(Luận văn thạc sĩ) institutional quality, macro liquidity excessive and stock market volatility empirical evidences from emerging markets

506 | ICUEH2017 Institutional quality, macro liquidity excessive and stock market volatility: Empirical evidences from emerging markets NGUYEN PHUC CANH University of Economics HCMC – canhnguyen@ueh.edu.vn SU DINH THANH University of Economics HCMC – dinhthanh@ueh.edu.vn Abstract The relationship between monetary policy and stock market is still argument in the literature, especially in emerging countries The study investigates the relationship between institutional quality, macro liquidity excessive and stock market volatility, in which macro liquidity excessive is used as a proxy for monetary policy Using a panel data of 32 emerging markets in the period of 2002 – 2013 and employing Sys GMM estimation, the study finds that the relationship between macro liquidity excessive and stock volatility is significantly negative Interestingly, when interacting with institutional quality variables, namely regulatory quality and law indicator, the effects of institutions on stock returns are significantly negative That means that institution quality moderates the effect of macro liquidity excessive on stock market volatility, implying that emerging countries should attend to improving institutional quality to reduce stock market volatility Keywords: institution; liquidity excessive; stock market; volatility Introduction Stock market volatility is undoubtedly one of the most interesting topics in financial economics at both micro and macro level With regard to volatility characteristics, tremendous studies have considered the determinants of stock volatility at both individual and market levels (see Harris (1989), Damodaran and Lim (1991), Jaleel and Samarakoon (2009), Vlastakis and Markellos (2012), Sharma, Narayan, and Zheng (2014), and X V Vo (2016) However, in the context of deeply financial and economic integration and the Nguyen Phuc Canh & Su Dinh Thanh| 507 recent 2008 global financial crisis, much attention has been withdrawn the stock volatility at market level (for instance, see Abbas, Khan, and Shah (2013), Zare, Azali, and Habibullah (2013), Bouri (2015a), Syriopoulos, Makram, and Boubaker (2015), Assaf (2016)) It is important to understand stock market volatility due to its role in portfolio management and predictability model of individual stock returns and volatility, and economic volatility (Mittnik, Robinzonov, & Spindler, 2015; Sharma et al., 2014; Syriopoulos et al., 2015) Many previous studies have focused on main determinants of stock market volatility such as oil price, exchange rate, interest rate, inflation, economic cycles, market liquidity, financial liberalization, etc., (see Pierdzioch, Döpke, and Hartmann (2008), Bley and Saad (2011), Walid, Chaker, Masood, and Fry (2011), Girardin and Joyeux (2013), Bouri (2015b), Choudhry, Papadimitriou, and Shabi (2016), Kawakami (2016)) Some studies have investigated the effects of institutions on stock market volatility as “government policy uncertainty” found in the study of Pastor and Veronesi (2012) The study of Vortelinos and Saha (2016) examines the impact of political risk on stock market volatility in sixty-six countries and finds that political risks explain the high volatility and discontinuity in international stock and foreign exchange markets in most of regions excluding Europe Günay (2016) finds that the Turkish stock market responds to political events when analyzing the effects of internal political risk on stock market in the period of 2001–2014 However, these studies only focus on examining the effects of only political risk, while ignoring the other important aspects of institutions such as regulations, law system In addition, previous studies have investigated effects of money dynamic on stock market (see Rogalski and Vinso (1977), Fama (1981), Cutler, Poterba, and Summers (1988), Jensen, Mercer, and Johnson (1996), Thorbecke (1997), Abugri (2008), Issahaku, Ustarz, and Domanban (2013), McMillan (2015), Gay (2016)) The money growth effect of stock returns and volatility is found to be significant However, these studies only pay attention to the effects of changes in money supply without considering its fluctuations around its theoretical equilibrium The institution is defined as “the game rules” in a society (Douglass C North, 1990), which includes “humanly devised” which contrasts with other economic fundamentals, “the rules of the game” to set “constraints” on human behavior (see Douglass Cecil North 508 | ICUEH2017 (1981), Acemoglu and Robinson (2008)) Hence, improvements in institutions reduce asymmetric information problem, transaction cost, and risk, and then increase market efficiency, especially efficiency of asset allocation (Cohen, Hawawini, Maier, Schwartz, & Whitcomb, 1983; T S Ho & Michaely, 1988; Williamson, 1981) Thus, it is argued that better institutional quality would have stronger impact on stock market volatility, especially in emerging markets Therefore, this study provides new arguments and empirical