - models con Regression discontinuity monthly data point to the same conclusions. firmed a statistically significant break in the slope of the regression line precisely that evidence providing further point when the tax was introduced, at the cut-off dropped period and then sizeably in the pre-tax was increasing the trading volume - sug panel regression estimations when the tax entered into force. In addition, growth in below-average in a 45 percent resulted tax introduction the that gested into force, and 16 percent above-average trading volume the month the tax entered the last month before the tax was introduced. Finally, in volume growth in trading volume in suggest that the average trading estimations difference-in-differences indicat by 23 percent from the pre-tax period, post-tax years decreased the three but also not only short-term, are this tax of introducing consequences the ing that creating important policy implications. nature, of a longer-term on the literature 2 presents a review of as follows. Section The paper is structured 3 describes the trading volume. Section link between taxation and stock market 4 reports while Section analysis, in the utilized and data methodology of the details of validity test the to robustness checks extensive with Section 5 deals results. the offers and analysis the of conclusions main the states section final The results. the policy recommendations. 2016 or later will be taxed if they are sold within two years of their purchase. We We of their purchase. taxed if they are sold within two years 2016 or later will be investors to build for short-term incentives created a policy such that hypothesize 2016 because they would with stocks bought prior to 1 January up their portfolio volume trading increasing if sold quickly, even to taxation subject been not have of end the near but that period was subsequently cut to two years. 2 field. Thisfield. is, toour knowledge, the first empirical study to analyse theimpact of makes which market, stock Croatian on the tax gains capital introduced newly the other all and companies boards of listed investors, makers, to policy relevant it abroad. in the country and stakeholders force into came trading, security includes which tax, gains capital the In Croatia, which surtax, city plus 12% of rate the at taxed are Gains 2016. January 1 on (or other of shares sales the from gains 18%. However, and 0% between ranges financial assets) acquired before 1 January 2016 and/or owned for more than two are exempt. years

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

302 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

303 44 (3) 299-329 (2020) on the zagreb stock exchange - - - ESM these policy changes and found that the introduc these policy changes Other authors found that stocks approaching the date of long-term tax qualifica policies exemption tax and cut tax gains capital implemented have countries Some Ago- stock market. in the domestic depth and liquidity to increase participation, and study case as a reform 2001 tax its and Chile took (2014) Siravegna and stini in the decrease led to a stock price of such policies found that the introduction as such Other types of taxation, effect. tax lock-in the of 15%, due to magnitude but only with the stock market, tax, have also been found to affect transaction volatil market on found was effect significant no while price, stock the to respect - In the literature on the methodology for testing abnormal trading volume, the com bymon approach is to use the event study methodology (ESM). Seminal studies Ajinkya and Jain (1989) and Cready and Ramanan (1991) extended the use of tion of the capital gains tax negatively influenced individual trading, while the found similar Gary et al. (2016) in the opposite direction. 2003 tax cut worked of changes in various on US data, focusing on the effects results in a study based investment. the volume of intercorporate stock market types of tax rates on have gains, capital on taxed be owner cannot their which after date the i.e. tion, Jr. Reese instance, For qualification. of date the around volumes trading abnormal (1998) found that stocks that appreciated prior exhibit increased to trading volume long-term just after tax their qualification date, qualification while stocks that depreciated prior to long-term qualification exhibit these effects just prior to tax their decrease to sellers the enable strategies these because qualification, their returns. burden and increase after-tax have also been studies suggesting that There turnover (Hu, 1998). ity and market Covering 50 years of invest- overstated. the impact of the tax rate changes may be it is not the changes (2013) found that Akindayomi data on US stock markets, ment gains, or the capital the possibility of realizing gains tax rates, but rather in capital behaviour. lack thereof, that impacts stock market investments and investors’ used test-statistics are Widely to the analysis of stock returns and trading volume. (1996) who imparted greater power to Wasley those developed by Campbell and (1992) explains that trading volume is a useful variable to use in Yadav the tests. event study methodology. This is due to this volume reflecting the the different 2 LITERATURE REVIEW 2 LITERATURE respect series with and return of volumes reactions observes usually literature The to Thus, tax the introductions firstor group changes. of papers in this review sec- gains capital Changes in focuses on such reactions. of research that tion consists As shown by stock market. volume on the the trading found to affect tax rates are and turn- volume trading in increases to were connected cuts tax (1982), Slemrod of on the volume no effect Exchange. However, Stock York on the New over rates 1990). 1987 (Henderson, in increase tax gains capital the was found after trading gains tax fairly capital advanced economies that introduced a Japan was one of the and Ono underwent a tax cut reform. Hayashida (in 1989) and subsequently late of effects (2010) analysed the - - . This debate 3 See, for example Jin (2006) – it cannot be argued that increasing capital gains tax rates will slow down trad- will rates tax gains capital increasing that argued be cannot Jin (2006) – it for example See, has been ongoing for a long time (see Fenberg and Summers, 1989). has been ongoing for a long time (see Fenberg Finally, we briefly mention the idea of speculative investing because oneof the The idea of gains tax could be to discourage such behaviour. ideas of a capital Kreps, 1978), but Harrison and 1977; new (Miller, is not behaviour speculative Some of the 2019). Weitzel, and (Janssen, Füllbrunn interesting the topic is still of investors (Scheinkman beliefs heterogeneous the include explanations main sta- and Xiong, 2003; Hong, Scheinkman and Xiong, 2006). In his long study on if the primary purpose for (1989) concludes that Repetti the stock market, bilizing curb speculation, it is gains is to of preferences for long-term capital re-enactment not advisable to do so as it would decrease societal welfare. ing on a stock market; whereas Auten (1999) states that lower and middle income taxpayers are losers in the losers in the are taxpayers income lower and middle Auten (1999) states that whereas ing on a stock market; or sus- their introduction rates, of tax amount to the respect on pros and cons with literature long run. Other (2013). Akindayomi pension can be found in 3 impacts new information arriving on the market makes. Individual investors are investors Individual makes. on the market arriving new information impacts on the mar expectations different to due differently information new by affected Thus, the trading etc. information asymmetry, adjustments to taxes, ket, clientele information is interpreted. consensus when new the lack of a volume indicates increases the trading volume studies found that ESM approach, several Using the of such as changes to other announcements, event day with respect around the group of papers is the This and dividend announcements. market index structure utilizes the ESM approach, which overview, this literature second group within (1986) Vermaelen and Lakonishok instance, For issues. tax focus on not does but sample the by dividing days, around ex-dividend volume trading focused on the the of ones. Stocks non-taxable and distributions taxable for subsamples into 1970-1981, with period in the were analysed company Therapeutics CRISPR Authors found sig- dividends. stock and splits for stock 2500 ex-dates than more Vijh and Bajaj days. ex-dividend the after and before volume of increases nificant day announcement dividend around volume in increase the (1995) found not only more Other studies focus returns as well. and volatility but in (due to tax trading), stock market index com- and acquisitions; mergers on dividend announcements, or Chaudary 2011; Gregoriou, 2002; Kim, and Rui Xu, (see etc. changes, position on stock returns the effects evaluate and Mirza, 2017). Some authors empirically are gains taxes are put in place or capital and investor demand for stocks when Blouin, Raedy and Shackefold, 2000). changed over time (Shackefold, 2000; the intro- to be drawn. Firstly, allows several conclusions The existing literature on the volatilities returns and and affects volume trading hurts the of taxes duction 2013; Blouin, Raedy and Shackefold, Akindayomi, majority of stock markets (see Zhang, and Shackelford Dai, 1992; and Stebbins, Amoaku-Adu, Rashid 2003; taxa of problem the solve how to consensus on clear no is there Secondly, 2013). tion, in terms of completely abolishing taxes or finding some combination of tax brackets according to the type of investor and other classifications

