Institutional quality, macro liquidity excessive and stock market volatility: empirical evidences from emerging markets

Institutional quality, macro liquidity excessive and stock market volatility: Empirical evidences from emerging markets NGUYEN PHUC CANH University of Economics HCMC – canhnguyen@ueh.e

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

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

1 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

recent 2008 global financial crisis, much attention has been withdrawn the stock volatility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

(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 3 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

1 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

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 2 provides a literature review on determinants of stock market volatility and impacts of institutions and macro liquidity excessive Section 3 briefly describes the methodology in estimating macro liquidity excessive and examining effects of institutions on stock market volatility Section

3 also presents our data definitions, calculations, and sources Section 4 presents results and discusses the findings Section 5 provides a summary and concludes this paper

2 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 time-varying 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

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

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

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

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

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

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

that the stock market volatility and the number of publicly available global news stories are strongly linked, the directional link between news and volatility, furthermore, rather

is from news to volatility than vice versa Shi, Ho, and Liu (2016) indicate that specific news sentiment is more significant in quantifying intraday volatility persistence

firm-in the low volatility state than the high state Lansfirm-ing and LeRoy (2014) show that the volatility of the price–dividend ratio increases monotonically with investor information but the relationship between investor information and equity return volatility can be non-monotonic, depending on risk aversion and other parameter values

Previous studies about the impacts of other institutional aspects on stock market volatility find interesting results Hayashida and Ono (2016) examine the effect of stock transaction taxes (STT) on stock return volatility in Japan and find that the STT abolition

in 1999 reduced volatility, and that the tax reforms in 2003 reduced volatility through a cut in the dividend tax Bohl, Reher, and Wilfling (2016) find empirical evidence that the financial crisis was accompanied by an increase in volatility persistence and that this effect was particularly pronounced for those stocks that were subject to short selling constraints

in German While, Papadamou, Sidiropoulos, and Spyromitros (2014) addresses the issue

of impacts of central banks’ transparency on stock market volatility and analytically find

a negative link between stock prices volatility and central bank transparency

In addition, the institution also has effects on stock market volatility through the association with other determinants For instance, the study of Jayasuriya (2005) link post-liberalization volatility with market characteristics and quality of institutions to examine the effect of stock market liberalization on stock return volatility for eighteen emerging markets and find that countries that experienced lower post-liberalization volatility are in general characterized by favorable market characteristics such as higher market transparency and investor protection, and better quality of institutions such as a higher regard for rule of law and lower levels of corruption Therefore, we argue a significant impact of association between institutions with macro liquidity excessive in this study Notably, the institutions will form the behaviors of investors and other sectors

in the economy when they face to the excessive liquidity The better institutional quality means the higher efficiency of market and asset allocations, therefore the favorable effects

of macro liquidity excessive for economic conditions will be exuberated under the better institutional environment, which means that their associations are more favorable for the stability of stock market

In the context of emerging markets, who are on the ways of improving their institution and developing financial markets, the effects of macro liquidity excessive and institutional quality are argued in a stronger stance Since the positive effects of institutions on economic conditions are documented (Young & Sheehan, 2014), the improvement in institution will have stronger impacts on economic factors in some circumstances For instance, P.-H Ho, Lin, and Tsai (2016) find that the improvement in country governance just enhances the effectiveness of banks and then promote the economic growth in developing countries, while it reduces these effects in developed countries due to smaller spaces for improvement Similarly, Yu Wang, Cheng, Wang, and Li (2014) argue that the improvements in institutional quality just have strong effects on promoting economic development only when institutional quality is within a certain range

The works of Kaufmann, Kraay, and Zoido-Lobatón (1999), Kaufmann, Kraay, and Zoido (1999), and later studies under supporting from World bank have classified institutions into six aspects: Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption In which, we argue that the changes in Regulatory quality and Rule of Law will have stronger impacts on stock market volatility due to its thin relations to stock market activities Indeed, the regulatory quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development which including the financial markets (Worlbank, 2015) Thus, the better regulatory quality enhances both of the development of financial markets and the economic conditions, which then induces higher efficiency through lower transaction cost and asymmetric information problem While, the rule of law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence (Worlbank, 2015) In fact, the better quality of contract enforcement, property rights and other factors of rule of law are favorable for lower volatility of stock market