evidences for shedding light on the question of whether or not institutions and excessive in money supply (or macro liquidity excessive) lower stock market volatility in 32 emerging markets Besides this, we investigate whether adding the association between institutions with macro liquidity excessive can significantly explain for stock market volatility Using unbalance annual panel data of 32 emerging markets1 from 2002 to 2013 to investigate impacts of institutions, macro liquidity excessive, and their associations on stock market volatility while controlling main macroeconomic determinants Our study is firstly different from the aforementioned studies in measuring the macro liquidity excessive, which is presented detail in Section We believe that our method in measuring macro liquidity excessive is more advantage as a proxy for money supply excessive at country level Previous studies only investigate impacts of political events such as election and political risk, which only impose risk indirectly on stock market volatility Our study examines the effects of two important dimensions of institutions, namely regulations and law on stock market volatility, to which these institutional indicators have directly impacts on the efficiency of stock market through their impacts on transaction cost, risk, and the asymmetric information problem We also take our analysis one-step further by examining effects of the associations between institutions with macro liquidity excessive on stock market volatility, which contribute to the literature on the interaction of institution with macroeconomic factor on stock market volatility, and the policy implication for authorizers in stabilizing financial market With this strategy, we believe that our study has significant contribution to both scholar and practice First, our study contributes to the detrimental literature of stock List of emerging markets: Argentina, Brazil, Bulgaria, Chile, China (mainland), Colombia, Czech Republic, Egypt Arab Rep., Estonia, Greece, Hungary, India, Indonesia, Korea Rep., Latvia, Lithuania, Malaysia, Mexico, Morocco, Nigeria, Oman, Pakistan, Peru, Philippines, Poland, Romania, Russian Federation, Slovenia, South Africa, Thailand, Turkey, and Vietnam Nguyen Phuc Canh & Su Dinh Thanh| 509 market volatility by adding new factors including the macro liquidity excessive and institutional quality To the best of our knowledge, this paper is the first work on the impacts of macro liquidity excessive and institutions on stock market volatility Our empirical results show consistent evidences that the macro liquidity excessive has strong significant negative impacts on stock market volatility in emerging markets, which confirms the literature that the excessive in money supply moves into stock market and makes it more stable In addition, our empirical results also show that the better institutional quality including quality of regulations and law reduce stock market volatility, which implies a strong suggestion for stabilizing stock market at emerging economies Second, our study contributes empirical evidences to the scholar that the institutional improvements in associating with higher excessive of money supply reduce stock market volatility This result implies that the excessive macro liquidity is less risky for stock market if institution is improved At last, our study contributes enhanced measurement to determine the excessive in money supply beside the growth rate of money supply and decompose money growth rate into underlying and non-underlying parts for examining the effects of money on stock market volatility The rest of the paper is organized as following manner Section provides a literature review on determinants of stock market volatility and impacts of institutions and macro liquidity excessive Section briefly describes the methodology in estimating macro liquidity excessive and examining effects of institutions on stock market volatility Section also presents our data definitions, calculations, and sources Section presents results and discusses the findings Section provides a summary and concludes this paper Literature review There is a huge literature investigating the relationships between macroeconomic factors and stock market volatility The question about macroeconomic determinants of stock market volatility was asked by Schwert (1989), where he investigates the timevarying stock return volatility by means of the time-varying volatility of macroeconomic and financial variables In overall, he points to a positive linkage between macroeconomic volatility such as inflation, money growth, industrial production with stock market volatility (see Whitelaw (1994), Campbell, Lettau, Malkiel, and Xu (2001), Beltratti and Morana (2006)) The model of Schwert (1989) is applied and tested in many studies such 510 | ICUEH2017 as Pierdzioch et al (2008) use to forecast the volatility of Germany stock market, while Beltratti and Morana (2006) test it in US stock market Many previous studies have examined other macroeconomic factors including internal and external factors such oil