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

304 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

305 44 (3) 299-329 (2020) on the zagreb stock exchange - - - 21days, with 10 days prior and 10 days after the event day. after the event day. 21days, with 10 days prior and 10 days We also employ two additional estimation methods – regression discontinuity – methods estimation two additional employ also We estima which include the difference-in-differences design and panel regressions, 3 DATA AND METHODOLOGY 3 DATA DESCRIPTION 3.1 DATA stocks data for 45 daily trading volume analysis, of empirical For the purpose stocks included The full list of website. from the ZSE (2019) collected have been total stocks in terms of The most liquid A1. Table in Appendix in the is reported analysis. for the selected been have in 2018 transactions of and number turnover the upon depending study differ this used in frequency span and data time The data daily the utilizes analysis the of part first the Specifically, used. methodology January 2 span from time the we used Here, study methodology. event for the 2016. 2015 until 1 February The pre-event window for the event study estimation of the market model of trad- model market the of estimation study event the window for pre-event The 2015, with 2015 until 10 December ing volumes is chosen to be from 2 January (1997) recommends MacKinlay series. for every volume observations 236 daily depending upon data avail estimation, around 250 days for the pre-event window sub-periods can 1997, several in market stock Croatian of the the beginning Since phase until 2003, which saw the market was in a stagnant be distinguished. Firstly, the start of the trend of an increasing growth of the official stock market index ended with the crisis all That transactions. CROBEX, as well as of the number of The fast pre-crisis growth was due to the IPOs of several big companies of 2008. The market recovery Group, Ingra, Magma and Optima. Atlantic Ina, such as HT, has been, the whole market in 2010. Ever since, and ended was very limited, and stagnating volume low trading phase, with a stagnant in speaking, broadly market index values (see Graphs 1 and 2). tions. These estimations are based on monthly data to further test whether the are based on monthly data to These estimations tions. than volume trading on consequences longer-term also had tax of the introduction time longer covers a period estimation Thus, the ESM results. by the implied those making the pre- and runs from 2013:M01 to 2019:M01, period pre- and post-tax and post-event periods of similar size. Thus, short. The event-window length is usually topic of interest. and the ability we select the length of methodol on the regression discontinuity In later stages of our analysis, we focus fre- to monthly data the daily ogy and panel regressions. Here, we transformed descriptive 2019:M01. Detailed to 2013:M01 from span time the with quencies, Appendix in frequencies are shown in the both for monthly and daily statistics A2. Table

6,000 5,000 4,000 3,000 2,000 1,000 0 1-Apr-19

1-Apr-18

1-Apr-17

1-Apr-16

1-Apr-15

1-Apr-14 1-Apr-13

CROBEX

1-Apr-12

1-Apr-11 1-Apr-10

Return

1-Apr-09

1-Apr-08

1-Apr-07

1-Apr-06 1-Apr-05

Liquidity is one of the greatest problems on ZSE today (see Vidović,

4 1 1-Apr-04 raph 0.20 0.15 0.10 0.05 0.00 For a more detailed discussion on the link between legislation and the composition of investors on ZSE see composition and the legislation between link discussion on the For a more detailed -0.05 -0.10 -0.15 2013; or Škrinjarić, 2018 for details), which is also evident from Graph 2. 2013; or Škrinjarić, 2018 for details), which Grubišić Seba (2017). 4 Source: ZSE. Source: Legislative analysis regarding the trading on ZSE is detailed in Grubišić development the enhance not did Croatia in legislation the that argues who (2017), Šeba the from shareholders of small out crowding the in resulted instead but of ZSE, market. G ZSE axis) on series (left return axis) and (right index value Market

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

306 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

307 44 (3) 299-329 (2020) on the zagreb stock exchange

-

23-Feb-19

23-May-18

23-Aug-17

23-Nov-16

23-Feb-16

23-May-15

23-Aug-14

23-Nov-13

23-Feb-13 23-May-12

Trading volume

23-Aug-11

23-Nov-10

23-Feb-10

23-May-09

23-Aug-08 23-Nov-07 2 0 50 250 200 150 100 raph Graph 3 reports the yearly trading volume on ZSE, which shows a 15.1 percent shows a which ZSE, on volume trading yearly the reports Graph 3 intro- the is that Our hypothesis previous year. to the respect in 2016 with decline 2016 played a role in this decline, gains tax from 1 January duction of the capital that the trading Graph 3 also indicates which we test in the following sections. of over 30 per growth rate with a yearly in 2017 bounced back strongly volume Source: ZSE. Source: we compared average daily volumes in theBefore formally testing our hypotheses, It turned out average in the 10 days after. 10 days prior to the event day with the the in average trading volume. Moreover, that 34 out of 45 stocks marked a decline were lower than in December 2015 foraverage monthly volumes in January 2016 thein stocks 37 for decreased volume monthly cumulative the while stocks, 36 same period. Descriptive analysis suggests that the tax may have influenced the trading volumes on ZSE, which we test more formally in the following sections. cent. However, this was primarily the result of a major fire sale ofcent. stocksHowever, of com- into a major which had fallen Agrokor, food concern to the large panies connected half of 2017. financial crisis that escalated in the first G in mil HRK on ZSE, volume trading Total 0 40 20 -20 -40 -60 -80 2018 the outstand- i,t S 2017 ) (1) ) (2) t of stock i, 2016 ) is estimated as follows: i,t t I 100 + ε M,t 2015 V i , it S + b 0.000255 i + 2014 , it n ) = E(a t |I i,t 2013 = log ( i,t E(V V 2012 t as: 2011 denotes the number of shares traded at date the number of shares traded denotes i,t 2010 3 n 6 5 4 3 2 1 0 raph where Source: ZSE. Source: METHODOLOGY STUDY 3.2 EVENT established in literature, we give only aSince the event study methodology is well Olson and Peare (2007), Bartholdy, brief overview following MacKinlay (1997), return, (1996). ESM is usually used to show how stock Wasley and Campbell and economic, political, social or other different volatility and trading volume reacted to ESM is usually applied over short-term horizons (several days events. Moreover, actual returns, vola- The basic idea is to compare the prior to and after the event). occurred in the absence of the event.tilities or volumes to those that would have trading the on effect significant a have not did event the that is hypothesis null The volume relative log-transformed the define (1996) Wasley and Campbell volume. for stock i at date G total trading volume change on (right ZSE (left axis, in billions), percentage Yearly axis, in %)

. Value of 0.000255 is added so that the value of 0.000255 is added so that Value ing shares of the i-th stock at date t. under the log is not zero if in some days there was no trading, as suggested by trading volume abnormal The market model of (1996). Wasley and Campbell (trading volume conditioned to the information set

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

308 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

309 44 (3) 299-329 (2020) on the zagreb stock exchange (4) ) holds. It is ) holds. It 2 i , calculated as the , calculated , it N (0, σ V 1 ~ = i M i -1}) to avoid any effects of any effects -1}) to avoid å is a deterministic function of function is a deterministic i start 1 M τ (5)    (3) ) τ = ~ N(0,1) |I τ M,t < ≥ , in the event window, defined as: , in the event window, τ tc

tc

. We estimate the RD model with the estimate We i. if if {1, 2, ..., – E(V ϵ τ - 0 1 ii    k Ek () ( ( )) = = V sk 1 τ i = N ῡ i T } is the index referring to the time span of the event span of the time to the referring index } is the (0,1), under the null hypothesis. ~ N(0,1), under the null å end 1 t N v t, so that: ϵ {0,1}, on unit i () t T v , … ,τ var event , … τ start τ is the market volume measure, V measure, volume market is the ) of the treatment (the introduction of the capital gains tax), represented of the capital (the introduction ) of the treatment i ) is the standard deviation of the port- of the is the rank of the i-th stock, and s(k) is the standard deviation M,t

i V k τ ϵ { the event itself on the results. The usual assumption of ε assumption usual The results. the on itself event the

the running time variable folio mean abnormal rank. Corrado (1989), and Campbell and Wasley (1996) Wasley and (1989), and Campbell rank. Corrado folio mean abnormal abnormal tests are more powerful for detecting nonparametric have shown that upon the of these tests is that they do not depend advantage Another performance. as the number of stocks in the test grows, the test However, assumption. normality tests to a normal unit distribution. Other nonparametric in (4) converges statistic signed rank test, etc. (for more details Wilcoxon sign test, the include the binomial see Sheskin, 1997). window. The test statistic is the ratio of the average abnormal volume and the is the ratio of the average abnormal statistic The test window. standard deviation, sharp design, which means that the assignment of T assignment the that sharp design, which means assumed that the volume variable would behave as in (2) in the absence of the (2) in the absence behave as in would the volume variable assumed that volume expected the define would (2) in parameters that assumed is it Next, event. These forecasts (2). as well, thus forecasts are made with model in the event window the abnormal volume, ῡ are used to calculate We estimate the regression discontinuity (RD) the regression discontinuity data in the estimate model, designing the We potential outcomes framework (Rubin, 1974). The objective is to find the causal (C effect 3.3 REGRESSION DISCONTINUITY DESIGN 3.3 REGRESSION DISCONTINUITY where where where

