Empirical investigation of efficient market hypothesis in Vietnam stock market

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY LÊ ĐẶNG BÍCH THẢO EMPIRICAL INVESTIGATION OF EFFICIENT MARKET HYPOTHESIS IN VIETNAM STOCK MARKET MASTER THESIS Ho Chi Minh City 2011 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY LÊ ĐẶNG BÍCH THẢO EMPIRICAL INVESTIGATION OF EFFICIENT MARKET HYPOTHESIS IN VIETNAM STOCK MARKET MAJOR: BANKING AND FINANCE MAJOR CODE: 60.31.12 MASTER THESIS Supervisor: Dr Võ Xuân Vinh Ho Chi Minh City 2011 Acknowledgement I would like to express my heartfelt gratitude and deepest appreciation to my research Supervisor, Dr Vo Xuan Vinh for his precious guidance, share of experience, ceaseless encouragement and highly valuable advice and comments throughout the course of my research I would like to thank many of my friends in our group from ebanking class, who have been sharing experience during doing research: Ms Nguyen Thi Kim Ngan, Ms Tran Thuy Huyen, Ms Do Ngoc Anh, Mr Ta Thu Tin, Ms Pham Thi Tuyet Trinh My special gratitude is extended to all instructors and staff at Faculty of Banking and Finance Postgraduate Faculty, University of Economics HoChiMinh City (UEH) for their support and the valuable knowledge during my study in UEH Finally, the deepest and most sincere gratitude goes to my parents, my sisters for their love and support Fulfilling this goal would not have been possible without them i Abstract This research examines the efficiency of Vietnam stock market at weak form level by using daily and weekly observations of market index and eight selected stocks of real estate and seafood processing companies for the period from 2007 to 2010 Parametric and nonparametric tests including auto correlation test, run test, variance ratio test, regression test, ARCH, GARCH (1,1) have been employed in this study All tests’ results fail to support the hypothesis of weak form efficiency with daily data, even in case, returns are adjusted for thin trading However, with weekly data, results obtained from run test and autocorrelation test not completely reject hypothesis of weak form efficiency while result given from variance ratio test fully provides evidence against a random walk Besides that, the findings of no clear calendar effect by examining day of week effect also give the evidence that even if the anomalies existed in the sample period, the practitioners who implement strategies to take advantage of anomalous behavior can cause the anomalies to disappear Keywords: efficient market hypothesis, randomness, calendar effect ii Table of contents Acknowledgement .i Abstract ii Table of contents .iii List of tables v Abbreviations vi INTRODUCTION LITERATURE REVIEW 2.1 The theory of Efficiency Market Hypothesis 2.2 Review of Literature on Weak Form Market Efficiency 2.2.1 Evidence from developed markets 2.2.2 Evidence from developing markets 10 DATA AND METHODOLOGY 14 3.1 Data Description 14 3.2 Methodology 17 3.2.1 Auto Correlation Test 17 3.2.2 Run test 19 3.2.3 Variance ratio test 20 3.2.4 Calendar effect 23 3.2.5 Thin trading adjustment 25 3.2.6 Robustness check 26 EMPIRICAL RESULT 27 4.1 Autocorrelation Test 27 4.2 Runs test 34 4.3 Variance ratio test 38 4.4 Day of week effects 44 iii CONCLUSION 48 REFERENCES 50 Appendix 56 Table A Summary results of all tests for daily returns in 2007 56 Table A Summary results of all tests for thin trading adjusted daily returns in 2007 56 Table A Summary results of all tests for daily returns in 2008 57 Table A Summary results of all tests for thin trading adjusted daily returns in 2008 57 Table A Summary results of all tests for daily returns in 2009 58 Table A Summary results of all tests for thin trading adjusted daily returns in 2009 58 Table A Summary results of all tests for daily returns in 2010 59 Table A Summary results of all tests for thin trading adjusted daily returns in 2010 .59 iv List of tables Table 3.1 Descriptive statistics of daily return 15 Table 3.2 Descriptive statistics of weekly return 15 Table 4.1 Results of autocorrelation coefficients and Ljung-Box Q statistics for daily returns 29 Table 4.2 Results of autocorrelation coefficients and Ljung-Box Q statistics for thin trading adjusted daily returns 31 Table 4.3 Results of autocorrelation coefficients and Ljung-Box Q statistics for weekly returns 32 Table 4.4 Results of autocorrelation coefficients and Ljung-Box Q statistics for thin trading adjusted weekly returns 33 Table 4.5 Results of run test for daily price & return 36 Table 4.6 Results of run test for weekly price & return 37 Table 4.7 Variance ratio test results for daily returns under homoscedasticity and heteroscedasticity 40 Table 4.8 Variance ratio test results for thin trading adjusted daily returns under homoscedasticity and heteroscedasticity 41 Table 4.9 Variance ratio test results for weekly returns under homoscedasticity and heteroscedasticity 42 Table 4.10 Variance ratio test results for thin trading adjusted weekly returns under homoscedasticity and heteroscedasticity 43 Table 4.11 Results of OSL and GARCH (1,1) models for daily returns 46 Table 4.12 Results of OSL and GARCH (1,1) models for thin trading adjusted daily returns 47 v Abbreviations ABT : Ben tre Aqua product Import And Export Joint Stock Company AGF : An Giang Fisheries Import and Export Joint Stock Company ARCH : Autoregressive conditionally heteroscedastic CII : Ho Chi Minh City Infrastructure Investment Joint Stock Company EMH : Efficient Market Hypothesis GARCH : Generalised Autoregressive Conditional Heteroscedasticity FMC : Sao Ta Foods Joint Stock Company HOSE : Ho Chi Minh Stock Exchange ITA : Tan Tao Investment Industry Corporation OSL : Ordinary Least Standard SJS : Song Da Urban & Industrial Zone Investment and Development Joint Stock Company TDH : Thu Duc Housing Development Corporation TS4 : Seafood Joint Stock Company No vi INTRODUCTION Efficient Market Hypothesis (EMH) has been a popular topic for empirical research since the introduction of market efficiency theory by Fama (1965) There are many