price, exchange rate, interest rate, economic growth, foreign portfolio investment flow, stock market liberalization, US stock market in determining stock market volatility For instance, Kearney and Daly (1998) find that among the most important determinants, such as the inflation and interest rates, the conditional volatilities of industrial production, the current account deficit and the money supply are indirectly associated with Australian stock market conditional volatility Beltratti and Morana (2006) also find strong evidences of causality running from macroeconomic factors such as Fed fund rate, inflation, output growth, money growth to US stock market volatility Engle and Rangel (2008), one of the popular study, propose to model including both macroeconomic effects and time-series dynamics to investigate the determinants of stock market volatility for 50 countries in a balanced panel They find that stock market volatility is a positive function of output growth, inflation, and short-term interest rates In addition, they find that the stock volatility is larger in the lower output growth and high inflation environment, and stock volatility is higher both for emerging markets and for large economies Along different direction, Diebold and Yilmaz (2008) examine the links between asset return volatility and the volatility of its underlying macroeconomic determinants for forty countries and find a positive relationship between stock return and GDP (or consumption) growth volatilities Similarly, Engle, Ghysels, and Sohn (2008) find that the long-term component of stock return volatility is driven by inflation and industrial production growth Girardin and Joyeux (2013) find that the influence of macroeconomic variables on the long-run volatility of the Chinese stock market is limited to the nominal variables, with a noteworthy disconnect form the real economy However, they conclude that macroeconomic fundamentals play an increasing role after China joined WTO, especially for CPI inflation Beside inflation, economic growth, interest rate, the exchange rate fluctuations also play important role in explaining stock market volatility Walid et al (2011) find strong evidence that the relationship between stock and foreign exchange markets is regime dependent and stock-price volatility responds asymmetrically to events in the foreign Nguyen Phuc Canh & Su Dinh Thanh| 511 exchange market While, Creti, Joëts, and Mignon (2013) find strong correlations between commodity such as oil, coffee, cocoa, gold and stock markets evolve through time and are highly volatile, particularly since the 2007–2008 financial crisis In the same argument, M Vo (2011) finds that the stock volatility and oil futures prices are inter-related following a time-varying dynamic process and tends to increase when the markets are more volatile P Wang and Moore (2009) investigates sudden changes in volatility in the stock markets of new European Union (EU) members and finds that a sudden change in stock volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises Meanwhile, the effects of foreign portfolio investment on stock volatility are got more attentions in recent years due to the higher integration between markets Jayasuriya (2005) finds that volatility may decrease, increase, or remain unchanged following liberalization at eighteen emerging markets, where countries that experienced lower post-liberalization volatility are in general characterized by favorable market characteristics Jaleel and Samarakoon (2009) liberalization of the market to foreign investors significantly increased the return volatility in the Colombo Stock Exchange Ben Rejeb and Boughrara (2015) find that financial liberalization contributes significantly in amplifying the international transmission of volatility and the risk of contagion in emerging markets In contrast, Bley and Saad (2011) point that international participation in local trades has no impact on idiosyncratic volatility and a rising impact on total volatility, but capital account openness significantly reduces total volatility, especially for stocks with low foreign ownership limits In the trend of financial and economic integrations, the spillover or contagion from a large stock market to other stock markets are strong noticed Mukherjee and Mishra (2010) study the stock market integration and volatility spillover between India and its major Asian counterparties They find that contemporaneous intraday return spillovers between India and its Asian counterparts including Hong Kong, Korea, Singapore, and Thailand are found to be positively significant and bi-directional Yarovaya, Brzeszczyński, and Lau (2016) investigate the channels of volatility transmission across stock index futures in six major developed and emerging markets in Asia, they find strong linkages between markets within the Asian region, indicating that the signal receiving markets are sensitive to both negative and positive volatility shocks, which reveals the asymmetric nature of volatility transmission channels 512 | ICUEH2017 However, in the context of emerging