Another approach to testing the null hypothesis is to use a nonparametric test, in test, is to use a nonparametric Another approach to testing the null hypothesis rank rank from the expected of the stocks’ deviation of the mean which the ratio of the port- by the standard deviation is divided the size of the volume) (regarding folio mean abnormal rank:

by the binary indicator average trading volume of stocks contained in the market index. The estimation of estimation The index. market in the contained of stocks volume trading average window (t in the pre-event (2) is done where - - to (6) (7) i,t is the

i,t stdev tax + i,t i is the error term. i,t aftertax e 4 tc + β i,t pretax 3 (0) i i Z + β i,t is the dummy variable for the last month is the dummy variable (1) – tax ¯- i 2 tc i,t , consists of the following variables: following the of consists , = Z i,t + β i (8) X C i,t i,t–1 ) + e i (equals 1 for each January, 0 otherwise) to control for 0 otherwise) to control January, 1 for each (equals ( i,t volume 1 + δ i,t to control for the monthly return of each stock; and the of each return for the monthly to control (0) the potential outcome (trading volume) under control outcome (trading volume) under (0) the potential

i i,t ) X 5 ( is the dummy variable that splits the sample into the period before period into the sample the splits that variable dummy is the is the average trade volume of stock i in period t, is the average trade volume of stock + β' = α + β  [1 0|]lim[(1)|]lim[(0)|] i,t i,t return i,t represents the cross-section fixed effects, and represents the cross-section fixed effects, i = - == =- = iii (1) denotes the potential outcome (trading volume) of unit i under treat outcome (1) denotes the potential = 1) and Z

i i CEZ Z tc EZtc EZtc volume is the cut-off point set at January 2016 – the month in which the capital which the in – the month 2016 set at January point cut-off c is the Z aftertax volume = 0). With the RD design, we estimate the average causal effect of treatment at of treatment the average causal effect estimate the RD design, we With = 0).

i dummy variable january variable dummy before the introduction of the capital gains tax (equals 1 for 2015:M12, 0 other 0 2015:M12, for 1 (equals tax gains capital the of introduction the before wise), control for the volatility of stock prices as an important determinant of trading of stock prices as an important determinant control for the volatility of daily volume on the stock market, measured as the monthly standard deviation stock prices; and after the introduction of the tax (equals 1 for the period after 2016:M01, 0 of the tax (equals and after the introduction otherwise), δ The vector of control variables, of control vector The dummy variable for the month when the capital gains tax was introduced (equals was introduced tax gains capital the when month the for variable dummy 1 for 2016:M01, 0 otherwise), pretax the cut-off point, t = c: the cut-off (T 3.4 PANEL REGRESSIONS 3.4 PANEL a estimate We panel regressions. approach utilizes Our third methodological fixed effects: dynamic panel model with cross-section where where 2016 in January stocks recorded of all volumes Trading tax was introduced. gains of the same while the volumes group, treatment considered as the or later are in the control group. 2016 are put period before January stocks in the as: is defined effect The causal where the possible existence of the so-called January effect on the Zagreb Stock Zagreb on the effect January so-called of the existence possible the anom- of calendar analysis for the 2011 Diaconasu, and e.g. Stoica (see, Exchange Central and Eastern European stock markets). alies on emerging for each volume trading daily for average data we use monthly As in RD design, month from 2013:M01 to 2019:M01, for the same 45 company stocks as before. where ment (T We use monthly growth rates in average daily trading volume for each month volume for each trading daily average in growth rates use monthly We same 45 company stocks listed on the (from 2013:M01 to 2019:M01) for the Appendix. A1 in the Table Zagreb Stock Exchange and denoted in

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

310 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

311 44 (3) 299-329 (2020) on the zagreb stock exchange 10 ence 5 0 , with the respective confidence intervals τ ). 5 -5 4 raph 0.0 0.5 1.0 The “0” day remains 31 Dec 2015, as stocks bought from 1 Jan 2016 were subjected to taxation (if they The “0” day remains 31 Dec 2015, as stocks bought from 1 Jan 2016 were subjected to taxation (if they -1.5 -1.0 -0.5 It can be seen that the abnormal trading volume began before the event day, which day, before the event began trading volume the abnormal It can be seen that The in the last few days of 2015. trading their investors increased that indicates abnormally high trading volume is statistically significant.We interpret this as evidence that the introduction of the tax had a as accumulate to incentives had investors because ZSE, on trading and behaviour significanteffect on investors’ respect to their invest- in their portfolio as possible, with many tax-free securities ing strategies. (CI) at the 95% confidence level. The results are shown in Graph 4, where day 0 before the last trading day 2015 (the to 31 December on the x-axis corresponds into force capital gains tax entered 5 Source: Authors’ estimations. Authors’ Source: Abnormal volume (full line) with 95% CIs (dashed lines), classic infer Abnormal volume (full line) with 95% CIs G 4 RESULTS DATA DAILY WITH 4.1 ESTIMATIONS first estimateWe the event study model withthe pre-event window spanning the (2). Next, equation 2015 to estimate 10 December 2 January 2015 to period from volumes, ῡ the abnormal we calculate were sold within 3 years after purchase). Thus, the zero day is the last “neutral” day when compared to +1 +1 to compared when day “neutral” last the is day zero the Thus, purchase). after years 3 within sold were day which is now in Jan 2016. 10 ence and five. This five. and 6 5 0 -5 5 -inference for the event study estimator, we re-estimated equation (2) with equation we re-estimated study estimator, for the event T-inference raph 1.0 0.5 0.0 Although it seems that on day two the zero value is included in the confidence intervals, the upper interval intervals, the confidence in the is included zero value on day two the seems that Although it -0.5 -1.0 -1.5 value is -0.004, which excludes the zero value. 6 Source: Authors’ estimations. Authors’ Source: sign test Wilcoxon the nonparametric equation (2) was using estimated Finally, previous the to when compared wide are case this CIs in the Although (Graph 6). day fifth the and day event the before days several regarding conclusions the ones, post-event are the same: we detect statistically significant abnormal trading Abnormal volume (full line) with 95% CIs (dashed lines), bootstrap infer Abnormal volume (full line) with 95% CIs G In addition, we observe a strong negative response of the trading volume in the volume of the trading response a strong negative observe we In addition, two on days responses negative statistically with period, post-event suggests that the introduction of the tax created disincentives to trading because trading to disincentives created tax the of introduction the suggests that subject to 1 January 2016 were acquired after gains from securities all capital of the market. the liquidity taxation, hurting with the clas- 4, which were estimated reported on Graph to the results In addition sic 5 shows the result of the Graph estimator. for the same the bootstrap approach done replacement and sampling with with 1000 replications bootstrap approach, is chosen because it corrects for This approach observation. within the units of of the distribution possible non-normal due to the results the possible biases in results The for details). 2014 Westfall, and (see Hein correlation and serial data and pre- the in volume trading the to respect with conclusions same the indicate post-event period.

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

312 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

313 44 (3) 299-329 (2020) on the zagreb stock exchange - 10 5 0 -5 6 raph 0.0 0.5 1.0 -1.5 -1.0 -0.5 Two additional nonparametric tests were performed, the results of which are tests were performed, the results nonparametric additional Two normal of the assumptions respective sign tests with the The 1. Table in reported period. were performed for every day in the event distribution and exact binomial before of a variable changes in the value Since these tests are useful for detecting conduct this test by comparing the abnor and after the treatment, we additionally Source: Authors’ estimations. Authors’ Source: mal volume stocks’ rank with the median rank. Results indicate significant effects effects significant indicate Results rank. median the with rank stocks’ volume mal in 0, which is also evidence day and after before both of the tax introduction tests particular these that note to is important hypothesis. It of our research favour is positive volume trading on the impact the whether do not answer the question because their construction is based The test values are all positive or negative. upon sample proportions. G inference lines), Wilcoxon 95% CIs (dashed volume (full line) with Abnormal volume on ZSE. The greatest effects were found on the day before the event and the event day before on the were found effects The greatest on ZSE. volume 6). 4, 5 and 0 (Graphs on day - (0.243) (0.144) (0.019) (0.079) (0.040) (0.040) (0.079) (0.079) (0.019) (0.019) (0.019) (0.001) (0.008) (0.008) (0.008) (0.008) (0.008) (0.001) (0.008) (0.008) (0.008)

*** *** *** * *** *** ** ** * * *** ** ** *** *** ** *** *** ** 28 29 33 30 30 33 32 35 33 32 33 33 32 35 33 33 30 33 31 31 32 Exact binomial Sign test (0.243) (0.145) (0.009) (0.080) (0.001) (0.009) (0.009) (0.009) (0.001) (0.009) (0.009) (0.080) (0.009) (0.041) (0.041) (0.080) (0.009) (0.020) (0.020) (0.020) (0.020)