Meanwhile, other aspects of institution including Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, and Control of Corruption are argued with less impact on stock market volatility For example, Yuanyuan Wang and You (2012) find that the corruption will not be a vital constraint on firm growth if financial markets are underdeveloped when they examine the effects of institutional

quality on the aspect of the corruption controlling in China While, the study of Aidt, Dutta, and Sena (2008) find that corruption has a substantial negative impact on economic growth in high institutional quality economies, otherwise it has no impact on economic growth in low quality one Similarly, the study of Perera and Lee (2013) in India finds that the improvements in institutional quality in the aspects of government stability and law and order reduce poverty, however the better institutional quality in the aspects

of corruption controlling, democratic accountability, and bureaucratic quality are worsening of the income distribution In fact, the voice and accountability do not play important role in the political environment at emerging markets While, the government effectiveness will have affects the efficiency of fiscal policies other than the efficiency of stock market At last, the political stability is proxy for the political risk, which is examine

in many previous works thus, we ignore these aspects in this study

3 Methodology and data

3.1 Methodology

In this section, we present our methodology and data to examine impacts of macro liquidity excessive, institution, and their associations on the stock market volatility in 32 emerging markets in the period of 2002 - 2013 In the first step, we estimate the theoretical equilibrium in money market with three main explanatory variables including the level of logarithm of real GDP per capita as a proxy for national income level, GDP deflator as a proxy for inflation under the literature of the quantity theory of money, and deposit interest rate as a proxy for interest rate under the literature of the Keynesian economics:

in which: i and t denote country i and year t; M2 is the ratio of broad money (M2) to GDP, which is the proxy of money equilibrium in the money market, Loggdppc is the logarithm

of GDP per capita, Inf is the GDP deflator, Interest is the deposit interest rate, and 6 is the

residual term Next, we collect residuals and fitted values of M2 from the equation (1), and then we divide each residual for its fitted value and multiple for 100 to scale up as the percentage of money supply differs from its theoretical equilibrium, which is denoted as

Naliqvo Then, we calculate the standard deviation of Naliqvo and define dummy variable, which is the proxy for macro liquidity excessive (Naliqex), as following formula:

789:;3< = 1 0 :1 789:;@* > [C380 789:;@* + 1.5 ∗ 52, 789:;@* ]:1 *2ℎ34I:53 (2)

Following the calculation in equation (2), if Naliqex receives value at one, which means

that the money supply is excessive higher than the theoretical equilibrium and its normal deviation in money market that is best proxy for the macro liquidity excessive

In the second step, following previous works in examining determinants of stock market volatility, such as Beltratti and Morana (2006), Jiang, Rapach, Strauss, Tu, and Zhou (2011), Girardin and Joyeux (2013), Mittnik et al (2015), Chen, Jiang, Li, and Xu (2016), we apply the model with control variables, including stock market turnover, stock market capitalization, real GDP growth rate, GDP deflator, deposit interest rate, the growth rate of M2, the net flow of foreign portfolio investment to GDP, volatility in changes of nominal exchange rate, price volatility in US stock market, and the volatility

in the changes of WTI oil price to examine impacts of regulatory quality, macro liquidity excessive, and their associations on stock market volatility:

J2*.K@*#$ = J2*.K@*#$&'+ LM40*@34#$ + J2*.K.8-#$+ N,-+#$+ /01#$+/0234352#$+ !2+#$+ O-:#$ + O<@*#$ + P5@*#$ + Q:9@*#$ + 789:;3<#$+

in which: Stockvo is stock price volatility in each emerging market, which is the proxy

of stock market volatility; Turnover is the stock market turnover calculated by the ratio

of trade value to market capitalization, which is the proxy of market liquidity; Stockcap is

stock market capitalization calculated by market value of stock market to GDP, which is

the proxy of stock market size; Gdpg is the real GDP growth rate, which is the proxy of real economic growth; Inf and Interest are same as in equation (1); M2g is the growth rate of M2, which is the proxy of money growth rate; Fpi is the ratio of foreign portfolio investment net inflow to GDP, which is the proxy of portfolio investment flow; Fxvo is

the volatility of percentage changes in nominal exchange rate, which is the proxy of the

risk in foreign exchange market; Usvo is price volatility in US stock market, which is the proxy for the effects of US stock market to emerging markets; Oilvo is the volatility in the

changes of WTI oil price, which is the proxy for the changes in commodity market;

Reguqua is the percentage changes in Regulatory quality indicator, which is the proxy for changes in institutional quality; the interaction term between Naliqex and Reguqua is

used to identify the associations between institutional quality and excessive in macro liquidity on stock market volatility; and S is the residual term

In the third step, we use the percentage changes in Rule of law indicator to replace for the changes in Regulatory quality as the proxy for the institutional quality in equation (3) This step aims at testing the effects of rule of law and its association with macro liquidity excessive on stock market volatility and the consistence of our results

3.2 Data

In this paper, we collect data of 32 emerging markets from 2002 to 2013 mainly from the World Development Indicators, World Governance Indicator, and Global Financial Development Database of World bank Our range of data from 2002 to 2013 due to the available of institutional quality indicators from World Governance Indicators, which contains annual continuous series from 2002 In our sample, deposit interest rate is collected from the International Financial Statistics of IMF, while the excessive of macro liquidity is estimated from our method as presented in above sub-section, the volatility in exchange rate is calculated from monthly nominal exchange rate of currency of each emerging market with USD, and the volatility in oil price is calculated by daily WTI oil price All variables, definitions, calculations, and sources are presented in table 1

Table 1

Data definitions and sources

Stockvo The annual price volatility of market index (%) GFDD

Turnover Stock market turnover ratio (%) (trade value to market cap) GFDD

Stockcap The ratio of stock market capitalization to GDP (%) GFDD

Loggdppc Logarithm of real GDP per capita Calculation

from WDI

Interest The deposit interest rate (%) IFS

Fdi The ratio of net portfolio investment inflows to GDP (%) Calculation

from WDI

Variable Definitions Sources

Fxvo The volatility of exchange rate (%): the standard deviation of

monthly changes of nominal exchange rate

Calculation from data of OANDA

Usvo The annual volatility of US stock market (%) GFDD

Oilvo The annual volatility of oil price (%): the standard deviation of daily

changes of WTI oil price * square of trading days in a year

Calculation from WTI oil price

Naliqvo The ratio of the difference between real ratio of M2 to GDP with its

theoretical equilibrium to its theoretical equilibrium

Detail calculations are presented in table 3 and 4

Naliqex

The dummy variable: it receives 0 if Naliqvo is less than (its

theoretical equilibrium + 1.5*its standard deviation), it receives 1 if otherwise

Rulelaw Percentage change in Rule of law indicator (%) Calculation

from WGI

Reguqua Percentage change in Regulatory quality indicator (%) Calculation

from WGI Note: the percentage change in institutional indicators is standardized following formula: TUV$#$W$#XU YWZ[#$\ #U]#^Z$X_`&TUV$#$W$#XU YWZ[#$\ #U]#^Z$X_`ab

c , which is better proxy for changes in institutional quality of a country since each indicator is scaled from -2.5 to +2.5 under the definition and measurement of Worldbank in World Governance Indicators

The data description in table 2 shows that the stock markets at 32 emerging markets

in our sample are important since they have capitalization over 45% of GDP, in average While, their stock markets are a little liquid since the turnover ratio is over 52%, which passes by their capitalization In addition, the average volatility of our sample is little higher than the volatility of US stock market with the value at 22.795% and 19.6928%, respectively