markets, there is clearly conclusion that US stock market has strong impacts For instance, Y A Liu and Pan (1997) investigates the mean return and volatility spillover effects from the U.S and Japan to four Asian stock markets, including Hong Kong, Singapore, Taiwan, and Thailand, their results suggest that the U.S market is more influential than the Japanese market in transmitting returns and volatilities to the four Asian markets Syriopoulos et al (2015) find significant return and volatility transmission dynamics are identified between the US and BRICS stock markets and business sectors Alotaibi and Mishra (2015) find significant return spillover effects from Saudi Arabia and US to Bahrain, Oman, Kuwait, Qatar, United Arab Emirates markets However, the study of Schwert (1989) finds that the level of macroeconomic volatility explains less than half of the volatility of stock returns Therefore, there definitely consists other determinants of stock market volatility, where we argue important impacts of macro liquidity excessive and institutional quality In fact, the money supply is defined as the main macroeconomic determinant of stock market volatility Theoretically, the relationship between changes in money supply with asset prices is argued by theoretical studies including Brunner (1961), Tobin (1963), Friedman and Schwartz (1975) by following direction: the unexpected changes in the money growth rate results in a change in the equilibrium position of money with respect of other asset in the portfolio of investors, hence investors try to adjust the proportion of their asset portfolio represented by money balances, while the system cannot adjust since all money balance must be held; hence, equilibrium is reestablished by changes in the price levels of the various asset categories including the stock prices (Rogalski & Vinso, 1977) Then, the study of Rogalski and Vinso (1977) conclude that the changes in the money supply as affected by changes in Fed policies will have a direct impact on returns from common stocks in US And in the study of Schwert (1989), he uses the money growth is one of the main explanatory variable in model of explaining the stock volatility and finds that the money growth volatility predicts stock volatility in various sub-samples Meanwhile, the higher money supply leads to improving economic conditions and lower required returns of stocks, hence it is better for stock price stabilization (McMillan, 2015) However, the study of Keran (1971) argues that the standard theory of stock price determination, discounting to the present the value of expected future earnings, which involves the use of a nominal interest rate which includes real interest rate and expected Nguyen Phuc Canh & Su Dinh Thanh| 513 inflation to determine the present value of expected corporate earnings over some future time horizon Therefore, in the contrast point of view, the higher money supply also leads to higher pressure of inflation, then increases the volatility of stock market volatility, which is documented in both literature and many previous works For instance, the study of Thornton (1993) finds the existing feedback effects between money supply volatility and stock price volatility in UK More interesting, Kearney and Daly (1998) find a strongest effect of the money supply to the conditional volatility of the stock market in Australia Cai, Chen, Hong, and Jiang (2015) also find that changes in the M1 money supply besides other factors such as inflation, stock turnover positively and significantly forecast the Chinese stock market volatilities, where the increases in money supply (M1) lead to a high future stock market volatility and hence high market risk Despites, many previous studies define that money supply growth is an important determinant of stock volatility, Liljeblom and Stenius (1997) can’t find significant evidence on the effects of money supply M2 in Finnish stock market, while they reveal significant impacts of inflation, industrial production, and changes in term of trade Similarly, Choi and Yoon (2015) find that the money supply of both Korea and US had no effect on the Korean stock market volatility Therefore, Jung and Kim (2016) propose new way of examine the effects of money supply on stock market volatility by decomposing the broad money M2 into an underlying and a non-underlying part and propose innovations in future non-underlying M2 growth as a proxy for macro liquidity They find that risk related to innovations in future non-underlying M2 growth is strongly significantly priced in Korea, after controlling for the well-known risk factors and other macroeconomic variables Overall, they conclude that non-underlying M2 growth more directly affects macro liquidity than does aggregate or underlying M2 growth Theoretically, money growth affects both on market-wide liquidity, equivalently macro liquidity or macro liquidity, and ultimately the level of capital available for investors to trade securities, where there is a link between macro liquidity and micro liquidity (see Chordia, Sarkar, and Subrahmanyam (2005)) Meanwhile, liquidity