*** ** ** * ** *** *** ** *** *** ** *** *** *** * *** * *** ** 1.75 2.63 1.17 3.21 2.63 2.04 1.75 2.63 2.33 3.21 2.63 2.63 1.46 1.75 2.63 2.04 2.33 2.63 2.33 2.63 2.33 Normal approximation 4 1 6 9 2 3 5 7 8 0 1 -9 -8 -6 -5 -2 -7 -4 -3 -1 10 Day -10 able Note: ***p<0.01, **p<0.05, *p<0.1. p-values in parentheses. Note: ***p<0.01, **p<0.05, *p<0.1. p-values estimations. Authors’ Source: on ZSE shortly before of the trading volume the increase The results indicating its coming right after gains tax, and the decrease of the capital the introduction Bajaj (1986), Vermaelen and Lakonishok in findings the with line in are force, into with the theory They are also in line (1995), and Xu, Rui and Kim (2002). Vijh and pre-announce the (1995), i.e. Wang He and (1989), and Varian (1986), Karpoff in ment disagreement hypothesis, because the abnormal trading volume patterns volume trading the abnormal hypothesis, because disagreement ment although investors that, This hypothesis says day. were found prior to the event (in this case the introduction of an announcement can agree upon the implications too high, so that the disagreement is sometimes uncertainty of a tax), the pre-event tests provide nonparametric volume. However, causes the increase in the trading evidence in favour of a differential interpretation hypothesis (significant results (1991a; 1991b) state, the Verrecchia after the event day) as well, but, as Kim and asymmetry due to the information exclusive, two hypotheses are not mutually before the event day. T tests results Nonparametric

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

314 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

315 44 (3) 299-329 (2020) on the zagreb stock exchange 2019m1 2019m1 2018m1 2018m1 2017m1 2017m1 Polynomial fit of order 3 Polynomial fit of order 1 2016m1 2016m1 2015m1 2015m1 2014m1 2014m1 Sample average within bin Sample average within bin (b) Polynomial fit of order 3 (b) Polynomial fit of order (d) Polynomial fit of order 1 (d) Polynomial fit of order 2013m1 2013m1 1 0.5 0 1 0.5 0 –0.5 –0.5 2019m1 2019m1 2018m1 2018m1 2017m1 Polynomial fit of order 2 2017m1 Polynomial fit of order 4 2016m1 2016m1 2015m1 2015m1 2014m1 2014m1 Sample average within bin Sample average within bin 7 (c) Polynomial fit of order 2 (c) Polynomial fit of order (a) Polynomial fit of order 4 (a) Polynomial fit of order REGRESSION DISCONTINUITY DESIGN DISCONTINUITY REGRESSION 2013m1 2013m1 raph 0.6 0.4 0.2 0 0.6 0.4 0.2 0 –0.2 –0.4 –0.2 –0.4 Table 2 Table reports the tests for the statistical significance of these estimations. The discontinuity in the trading volume is confirmed acrossorders polynomial and for all estimator, polynomial local bias-corrected using the all polynomial orders Right after the cut-off other than order 1 using the robust standard-error estimator. volume in the trading was a reduction of the tax), there point (the introduction is This order. polynomial the on depending 72%, and 41% between of rate growth Source: Authors’ estimations. Authors’ Source: G dis- regression function fits the ofRegression polynomials from of various orders – 2019:M01) continuity model (2013:M01 4.2 ESTIMATIONS WITH MONTHLY DATA MONTHLY WITH 4.2 ESTIMATIONS 4.2.1 Graph 7 plots the regression function fits of polynomials of various orders,with default The introduced. first was tax the when 2016, January at set date cut-off the type of estimation in Stata 15 software is the polynomial fit of order 4 (panel a of Graph 7), which shows a significant break in the slope of the regression line pre- cisely at the cut-off point. It confirms that the trading volume increasedThis force. into entered tax dropped when the sizably and then period pre-tax in the probably reflects the increased incentives for the accumulation the tax once to trade of incentives period, and then the lack in the pre-tax securities of non-taxable orders, various polynomial Other panels of Graph 7, showing was introduced. confirm the same narrative. * (4) p=1 3,096 1,574 1,522 (0.169) -0.251 (0.169) -0.309 -0.309 (0.196) represents i,t * * * (3) p=2 3,096 1,574 1,522 -0.411 -0.411 (0.219) (0.248) (0.219) -0.362 * ** ** (2) p=3 1,574 1,522 3,096 (0.249) (0.276) (0.249) -0.505 -0.536 -0.536 ** ** ** (1) p=4 1,574 1,522 3,096 (0.320) (0.320) (0.350) -0.667 -0.719 -0.719 2 PANEL REGRESSIONS PANEL able Estimator Conventional Polynomial order Robust std. errors Left of the cut-off Right of the cut-off Bias-corrected of obs. Number Total 4.2.2 with cross-section weights the models using panel EGLS estimator estimated We 3), but also the models without the weights (models 4-6 in Table (models 1-3 in of models where volume various iterations estimated We 3). Table Note: ***p<0.01, **p<0.05, *p<0.1. Standard errors in parentheses. errors Note: ***p<0.01, **p<0.05, *p<0.1. Standard estimations. Authors’ Source: T Sharp regression discontinuity estimated coefficientsregression using local polynomial measured by taking a difference in the mean values to the left of the cut-off point cut-off left of the to the mean values in the a difference by taking measured point (after of the cut-off to the right values the mean 2016) and January (before approximately bandwidth, includes the called This neighbourhood, January 2016). point. of the cut-off on each side 750 observations monthly growth rates of the average trading volume, as well as the logarithm of logarithm as the as well volume, trading average of the rates growth monthly kunas Croatian in volume trading non-transformed and volume, trading the (HRK), respectively.

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

316 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

317 44 (3) 299-329 (2020) on the zagreb stock exchange * * *** (6) 0.249 0.262 0.069 3,019 (0.037) -3,060.3 (7,654.1) 11,519.3 34,853.7 in HRK (5,914.17) (36,126.9) (23,000.9) (20,793.4) -19,739.5 -26,445.0 281,382 -32,576.2 (25,462.2) (17,940.9) ** *** *** *** *** (5) log 3,019 0.708 0.713 0.104 0.444 0.160 0.039 6.395 (0.113) -0.063 (0.049) (0.122) -0.489 (0.018) (0.281) (0.024) (0.033) -0.006 (0.010) * ** *** *** *** (4) rate 3,005 Panel least squares (no weights) Panel least 0.192 0.054 0.206 0.009 0.144 0.139 0.018 growth (0.011) (0.055) (0.102) (0.022) (0.094) (0.040) (0.022) -0.063 (0.047) -0.497 -0.442 *** *** *** *** (3) 313.56 232.0 (813.42) (574.83) 0.434 0.443 1,252.41 0.284 5,987.7 in HRK 3,019 (3,390.7) (8,840.2) (8,692.0) (8,468.0) (2,244.3) (0.029) 12,781.6 -27,961.4 220,956 *** *** *** *** *** (2) log 3,019 0.770 6.386 0.774 0.073 0.049 0.443 0.188 0.004 (0.113) (0.113) -0.078 (0.049) (0.122) -0.458 (0.276) (0.024) (0.033) (0.019) *** *** *** *** *** (1) rate 3,005 growth 0.032 0.190 0.061 0.204 0.102* 0.164 (0.011) -0.062 (0.047) -0.446 -0.001 (0.053) (0.104) (0.021) (0.038) (0.018) (0.097) -0.437 Panel EGLS (cross-section weights) Panel EGLS 3 able No. of observ. stdev Adj. R-sq. constant return tax Dependent Dependent variable (volume) R-squared aftertax january pretax volume(-1) The monetary effect of the tax on the trading volume is not negligible. According is not negligible. volume trading on the tax of the effect monetary The by HRK 27,961 per stock on average decreased volume (3), the trading model to There were 19 trading days in January 2016, per trading day in January 2016. in tax of the effect negative by 45 stocks, suggests an average multiplied which, the amount of HRK 24 million in trading volume that month alone. After controlling for all other variables, the benchmark model (1) suggests that the that (1) suggests model benchmark the variables, other for all controlling After average decrease in the trading volume tax introduction resulted in a 45 percent month. Results also suggest a 16 percent day that growth rate per stock per trading the reflecting likely 2015, December in rate growth volume trading the in increase These portfolios. in their securities tax-free for investors to accumulate incentives findings confirm the results of the event study methodology and the regression discontinuity model presented earlier. The results reported in Table 3 suggest a statistically significant negative effect of effect negative significant statistically a suggest 3 Table in reported results The a tax) and in January 2016 (variable tax on trading volume of the introduction the entered tax the before month last the 2015, December in effect positive significant across almost all specifications. into force (variable pretax). Results hold Notes: ***p<0.01, **p<0.05, *p<0.1. Standard errors in parentheses. errors Notes: ***p<0.01, **p<0.05, *p<0.1. Standard estimations. Authors’ Source: T (2013:M01-2019:M01) estimations regression of panel Results - * ** *** *** (3) 0.356 0.407 0.045 0.032 0.218 -0.011 (0.147) -0.270 (0.123) (0.035) (0.052) (0.091) (0.141) (0.161) 17.513 ** * *** *** (2) 0.345 0.012 0.009 0.277 0.201 (0.111) (0.110) -0.233 (0.090) (0.026) -0.021 (0.042) (0.069) (0.099) 17.683 * (1) 0.110 -0.663 (0.343) 4 able Stock market volatility VARIABLE (volume) VARIABLE Croatia post-2015:M12 Interest rate Growth in money supply Exchange rate volatility Constant R-squared Stock market return Notes: Treated observations are trading volumes of Croatian stocks after the capital gains tax was tax gains capital the after stocks Croatian of volumes trading are observations Treated Notes: Romania. and Poland, Hungary, Republic, Czech Bulgaria, of consists group Control introduced. Standard crisis. Agrokor the of effect the exclude to 2016:M12 after period the excludes (3) Model ***p<0.01, **p<0.05, *p<0.1 in parentheses. errors estimations. Authors’ Source: T results estimation Difference-in-Differences We also estimate panel regressions in a difference-in-differences framework using framework in a difference-in-differences panel regressions estimate also We country-level instead of stock-level data to find causal effects of the tax on the trading volume with a longer-term perspective. firstWe estimate a naïve differ on the trading volume data on the overall using parameter ence-in-differences from 2016:M01 period the group, and treated as the stock market Croatian of other non- control group consists period. Our the post-treatment onwards as Czech – Bulgaria, Eastern Europe and Central EU members from eurozone 4, Table in The results are reported Poland, and Romania. Hungary, Republic, As model can (1). be seen, the naïve parameter difference-in-differences is nega- tive and statistically significant for the Croatian trading volume in the three years of the tax. 2015, confirming the negative effect following December a also estimated we causal effects, negative sense of the size of the a better get To cross-country control vari- model including difference-in-differences conditional rates, growth in interest market returns and volatility, ables such as the stock difference- The 4). Table 2 in (model volatility rate and exchange supply, money for Croatia indicator an between interaction on the is that parameter in-differences Model (3) is the same as (2), 2015. for the period post-December and an indicator Agrokor of the possibility the exclude to 2016:M12 after period the excludes but the results. crisis affecting