is defined as the ability to trade large quantities of a security quickly with a low cost without affecting its price, unexpected changes in money growth therefore can cause unfavorable shifts in the investment opportunity set in stock market (Jung & Kim, 2016) However, Chordia et al (2005) only study the effect of money flows including bank reserves and mutual fund investments on transactions liquidity without 514 | ICUEH2017 considering the underling and non-underling part of money growth, which may miss in measuring the shocks of money supply on stock market volatility In fact, the study of Jung and Kim (2016) has contributed to the literature by decomposing money growth into an underlying and a non-underlying part, which means the expected and un-expected changes in money supply, this method is more advantage in measuring the effects of money growth on stock market volatility since the unexpected changes in money growth as a state variable that is an embody of risk factor, therefore impacting on investor’s behaviors and overall stock market volatility In this study, we propose an enhanced measurement to develop the method of Jung and Kim (2016) by embodying the money supply into non-excessive and excessive, which presents for the excessive at macro liquidity We argue that the excessive liquidity at national level has significant impacts on stock market volatility beside the non-underling part of money growth as in work of Jung and Kim (2016) The excessive in money supply is difference from the unexpected changes in money supply since it measures the excessive of money in comparing to the theoretical equilibrium of the overall economy, which presents for the excessive in macro liquidity The macro liquidity excessive, in the one hand, leads to the better conditions for the economic activities, while it creates flexibility under the higher liquidity for investors in managing their investment portfolio, while the interest rate is lower due to the excessive of money leads to the lower required return, therefore, the stock market is more stable However, the excessive in liquidity, in the other hand, leads to the risk-taking behavior of investors, while it creates inflationary pressures, these combined effects lead to the higher volatility in stock market In short-term viewpoint, we argue that the macro liquidity excessive will favor the stock market by reducing the volatility due to the short-term positive effects on the economic conditions and the liquidity flexibility of investors in their investment Meanwhile, the excessive macro liquidity may lead to the higher stock volatility in the long – term due to the inflationary pressure if the economy cannot absorb this excessive into the real economic activities In addition to the economic determinants, theories and empirical studies also define that stock market volatility is determined by the institutional factors For instance, the study of Vortelinos and Saha (2016) conclude that political risks explain the high volatility and discontinuity in international stock markets Similarly, Arouri, Estay, Rault, and Nguyen Phuc Canh & Su Dinh Thanh| 515 Roubaud (2016) find that the increase in policy uncertainty reduces significantly stock returns and that this effect is stronger and persistent during extreme volatility periods L Liu and Zhang (2015) investigates the predictability of economic policy uncertainty (EPU) to stock market volatility, they find that higher EPU leads to significant increases in market volatility While Apergis (2015) documents the importance of both policy and technological risks, especially after the recent financial crisis event when he examines the role of both policy risk including the risk related to tax, spending, and monetary policies, and technological risk on U.S stock returns Chau, Deesomsak, and Wang (2014) examines the impact of political uncertainty (caused by the civil uprisings in the Arab World i.e., “Arab Spring”) on the volatility of major stock markets in the MENA region, they find that by distinguishing between conventional and Islamic stock market indices, they document a significant increase in the volatility of Islamic indices during the period of political unrests whereas the uprisings have had little or no significant effect on the volatility in conventional markets Günay (2016) also finds that the Turkish stock market responds to political events and it is stronger in recent years Since the higher efficiency of stock market means that the faster of the information incorporating into stock prices thus the volatility of stock market is strongly impacted by its efficiency, while the stock market efficiency is strongly impacted by the asymmetric information problem and transaction cost (Gilson & Kraakman, 2014; Gorton, Huang, & Kang, 2016) As stated, the institution is the rules of the game in a society (Douglass C North, 1990) including “humanly devised” which contrasts with other economic fundamentals, “the rules of the game” to set “constraints” on human behavior, and the incentives which transmit effects of institution to economic activities (see Douglass Cecil North (1981), Acemoglu and Robinson (2008)) The better institution reduces asymmetric information problem, transaction cost, and risk, it, in turn, increases market efficiency and the efficiency of asset allocation (Cohen et al., 1983; T S Ho & Michaely, 1988; Williamson, 1981), therefore induces a lower stock volatility There are studies have noticed the impacts of the stock market efficiency on volatility through the effects asymmetric information problem and support for these arguments For instance, Koulakiotis, Babalos, and Papasyriopoulos (2015) reveal that trading volume appears to capture a significant part of volatility asymmetric behavior in the pre and post 2009 global financial crisis in the Athens Stock Exchange when they examine the information arrival as measured by volume on asymmetric news Byström (2016) finds Nguyen Phuc Canh & Su Dinh Thanh| 523 Table Description of macro liquidity excessive Variable Obs Mean Std Dev Min Max Residual from (1) 343 0.1138 4.5786 -11.3858 26.4083 Fitted value from (1) 343 65.9894 34.9944 5.4477 189.6167 Naliqvo=(Residual/Fitted value)*100 343 1.3377 17.5592 -28.7249 285.9599 Naliqex 352 0.0682 0.2524 Source: author’s calculation The table presents the correlation matrix between our variables This shows that the stock market volatility at emerging market has significant correlations with almost variables In which, the stock market volatility has significant negative correlations with stock market capitalization, real GDP growth, changes in regulatory quality and rule of law These results imply that the better institution, the higher economic growth, and the larger stock market are going with lower volatility Meanwhile, the stock market volatility has significant positive correlations with inflation, interest rate, volatility in exchange rate, US stock market and oil price These results are also quite sensible to theories and our arguments 524 | ICUEH2017 Table Correlation matrix Correlation Stockvo Turnover Stockcap Gdpg Inf Interest m2g Fpi Fxvo p-value Stockvo Turnover 1.000 0.248*** 1.000 0.000 Stockcap Gdpg Inf Interest m2g Fpi Fxvo -0.127** 0.085 0.018 0.114 -0.247*** 0.096* 0.099* 0.000 0.074 0.063 0.141*** -0.029 -0.095* 0.144*** 0.006 0.590 0.077 0.005 -0.058 0.001 0.396*** 0.980 0.000 0.372*** 0.160*** 1.000 1.000 1.000 1.000 0.000 0.003 0.282 0.035 0.032 -0.015 0.502 0.556 0.782 0.000 0.000 0.000 -0.025 0.036 0.206*** 0.110** -0.022 0.024 0.122** 0.628 0.508 0.000 0.034 0.671 0.645 0.018 0.332*** -0.052 0.065 -0.346*** -0.029 0.000 0.329 0.225 0.000 0.567 0.448*** 0.281*** 0.250*** 1.000 1.000 0.353*** -0.150*** -0.113** 0.000 0.003 0.029 1.000 Usvo Oilvo Naliqex Reguqua Rulelaw Nguyen Phuc Canh & Su Dinh Thanh| 525 Correlation Stockvo Turnover Stockcap Gdpg Inf Interest m2g Fpi Fxvo Usvo 1.000 Oilvo Naliqex Reguqua Rulelaw p-value Usvo Oilvo Naliqex Reguqua Rulelaw 0.508*** 0.026 -0.083 -0.427*** -0.087 0.039 -0.266*** -0.067 0.226*** 0.000 0.632 0.120 0.000 0.089 0.452 0.000 0.198 0.000 0.353*** 0.041 -0.016 -0.199*** 0.047 0.099* -0.045 0.000 0.447 0.764 0.000 0.359 0.056 0.377 0.000 0.000 0.000 0.028 -0.037 -0.005 -0.013 0.163*** -0.038 0.324*** 0.070 0.013 0.036 0.064 0.604 0.510 0.928 0.815 0.002 0.478 0.000 0.195 0.803 0.502 0.229 -0.058 0.289*** 0.004 0.010 -0.040 0.266 0.000 0.932 0.848 0.453 -0.014 0.214*** 0.011 0.001 0.002 0.875*** 0.793 0.000 0.838 0.983 0.968 0.000 -0.191*** -0.154*** 0.092* -0.261*** -0.351*** -0.350*** -0.312*** 0.000 0.004 0.088 -0.193*** -0.029 0.116** -0.247*** -0.332*** -0.279*** -0.320*** 0.000 0.585 0.030 0.000 0.000 0.000 0.000 0.000 0.000 Note: *, **, *** denote significant level at 10%, 5%, and 1% respectively Source: author’s calculation 0.000 0.000 -0.192*** 0.327*** 0.559*** 1.000 1.000 1.000 1.000 526 | ICUEH2017 Results and discussions This section presents our estimation results for equation (3) by system – GMM estimators We recruit the system – GMM estimators following the study of Arellano and Bond (1991), Arellano and Bover (1995), and extended by Blundell and Bond (1998) and Blundell and Bond (1998) for advantage of addressing the bias associated with the fixed effects in short panels and solving the problem of endogeneity in dynamic panel data This is the major problem in our study since the relationships between stock market volatility and macroeconomic variables are feedback mechanism (Thornton, 1993), therefore the system – GMM is more advantage than other estimators All results including the effects of macro liquidity excessive, institutions and their associations on stock market volatility in 32 emerging markets are summarized in table 6, 7, and The system – GMM estimators are not subject to serial correlation of order two when we have un-significant of the AR(-2) test and the instruments used are valid when we have unsignificant of Hansen test too, therefore these results are unbiased and consistence Table Macro liquidity excessive and stock volatility Dep Var: Stockvo Effects of control variables (1) Effect of macro liquidity excessive (2) Coef P-value Coef P-value Stockvo(-1) 0.2239*** 0.0020 