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

318 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

319 44 (3) 299-329 (2020) on the zagreb stock exchange 2017m1 2017m1 m7 2016m1 2016m1 Polynomial fit of order 3 Polynomial fit of order 1 m7 2015m1 2015m1 m7 2014m1 2014m1 m7 Sample average within bin Sample average within bin (b) Polynomial fit of order 3 (b) Polynomial fit of order (d) Polynomial fit of order 1 (d) Polynomial fit of order 2013m1 2013m1 0 0.5 0.5 0 –0.5 –0.5 2017m1 2017m1 m7 m7 2016m1 2016m1 Polynomial fit of order 4 Polynomial fit of order 2 m7 m7 2015m1 2015m1 m7 m7 2014m1 2014m1 m7 m7 Sample average within bin Sample average within bin 8 (c) Polynomial fit of order 2 (c) Polynomial fit of order (a) Polynomial fit of order 4 (a) Polynomial fit of order 2013m1 2013m1 raph 0 0.5 0 0.5 –0.5 –0.5 Source: Authors’ estimations. Authors’ Source: Regression function fits of polynomials of various orders from the regression dis- regression function fits the ofRegression polynomials from of various orders continuity model (2013:M01 – 2016:M12) G 5 ROBUSTNESS CHECKS Agrokor crisis, that the on the possibility focuses mainly Our robustness check which started in the first half of 2017,could have affected the results. Thus, we Graph 8 but with the data ending in 2016:M12. the same RD model estimated period the change we when even robust remain conclusions main the that confirms of analysis, with statistically significant breaks in the slope of the regression line point. right at the cut-off Both Both model (2) and model (3) indicate a statistically significant negative long- - trad that the average suggest Results volume. trading tax on the of the effect term 2) when by 23 percent (model years decreased in the three post-tax ing volume compared to the pre-tax period, and decreased 27 percent in the first year follow- intro- of consequences the that indicates This respectively. 3), (model tax the ing in (captured short-term not only are on ZSE volume trading on the tax this ducing nature, but also of a longer-term coming into force), and after the tax days before policy implications. which carries important * ** ** *** * HRK (12) 2,065 3,059.2 0.249 0.268 0.089 in HRK 32,604.4 (0.047) 268,943 60,357.4 -36,844.9 (65,500.3) (19,617.5) (13,406.9) (44,069.2) (23,534.1) (16,564.0) -34,607.8 -13,823.8 (13,840.0) *** ** ** * *** *** *** log (11) 0.710 0.717 0.156 0.032 0.045 0.122 7.069 0.377 0.037 2,065 -0.510 (0.061) (0.059) (0.033) (0.016) (0.021) (0.066) (0.314) (0.027) *** *** ** *** *** *** *** rate (10) 0.206 0.226 0.150 0.082 0.058 0.205 0.066 2,060 Panel least squares (no weights) Panel least squares (no -0.453 -0.176 -0.554 (0.028) (0.041) (0.017) (0.024) (0.047) (0.058) (0.024) (0.072) growth ** ** *** *** *** *** *** (9) 2,065 0.474 0.487 0.221 2,165.3 3,847.8 in HRK 7,020.49 (0.026) 237,926 (8,616.2) (2,847.7) (5,794.3) (4,069.4) (1,175.51) (6,238.3) (1,386.9) 13,091.4 3,699.25 -32,218.6 *** *** *** *** *** *** (8) log 2,065 0.792 0.057 0.078 0.101 7.084 0.372 0.182 0.797 (0.068) -0.451 -0.028 (0.059) (0.016) (0.022) (0.292) (0.025) (0.061) (0.033) dummy variable are in line with Lakonishok and with Lakonishok in line are variable january dummy *** *** *** *** *** *** *** (7) rate 2,060 0.210 0.084 0.095 0.169 0.056 0.176 0.229 growth (0.017) (0.026) (0.065) (0.058) (0.021) (0.054) (0.040) -0.490 (0.067) -0.239 -0.444 Panel EGLS (cross-section weights) Panel EGLS (cross-section 5 able No. of observ. Adj. R-squared return Dependent variable (volume) tax stdev pretax aftertax january R-squared constant Volume (-1) Volume 27 million on the trading volume in that month alone. 27 million on the trading volume in that of the values Positive Atiase and Bamber (1994) and Atiase and Gift (1991), Ajinkya, Smidt (1984), Jan- in volume trading who find greater 1999) (1997; Stober and Barron Bamber, stock prices as well. which affects uary, Agrokor crisis not the affecting results The was also confirmed in our difference- the affect not did crisis Agrokor the that confirmed also estimations in-differences 4. Table results, as already shown in Notes: ***p<0.01, **p<0.05, *p<0.1. Standard errors in parentheses. errors Notes: ***p<0.01, **p<0.05, *p<0.1. Standard estimations. Authors’ Source: trading the in decrease average percent 49 suggests a (7) model benchmark The of effect monetary in January 2016, with the negative growth rate volume T estimations (2013:M01-2016:M12) panel regression Results of We also estimated panel regression models with the sample period ending in in ending period sample with the models regression panel also estimated We affected crisis Agrokor the that the possibility to test for 7-12) (models 2016:M12 positive a and 2016 January in effect tax negative the confirms 5 Table results. the various specifications. 2015 across one in December