0.2257*** 0.0040 Turnover 0.0621*** 0.0010 0.0553*** 0.0000 Stockcap -0.0399*** 0.0000 -0.0253** 0.0370 Gdpg -0.8626*** 0.0010 -0.6151*** 0.0000 Inf 0.1109*** 0.0010 0.1816*** 0.0010 Interest -0.5457** 0.0230 -0.4401*** 0.0070 M2g 0.4340*** 0.0010 0.3540*** 0.0010 Fpi 3.5974*** 0.0060 2.5907*** 0.0010 Fxvo 7.7614*** 0.0000 4.5769*** 0.0010 Usvo 0.2511** 0.0230 0.3462*** 0.0000 Oilvo 0.0898* 0.0920 0.0976* 0.0750 -6.9621*** 0.0000 Naliqex No of IVs 24 26 Nguyen Phuc Canh & Su Dinh Thanh| 527 Effects of control variables (1) Dep Var: Stockvo Coef P-value Effect of macro liquidity excessive (2) Coef P-value No of Country 32 32 Obs 268 269 AR(2) test (P-value) 0.244 0.114 Hansen test (P-value) 0.881 0.714 Note: *, **, *** denote significant level at 10%, 5%, and 1% respectively Source: author’s calculation Table presents the impacts of macro liquidity excessive on stock market in 32 emerging markets in the period of 2002 – 2013 while controlling other factors We, firstly, estimate the equation (1) for all main control variables in model (1), then we add the macro liquidity excessive into model (2), this procedure aims at testing the robustness of our results The result in model (1) shows that all factors have significant positive impacts on stock market volatility excluding stock market capitalization, real GDP growth rate, and deposit interest rate, which have significant negative effects The significant positive effect of stock turnover on stock market volatility suggesting that the higher liquidity of stock market reduces the volatility of stock prices This result is consistence with theories and previous empirical evidences, where the stock market liquidity supports for its stabilization since the higher liquidity of stock market is in line with the lower liquidity premium of required return requirement, therefore favors the stock market returns and also the market stability (Chiang & Zheng, 2015; Jun, Marathe, & Shawky, 2003) The significant positive effect of inflation on stock market volatility means that the higher inflation is harmful for the stability of stock market in emerging markets This result is consistence with both literature and many previous studies, where the higher inflation is in long with higher risk factors and higher volatility (Beltratti & Morana, 2006; Engle et al., 2008; Fama, 1981) Other factors such as money growth rate, volatility in exchange rate, volatility in US stock market, and volatility in oil price are significant positive effects on stock market volatility in emerging market This results also consistence with theories and practice This also implies that the stock market of emerging economies are going to integrate higher with the international financial markets, therefore they are more impacted from the external shocks such as volatility in 528 | ICUEH2017 oil price, or US stock market In addition, the significant positive effects of foreign portfolio investment flow suggesting that the higher investment from external investors into stock market of emerging economies, the higher volatility they face to This fact defines the important role of external capital flow in emerging markets, where the domestic investors are still strongly impacted by foreign investors Meanwhile, the stock capitalization, real GDP growth rate, and deposit interest rate have significant negative effects on stock market volatility suggesting that the larger stock market, the higher real economic growth, and higher interest rate increase the stability of emerging stock markets The significant negative effects of stock market capitalization on its volatility is consistence with literature since the larger market capitalization the higher efficiency of markets due to the more investors and other products, thus the volatility of market is lower The significant negative effects of real GDP growth rate suggesting that the better conditions of economy induce lower volatility of stock market This result is also consistence with theory and empirical evidences Apparently, the significant negative effects of deposit interest rate on stock market volatility is quite strange to the previous evidences But the higher interest rate means the higher required return requirement, hence decreasing stock prices to lower level, the much of lower stock prices the lower probability of fluctuations The result in model (2) is consistent with model (1) when adding the proxy of macro liquidity excessive The result shows that macro liquidity excessive has strong negative effects on stock market volatility in emerging markets at 1% significant level This result is consistent with our argument, where the excessive in macro liquidity induces lower volatility in stock market due to its favorable impacts on economic conditions and the liquidity of investor’s portfolio The strong statistic significant level of our estimation also confirms the significant of macro liquidity excessive in explaining for stock volatility in emerging markets Next, adding regulatory quality and law indicator and their interaction with macro liquidity excessive to investigate the impacts of institutions on stock market volatility, results are presented in model (3) and (4) in table and Nguyen Phuc Canh & Su Dinh Thanh| 529 Table Regulatory quality, macro liquidity excessive and stock volatility Effects of Regulatory quality (3) Dep Var: Stockvo Effect of association between regulatory quality and macro liquidity excessive (4) Coef P-value Coef P-value 0.1381* 0.0640 0.0851 0.1630 Turnover 0.0500*** 0.0000 0.0547*** 0.0000 Stockcap -0.0132 0.4480 -0.0373** 0.0250 Gdpg -1.0837*** 0.0000 -1.0752*** 0.0000 Inf 0.3137*** 0.0000 0.1763** 0.0270 Stockvo(-1) Interest -0.4481* 0.0780 -0.8164*** 0.0020 M2g 0.5075*** 0.0000 0.5355*** 0.0000 Fpi 2.2199*** 0.0030 3.4142*** 0.0020 Fxvo 6.1953*** 0.0100 11.2846*** 0.0000 Usvo 0.4611*** 0.0000 0.3953*** 0.0000 Oilvo 0.0334 0.4800 0.0803 0.2960 Naliqex -8.1031*** 0.0010 -8.0741*** 0.0030 Reguqua -2.0831* 0.0810 -4.2446** 0.0110 -7.4005** 0.0260 Reguqua*Naliqex No of IVs 27 26 No of Country 32 32 Obs 268 268 AR(2) test (P-value) 0.157 0.745 Hansen test (P-value) 0.827 0.936 Note: *, **, *** denote significant level at 10%, 5%, and 1% respectively Source: author’s calculation 530 | ICUEH2017 Table Rule of law, macro liquidity excessive and stock volatility Effects of Rule of law (5) Dep Var: Stockvo Effect of association between rule of law and macro liquidity excessive (6) Coef P-value Coef P-value Stockvo(-1) 0.2260** 0.0140 0.2383** 0.0280 Turnover 0.0574*** 0.0000 0.0358*** 0.0010 Stockcap -0.0272* 0.0730 -0.0216 0.1600 Gdpg -0.8732*** 0.0000 -0.8625*** 0.0030 Inf 0.1742*** 0.0030 0.1397* 0.0550 Interest -0.6815*** 0.0020 -0.6595*** 0.0020 M2g 0.5172*** 0.0000 0.5338*** 0.0010 Fpi 2.4790*** 0.0010 2.6123*** 0.0010 Fxvo 5.8308*** 0.0030 5.0510** 0.0280 Usvo 0.3253*** 0.0000 0.3102*** 0.0010 Oilvo 0.0964* 0.0760 0.1269* 0.0610 Naliqex -8.8544*** 0.0000 -7.8250*** 0.0010 Rulelaw -2.2633** 0.0270 -1.4410* 0.0720 -5.0029* 0.0980 Rulelaw*Naliqex No of IVs 27 28 No of Country 32 32 Obs 269 268 AR(2) test (P-value) 0.154 0.198 Hansen test (P-value) 0.707 0.680 The results in model (3) and (4) of table and are consistent with previous results, which indicate our evidences are robustness The results in table and show that changes in regulatory quality and law indicator have significant negative impacts on stock market volatility These findings provide evidence that improvements in institutional quality reduce stock market volatility, implying that the crucial solution for the stock market stability is of improving the institutional quality, especially regulation quality Interacting changes in regulatory quality with macro liquidity excessive is significant negative Similarly, the effect of interacting macro liquidity excessive with law indicator Nguyen Phuc Canh & Su Dinh Thanh| 531 on stock market volatility is significant negative These results suggest that the effect of macro liquidity excessive on stock market volatility is enhanced in country with better institutional quality This result also implies that macro liquidity excessive is less risky for country with higher institutional quality and confirms our argument in previous section and contributes to the literature of institutions and its associations with macroeconomic factors Conclusions The relationship between monetary policy and stock market is still argument in the literature, especially in emerging countries Monetary policy is associated with stock market through some critical aspects: stock liquidity and stock stability An increase in money supply can lead to stock volatility due to increased stock prices and then stock market is unstable In contrast, other viewpoint argues that money supply extension lowers input costs of production, especially capital and then stimulates investment and economic activities, which in turn contribute to stock stability The study attempts at estimating the impacts of macro liquidity excessive for 32 emerging markets in the period of 2002 – 2013 Applying Sys GMM estimation, the study finds interesting results: First, the study uses macro liquidity excessive as a proxy for monetary policy and finds that the relationship between macro liquidity excessive and stock volatility is significantly negative This result suggests that macro liquidity excessive lowers stock market volatility in emerging countries, owning to its favorable impacts on economic conditions and the liquidity of investor’s portfolio Second, the impact of macro liquidity excessive is enhanced when interacting with institutional quality variables, namely regulatory quality and law indicator The effects of institutions on stock returns are significantly negative in all specifications That means that institution quality reshapes the effect of macro liquidity excessive on stock market volatility, suggesting that emerging countries must attend to improving institutional quality in order to reduce stock market volatility The results reported in this paper are subject to the usual caveats relating to data quality and availability, and interpretations of econometric modeling It will 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