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

320 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

321 44 (3) 299-329 (2020) on the zagreb stock exchange Given that the taxation of capital gains in Croatia is not a separate tax form, but gains Given that the taxation of capital the on how big statistics detailed the tax, wider income much of a a part rather How- are, are not publicly available. actually revenues from this type of taxation this amount by looking at the revenues from taxes on we can approximate ever, gains, but of capital taxation not only the which comprises from capital, income These revenues were HRK 146 million also income from dividends and interest. To our knowledge, this is the first empirical study to have analysed the impact of a of impact the analysed have to study empirical first the is this knowledge, our To results of thisThe Croatian stock market. newly introduced capital gains tax on the to policy makers, investors, boardspaper should thus be of interest and relevance It can also serve as a in the country. of listed companies and all other stakeholders policy makers, but also to those in otheruseful policy input not only to Croatian countries with small, poorly developed and shallow stock markets, characterized which have not yet introduced this type of taxation. by low levels of liquidity, Overall, our main conclusions remain unchanged after thorough and extensive after unchanged remain our main conclusions Overall, the new of the announcement that evidence and provide strong robustness checks securities of tax-free portfolio up a build to for investors incentives created tax and selling buying to disincentives as created as well force, into came it before the new tax burden on newly acquired stocks after 1 January 2016 because of weakly liquid market. securities, hurting the liquidity of an already Results of the event study based on daily data confirmed the hypothesis that the volume pat- high trading abnormally created gains tax of the capital introduction patterns low volume into force and abnormally the tax came terns shortly before after the fact. Our estimations based on monthly data confirmed these findings. Regression discontinuity models indicated a statistically significant breakin the - was intro tax when the point the cut-off precisely at line regression slope of the pre-tax the in increased volume trading the that evidence further providing duced, In addition, force. into entered tax dropped when the substantially and then period 45 a in resulted introduction tax the that suggested estimations regression panel into in the trading volume growth rate the month tax entered decrease percent in trading volume in the last month force, and a 16 percent increase in the growth sug- estimations difference-in-differences Finally, was introduced. the tax before percent was 23 years post-tax three the in volume trading average the that gest of introducing the consequences that indicating period, lower than in the pre-tax nature. of a longer-term this tax are not only short-term, but also 6 CONCLUSION AND POLICY IMPLICATIONS POLICY AND 6 CONCLUSION this dynamics, stock market on of taxation effects on the literature the on Building - gains tax on the trad capital introduced of the recently the effects paper analysed into force and after its coming Exchange before on the Zagreb Stock ing volume methodological different using three effects the analysed We 2016. in January panel and design discontinuity regression methodology, study – event approaches regressions. - , suggesting that its fiscal are effects almost negligible. 7 Revenues from the income taxes are revenues of the local government. On the other hand, however, the effects of introducing such a tax, as our study has as our study has such a tax, of introducing effects the however, hand, other On the and the par liquidity on market consequences had serious adverse shown, have Disclosure statement Disclosure by the authors. No potential conflict of interest was reported ticipation of small investors in the stock market. In these circumstances, one can stock market. In these circumstances, of small investors in the ticipation a only for problem large a created tax a such of introduction the that conclude the idiom from the title of this paper. small gain – explaining this study is that countries with of policy recommendations One of the main taxes introducing should avoid stock markets and poorly liquid underdeveloped market. the in participating in public the of interest the discourage further can that to invest their money into other and companies individuals This can incentivize market), estate real (e.g. the treatment tax preferential a more types of assets with Our for dangerous asset price bubbles. increasing the possibilities study suggests that fiscal (tax) policy in these countries should be used inthe opposite direction as possible, resulting new investors as many and attract investment – to encourage development of the stock market. in higher liquidity and facilitating faster pre-announcement the hypothesis, which explore work should empirical Future hypothesis, is stronger on ZSE, interpretation differential or the disagreement vola- the on volume trading of effects assumes different hypothesis each because the effects Another avenue for future research is examining of stock returns. tility and other hypotheses stock returns, volatilities volume on of abnormal trading (such as the clientele hypothesis, see Kross, Ha and Heflin, 1994) to make clear regard- of the uncertainty about the distribution on the (dis)agreement distinctions ing the event of interest. 7 higher in 2016 than in 2015 (Ministry of Finance, 2019), which can be interpreted can be interpreted which 2019), of Finance, (Ministry than in 2015 in 2016 higher taxation the that given tax, gains capital the from revenue of estimate rough as a would This earlier. introduced had been interest from dividends and of income of reve- constitutes only 0.36% gains tax capital the revenue from the imply that government local nues of

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

322 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

323 44 (3) 299-329 (2020) on the zagreb stock exchange , - The , 50, , 66(2), pp. , 66(2), pp. . Urban Institute Journal of Finance of Journal , 5(2), pp. 1-12. Journal of Banking and Finance Journal of Accounting and Economics, , 29(2), pp. 25-46. , 29(2), pp. The European Journal of Finance, 13, pp. 227-252. Accounting and Taxation , 72(4), pp. 575-597. Journal of Accounting and pp. 331-360. , 11(4), Economics , 42(3), pp. 43-48. https://doi.org/10.2469/faj.v42.n3.43 Review Management, 16(2), pp. 54-62. https://doi.org/10.2307/3666004 Amoako-Adu, B., Rashid, M. and Stebbins, M., 1992. Capital gains tax and M. and Stebbins, M., 1992. Capital Amoako-Adu, B., Rashid, and introduction the to reaction price stock of test Empirical values: equity exemption. gains tax of capital reduction Ajinkya, B. B., Atiase, R. K. and Gift, M. J., 1991. Volume of trading and the and the of trading Volume 1991. K. and Gift, M. J., R. Atiase, B., Ajinkya, B. The earnings forecasts. Accounting Review of analysts’ dispersion 389-401. Market Stock Daily of Behaviour The 1989. C., P. Jain, and P. B. Ajinkya, Volume. Trading and stock returns. Financial and Mendelson, H., 1986. Liquidity Y. Amihud, Analysts Journal Agostini, C. and Siravegna, M. C., 2014. The Effect of the Capital Gains Tax Tax Gains Capital of the Effect The C., 2014. M. Siravegna, C. and Agostini, Prices in Chile. Revista on Stock Market Exemption de Analisis Economico Review Analysis − Economic https://doi.org/10.1016/0165-4101(89)90018-9 investments: market stock and taxation gains Capital A., 2013. Akindayomi, empirical evidence. Press. https://doi.org/10.1016/0165-4101(94)90031-0 of Unbiasedness the and Behavior Trading A. M., 1995. Vijh, M. and Bajaj, Announcement. The to Dividend the Market Reaction 16(2), pp. 275-287. https://doi.org/10.1016/0378-4266(92)90014-q volume reactions to annual Trading L. S., 1994. Atiase, R. K. and Bamber, announcements. earnings accounting 17(3), pp. 309-329. In: J. Cordes, R. D. Ebel and J. G. Taxation. Gains Auten, G., 1999. Capital eds. The Gravelle, Encyclopedia of and Policy Taxation Tax pp. 255-279. https://doi.org/10.1111/j.1540-6261.1995.tb05173.x dif- and volume Trading 1997. L., T. Stober, O. E. and Barron, S., L. Bamber, announcements. with earnings coincident of disagreement aspects ferent Accounting interpreta Differential 1999. L., T. Stober, O. E. and Barron, S., L. Bamber, tions and trading volume. Journal of Financial and Quantitative Analysis, 34(3), pp. 369-386. https://doi.org/10.2307/2676264 studies on event 2007. Conducting J., Olson, D. and Peare, P., Bartholdy, stock exchange. small Benić, and V. Franić, I., 2008. Stock market liquidity: comparative analysis of practice, 32(4), pp. 477-498. and theory Croatian and regional markets. Financial Makers. Finan- Stock Markets, and Market L., 1987. Liquidity, Bernstein, P. cial https://doi.org/10.1080/13518470600880176 and Expected C., 2007. Liquidity C. R. and Lundblad, Bekaert, G., Harvey, Studies, 20(6), Financial of Markets. Review Returns: Lessons from Emerging pp. 1783-1831. https://doi.org/10.1093/rfs/hhm030

6. 3. 2. 5. REFERENCES 1. 4. 9. 7. 8. 10. 12. 15. 11. 13. 14.

, - The nja, va­ NBER Working NBER Working Journal of Accounting Journal of Accounting , Research . SIA Working Paper. Working . SIA , 34, pp. 55-63. https://doi.org/10.1016/j. , 32(1), pp. 165-175. https://doi.org/10.1111/j.1540- The Journal of the American Association Taxation , 61(4), pp. 2017-2046. , 14, pp. 203-215. https://doi.org/10.1016/0165-4101(91)90005-9 Advances in accounting , 6, pp. 309-326. https://doi.org/10.1007/bf00245187 Applied Financial Economics, 21(5), pp. 333-341. https://doi.org/10.1 The Journal of Finance of Journal The 35(2), pp. 1-31. https://doi.org/10.2308/atax-50509 and stock returns: R., 1998. Liquidity and Radcliffe, Y. Naik, N. T., V. Datar, test. Journal An alternative of Financial Markets , 1(2), pp. 203-219. https:// doi.org/10.1016/s1386-4181(97)00004-9 behav- stock market and year-end gains taxation A., 1977. Capital Dyl, E. ior. 6261.1977.tb03250.x Tax Gains Capital from Benefits Who 1989. H., L. Summers, and L. Fenberg, 4. Policy and the Economy: Volume Reductions?. In: L. H. Summers, ed. Tax https://doi.org/10.1086/tpe.4.20061790 A., 1999. Liquidity risk Fernandez, F. Frazzini, A., 2006. The disposition effect and underreaction to news. and underreaction The disposition effect A., 2006. Frazzini, Dai, Z., Shackelford, D. A. and Zhang, H. H., 2013. Capital Gains Taxes and Taxes Gains H. H., 2013. Capital A. and Zhang, D. Dai, Z., Shackelford, Stock Volatility. Return 30(1), pp. 1021-1032. https://doi.org/10.1080/1331677x.2017.1311228 30(1), pp. 1021-1032. Portfolio of Source Important an Investors Institutional 1994. Are Chuhan, P., Investment Bank Press, in DC: The World Emerging Markets?. Washington, Department. International Economics perfor security-price test for abnormal nonparametric A Corrado, C. J., 1989. in event studies. Journal mance of Financial Economics, 23(2), pp. 385-395. https://doi.org/10.1080/1331677x.2017.1311228 Log- Employing Tests The Power of R., 1991. M. and Ramanan, W. Cready, Abnormal Trading. in Detecting Volume Transformed Finance and Journal of Finance of tax rate changes on intercorporate The impact [et al.], 2016. R. F. Gary, investment. adiac.2016.07.002 to the CAC40 Stock of Revisions Effects The Liquidity A., 2011. Gregoriou, Index. 080/09603107.2010.530216 Blouin, J. L., Raedy, J. S. and Shackefold, D. A., 2000. Capital Gains Taxes Taxes Gains Capital 2000. A., D. S. and Shackefold, J. J. L., Raedy, Blouin, Announcements. Earnings Quarterly to Reactions Stock and https://doi.org/10.3386/w7644 Paper, No. 7644. Taxes Gains Capital A., 2003. D. Shackerfold, J. S. and L., Raedy, Blouin, J. Evidence. Empirical Trading: and Equity https://doi.org/10.1111/1475-679x.00118 611-651. 41(4), pp. - Vol Trading Abnormal Measuring 1996. E., C. Wasley, J. and C. Campbell, Using Parametric of NYSE/ASE and NASDAQ for Samples Securities ume Review Statistics. Test and Nonparametric of Quantitative Finance and Accounting returns to bid- N., 2017. Domestic and cross-border S. and Mirza, Chaudary, istraži ­ research-Ekonomska EU. Economic into the ders in acquisitions

24. 25. 26. 27. 28. 23. 20. 21. 22. 29. 30. 16. 17. 18. 19.

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

324 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

325 44 (3) 299-329 (2020) on the zagreb stock exchange

- Zagreb Zagreb , Economics , 30(2), pp. 273-309. The Journal of Finance, 41(5), Quarterly Quarterly Journal of , 61(3), pp. 1073-1117. https://doi.org/10.1111/ 1073-1117. , 61(3), pp. , 2, pp. 451-471. https://doi.org/10.1093/jjfinec/ 451-471. pp. 2, , The Review of Financial , 8(4), pp. 919-972. Studies , 29(2), pp. 109-126. Accounting Research Journal of Economics, 13(3), pp. 435-455. https://doi.org/10.1016/

, 22(4), pp. 243-253. https:// Economy, 22(4), pp. 243-253. World the and Japan Journal of Financial Economics Journal, 43(4), pp. 411-425. The Journal of Finance of Journal The Tax https://doi.org/10.1093/rfs/8.4.919 returns by 2004. Improving tests of abnormal P., Westfall, Hein, S. E. and event parameters. Jour regression model with bootstrapping the multivariate International International Review of Economics and https:// 41-58. pp. 20(1), Business, doi.org/10.1515/zireb-2017-0004 in a Stock Behavior Investor 1978. Speculative M. and Kreps, D., Harrison, Expectations. Heterogeneous Market with 323-336. https://doi.org/10.2307/1884166 92(2), pp. trading: gains tax and individual 2010. Capital M. and Ono, H., Hayashida, case of Japan. The doi.org/10.1016/j.japwor.2010.06.005 of Behavior and Dynamic Information J., 1995. Differential Wang, He, H. and Volume. Stock Trading Econometrics Financial of nal Grubišić Grubišić Šeba, M., 2017. 20 Years of the Croatian Capital Market. nbh018 volume. and stock market gains tax rates K., 1990. Capital Y. Henderson, National 0304-405x(84)90008-4 Kim, O. and Verrecchia, R. E., 1991b. Trading Volume and Price Reactions to Reactions Price and Volume Trading 1991b. R. E., Verrecchia, Kim, O. and Announcement. Public via Effects Clientele Risk of Test A 1994. R., Heflin, and L. G. Ha, W., Kross, Announcements. Earnings Response to Volume Trading of an Examination Journal of Accounting and https://doi.org/ 67-87. 18(1), pp. Economics, 10.1016/0165-4101(94)90019-1 behavior. turn-of-the-year and Volume 1984. S., Smidt, J. and Lakonishok, Journal of Financial 61(3), pp. 1399-1431. https://doi.org/10.1111/j.1540-6261.2006.00876.x Volume. Theory of Trading A J., Karpoff, 1986. pp. 1069-1087. Anticipated to R. E., 1991a. Market Reaction Verrecchia, Kim, O. and Announcements. Hong, H., Scheinkman, J. and Xiong, 2006. W., Asset float and speculative bubbles. j.1540-6261.2006.00867.x stock market– on the tax stock transaction of the effects The 1998. Y., Hu, S. Pacific-BasinAsian markets. from experiences Finance Journal, 6(3-4), pp. 347-364. https://doi.org/10.1016/s0927-538x(98)00017-1 speculative behav- U., 2019. Individual Weitzel, Janssen, D-J., Füllbrunn, S. and asset markets. Experimental overpricing in experimental and ior , Economics 22(3), pp. 653-675. https://doi.org/10.1007/s10683-018-9565-4 Finance, of and price pressure. Journal Jin, L., 2006. Capital gains tax overhang

35. 32. 33. 34. 31. 36. 45. 43. 44. 41. 42. 38. 39. 40. 37. , Journal of Proceedings Proceedings of the 11th Annual Econometric Research in Finance in Research Econometric , 53(5), pp. 1799-1819. https://doi. Virginia Tax Review, 8, pp. 591-637. Tax Virginia , 11, pp. 116-121. , 11, . Zagreb: Ministry of Finance. . Zagreb: Ministry of Quarterly, 10(1), pp. 3-16. https://doi.org/10.1177/

, 111(6), pp. 1183-1219. pp. 1183-1219. Economy, 111(6), Political pp. 642-685. https://doi.org/ economy, 111(3), Finance Public Economic research-Ekonomska 776-802. pp. 25(3), istraživanja, Journal of - Ex-Div around Trading Tax-Induced 1986. T., Vermaelen, and J. Lakonishok, Days. Journal idend of Financial https://doi. pp. 287-319. , 16, Economics org/10.1016/0304-405x(86)90032-2 returns. and stock illiquidity, Capital gains, and Zhu, X., 2013. Y. Lei, X., Zhou, Pacific-Basin Finance273-293. https://doi.org/10.1016/j. , 25, pp. Journal pacfin.2013.10.001 Finance. and Economics in Studies A. C. 1997. Event MacKinlay, https://doi.org/10.1080/1331677x.2012.11517533 stock risk and expected Liquidity 2003. R. F., L. and Stambaugh, Pástor, returns. , 35, pp. 13-39. Economic Literature Finance, 32(2), pp. 261-275. of Journal The Taxes. M. H., 1977. Debt and Miller, proračuna Državnog izvršenju o izvještaj 2019. Godišnji Ministry of Finance, za 2016 Republike Hrvatske Minović, J., 2012. Liquidity of the Croatian Analysis. Stock Market: An Empirical 10.1086/374184 Evi- activity: market and stock gains taxation A., 1998. Capital W. Reese Jr., from IPOs. The dence Journal of Finance org/10.1111/0022-1082.00073 The Law to Stabilize the Stock Market: Tax of The Use Repetti, J. R., 1989. Requirements. Period Holding of Efficacy in randomized and of treatments causal effects Rubin, D. B., 1974. Estimating studies. Journal nonrandomized of educational , 66(5), pp. 688- Psychology 701. https://doi.org/10.1037/h0037350 Scheinkman, J. and Xiong, 2003. W., Overconfidence andSpeculative Bub- bles. Journal of Political Changes: Tax Gains to Capital A., 2000. Stock Market Reaction Shackefold, D. Acts. Tax Policy Tax 1998 Evidence from the 1997 and Empirical and the Economy, 14, pp. 67-92. https://doi.org/10.1086/654703 Sheskin, D. J., 1997. Parametric and Nonparametric . Statistical Procedures Boca Raton: CRC Press. tax gains and the 1978 capital volume Slemrod, J., 1982. Stock transactions reduction. 109114218201000101 Anoma- Calendar of the An Examination D., 2011. O. and Diaconasu, Stoica, Stock Markets. Recent European and Eastern Central on Emerging lies Applied Economics in Researches https://doi.org/10.33119/erfin.2018.3.2.3 3(1), pp. 119-162. Markets, Financial of Opinion in Financial H. R., 1989. Differences Varian, Implications. I and Evidence Theory, Risk Škrinjarić, T., 2018. Revisiting herding investment behaviour on Zagreb Stock Zagreb on behaviour investment herding Revisiting 2018. T., Škrinjarić, approach. regression quantile a Exchange:

46. 47. 48. 52. 49. 50. 51. 53. 54. 55. 56. 57. 58. 59. 60. 62. 61.

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

326 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

327 44 (3) 299-329 (2020) on the zagreb stock exchange - - , 24(2), pp. 157-184. https:// , 24(2), pp. 157-184. Economic thought and prac- and thought Economic Business Systems Research: Inter Research: Systems Business Review of Quantitative Finance and , 2, pp. 537-550. The British Accounting Review Accounting British The , 19, pp. 45-63. Economic Economic Policy Conference of the Federal Reserve Bank of St. . Bos- Louis https://doi.org/10.1007/978-94-009-2665-3_1 ton: Kluwer. J., 2013. Investigation of stock illiquidity on Central and South East Vidović, framework. portfolio naïve in markets European tice-Ekonomska misao i praksa tice-Ekonomska Aljinović, Z., 2014. How and to Measure Illiquid J., T. Poklepović, Vidović, Stock Markets?. Emerging on European ity national journal of the Society for Advancing Innovation and Economy, 5(3), pp. 67-81. https://doi.org/10.2478/bsrj-2014-0020 Research in Change Following Dividend Kim, S., 2002. Risk Shift O. M. and Rui, Xu, P., The Announcement: Role of Trading. Accounting of returns and trading Event studies based on volatility K. 1992. P. Yadav, review. A volume: doi.org/10.1016/s0890-8389(05)80007-1 Stock Exchange. ZSE, 2019. Zagreb 63. 65. 66. 64. 67. Zagrebačka Banka Genera Viadukt Varteks Uljanik Plovidba Turisthotel Tankerska Next Generation Tankerska Tehnika Sunčani Hvar Riz-Odašiljači Valamar Riviera Valamar Petrokemija Podravka Plava Laguna Privredna Banka Zagreb Ot-Optima Telekom Ot-Optima Maistra Liburnia Riviera Hoteli Luka Ploče Ledo Kraš Končar elektroindustrija Full name ZABA VERN VDKT VART ULPL TUHO TPNG THNK SUNH RIZO RIVP PTKM PODR PLAG PBZ OPTE MAIS LRH LKPC LEDO KRAS KOEI Abbreviation Končar transformatori Jadranski Naftovod Jamnica Termes Grupa Termes Ingra Ina Institut IGH Hup Zagreb Htp Korčula Hrvatski Telekom Hoteli Maestral Imeprial Hotelijerstvo Ericsson Tesla Nikola Dalekovod Đuro Đaković Grupa Badel 1862 Atlanska Plovidba Excelsa Nekretnine Atlantic Grupa Arenahospitality Group Adris Grupa Adris Grupa AD Plastik Full name A1

able KODT JNAF JMNC IPKK INGR INA IGH HUPZ HTKP HT HMST HIMR ERNT DLKV DDJH BD62 ATPL ATLN ATGR ARNT ADRS2 ADRS ADPL Abbreviation Source: ZSE (2019). Source: APPENDIX T full names and abbreviations in the study, Stocks included

public sector tomislav globan, tihana škrinjarić:

economics penny wise and pound foolish: capital gains tax and trading volume 44 (3) 299-329 (2020) on the zagreb stock exchange

328 public sector tomislav globan, tihana škrinjarić: economics penny wise and pound foolish: capital gains tax and trading volume

329 44 (3) 299-329 (2020) on the zagreb stock exchange 73.53 29.89 32.62 96.95 71.99 29.78 29.09 38.92 88.08 35.43 87.09 911.76 211.61 792.66 120.80 302.72 129.44 123.77 624.03 202.21 591.25 109.47 122.86 454.71 249.64 534.32 567.35 303.27 213.69 122.96 199.05 155.84 140.10 493.60 170.53 159.69 212.86 1,211.95 Std Dev 1,737.54 1,159.17 1,247.46 1,363.60 1,061.10 1,385.18 1,164.48 1.11 0.07 0.91 4.05 0.55 0.00 0.14 3.27 0.62 7.73 2.30 0.67 3.35 0.08 0.03 2.66 0.09 1.72 0.06 0.21 0.40 4.68 0.04 1.13 0.14 0.03 0.23 0.01 0.02 0.57 0.25 0.09 2.41 0.82 0.08 0.33 0.29 6.02 0.02 0.52 0.09 0.29 42.88 85.50 Min 146.63 401.85 744.68 978.09 175.94 229.30 907.15 815.82 452.56 179.42 856.16 190.28 299.33 697.17 201.06 815.57 Max 1,377.11 4,414.41 1,473.83 5,650.90 1,327.39 2,073.68 1,561.05 8,994.87 1,164.25 4,783.23 1,088.35 6,471.87 2,408.00 7,246.07 7,418.40 6,703.40 2,063.88 1,884.55 1,127.95 3,906.28 1,448.86 1,498.57 1,567.48 11,025.00 14,962.34 14,719.90 14,400.00 12,294.00 10,257.70 12,017.97 Volume – daily series Volume 41.35 60.61 61.19 91.51 27.36 53.62 19.49 87.22 14.84 50.84 95.56 77.02 72.99 29.53 25.18 25.80 28.79 48.60 72.13 28.04 30.04 71.63 118.58 115.87 119.98 311.94 809.06 543.90 637.45 152.63 259.15 172.85 191.39 705.41 134.43 178.38 145.05 148.16 101.23 189.01 359.35 483.92 123.63 Mean 1,428.45 1,230.45 77 88 35 59 58 84 T 112 211 118 116 267 184 254 106 129 230 209 142 189 164 253 201 222 196 143 122 267 135 143 265 223 259 178 267 148 226 255 160 261 213 226 267 210 205 244 83.11 67.25 84.14 62.07 50.05 19.43 29.35 79.32 115.49 645.71 476.12 492.02 220.60 290.03 108.09 321.29 778.98 555.59 149.30 161.74 130.48 830.21 644.38 250.76 439.85 921.73 459.19 223.84 220.92 186.44 575.65 108.85 413.64 150.59 180.72 990.20 479.49 216.88 Std Dev 2,495.54 6,606.88 1,405.50 4,021.53 3,247.30 1,141.86 2,234.49 1.22 7.78 5.45 1.40 1.35 1.65 0.90 1.28 0.05 11.16 11.25 49.03 36.87 19.35 34.76 10.13 31.58 15.10 64.62 25.12 34.81 43.49 10.13 26.89 Min 107.36 497.06 191.83 5,263.15 3,197.20 2,104.67 2,105.70 5,691.94 7,158.87 5,908.33 6,427.43 3,531.91 2,028.40 7,746.58 2,168.67 3,355.38 2,291.80 6,566.67 3,452.14 3,291.37 1,319.17 692.44 400.06 608.64 473.32 830.74 404.98 334.56 169.46 898.46 448.85 999.37 932.35 174.86 750.82 Max 3,211.42 3,284.68 3,759.51 2,284.17 2,473.85 2,882.99 6,570.51 4,127.71 1,616.32 1,044.36 4,658.47 6,975.49 4,367.23 2,641.55 8,319.04 3,533.72 3,806.65 4,272.85 1,707.93 1,449.05 2,077.46 4,197.33 2,704.10 8,546.29 4,990.79 1,053.45 11,737.10 25,080.00 65,483.06 25,767.94 16,686.34 Volume – monthly series Volume 65.74 56.59 94.50 75.43 63.42 41.36 82.77 98.54 32.95 51.60 23.16 90.55 42.90 21.18 32.00 118.70 116.35 555.08 309.13 494.29 109.20 163.91 188.41 555.80 436.93 127.84 619.07 507.56 663.28 322.17 730.53 344.38 658.26 205.45 154.39 252.91 415.06 124.46 338.98 267.75 Mean 1,712.24 2,590.00 3,458.93 1,182.02 1,040.93 98 52 T 112 116 113 118 119 135 137 137 136 137 137 137 137 137 137 137 137 137 136 137 130 137 133 137 137 132 137 137 137 137 137 136 137 137 137 137 137 137 137 137 108 137 137 A2 able Stock RIZO RIVP PTKM PODR PLAG PBZ OPTE MAIS LRH LKPC LEDO KRAS KOEI KODT JNAF JMNC IPKK INGR INA IGH HUPZ HTKP HT HMST HIMR ERNT ZABA DLKV VERN DDJH VDKT BD62 VART ATPL ULPL ATLN TUHO ATGR TPNG ARNT THNK ADRS2 SUNH ADRS ADPL Note: T denotes number of observations; Std Dev denotes standard deviation. denotes number of observations; Std Dev denotes standard Note: T T in frequencies, daily and monthly in series volume trading of statistics Descriptive HRK thousands