studies examining whether the stock markets in both developed and emerging countries behave in line with the Efficient Market Hypothesis Most of them focused on weak form efficiency, the lowest level of Efficient Market Hypothesis and the results are mixed On the one hand, some studies reject the hypothesis that the stock markets are in the weak form efficiency (Hoque et al., 2007, Abeysekera, 2001b, Lima et al., 2004) On the other hand, some papers provide the evidence that stock markets in some countries are efficient (Chan et al., 1997, Lee, 1992, Worthington et al., 2004) Although there are many empirical studies devoted to testing for the weak form of Efficient Market Hypothesis in developed and emerging stock markets, there are not many studies examining the weak form of market efficiency in stock returns in Vietnam market The objective of this study is to investigate the existence of weak form of market efficiency in stock returns in Vietnam, and whether there are any anomalies existing in Vietnam stock market The discovery of anomalous patterns in stock returns can help investors take advantage of continuing to hold and adjust their buying and selling strategies accordingly to increase their returns by timing the market Since the establishment on 28 July 2000 with the first security trading center in Ho Chi Minh City (hereinafter called Hose) and only two listed companies that are Refrigeration Electrical Engineering Joint Stock Company (REE) and Saigon Cable and Telecommunication Material Joint Stock Company (SACOM), Vietnam stock market has continued to develop successfully by facing all the challenges and difficulties Over ten years of operation, the total number listed companies have increased significantly to 635 companies with a total market capitalization of VND 650.150 billions (Hose VND 523.933 billions, HNX VND121.217billions) The market capitalization to GDP ratio has been increased year by year It goes up from 0.24% in 2000 to 0.37% GDP in 2010 There are 102 securities companies licensed with a total registered capital of VND 31,866 billion (USD 1,528 million) Total trading accounts are about 1,031,000 (including the 15,000 trading stock accounts of foreign investors), compared to the 2,908 accounts in 2000 The high and rapid growth of Vietnam stock market is, of course, very appealing to domestic and foreign investors Although Vietnam stock market has developed rapidly and taken liberalization process recently, it still possesses many of features that are characteristics of emerging markets like more information asymmetry, thin trading and weak institutional infrastructure, which all together could cause market inefficiency However, not all of emerging markets are entirely inefficient such as some researchers who find the evidence to support the weak form efficiency in developing countries: Lima et al.(2004) found that Hong Kong and A shares for both the Shanghai, Shenzhen stocks exchanges are in weak form efficiency Dickinson et al.(1994) also provided the evidence that Nairobi Stock Exchange is behave in line with the market efficiency and Moustafa (2004) also supported the weak form Efficiency Market Hypothesis of United Arab Emirates stock market… Hence, considering the theoretical and practical significance, the testable implications and conflicting empirical evidence of random walk hypothesis motivate us to have a fresh look at this issue of weak form efficiency in the context of an emerging market, namely Vietnam stock market This study focuses on testing the weak form market efficiency and some anomalies existing in Vietnam stock market To analyze this issue, we require a decomposition of daily and weekly return of Vnindex and shares in real estate and seafood processing companies in Ho Chi Minh stock exchange from Jan 2007 to Dec 2010 Moreover, in the variance equations, all coefficients of the three terms are statistically highly significant through all models in the variance equations, such as γ is significant at 1% for the whole selected stocks δ and ω also significant at 1% level The significant of all three terms strongly supports the validation of GARCH modeling for the data In additional, the finding from day of week effect under thin trading adjusted return has been reported in table 4.12 also show no clear evidence of day of week effect In the conclusion, the findings in day of week effect are highly mixed and show no clear evidence of day of week effect that has long documented in the literature, but the daily effects seem to appear randomly on the other day of the week Different stocks and different models generally provide different results Such as the negative Tuesday effect has been explored for only ABT and positive Friday effect has been found for FMC stock in the OSL model Under the GARCH (1,1) model the day of week effect has been found in the ABT, FMC, AGF, CII stocks also Specially, the positive Friday effect has been found in the FMC, AGF and CII The negative Monday effect has been found in the FMC and AGF ABT has been found negative effect in the Tuesday while the FMC has found the positive Wednesday effect This findings not completely support with the findings of Loc (2006) and Hau (2010) which has found that the negative Tuesday return effect in the week 45 Table 11 Results from OSL & GARCH (1,1) models for daily returns for the day of week effects Year OSL C TUE ABT TS4 FMC 0.00223 0.00084 (0.21960) (0.73240) AGF TDH SJS ITA -0.00450** -0.00229 0.00009 0.00160 -0.00028 -0.00052 -0.00019 (0.02960) (0.47040) (0.89550) (0.24200) (0.96540) CII (0.79150) VNINDEX (0.89200) -0.00487* -0.00289 -0.00078 -0.00357 -0.00210 -0.00209 -0.00175 -0.00100 -0.00187 (0.05770) -0.40390 WED -0.00363 -0.00292 0.00482* 0.00339 (0.15500) (0.39710) (0.09640) THU -0.00342 0.00037 0.00316 (0.18290) (0.91530) (0.27820) (0.73340) (0.39820) (0.61230) (0.93240) (0.90020) (0.79410) 0.00019 0.00358 0.00835***0.00414 0.00019 0.00260 0.00267 0.00389 0.00148 (0.94080) (0.30280) (0.00430) (0.13390) (0.94670) (0.40540) (0.37720) (0.16330) (0.44990) (0.00370) (0.00030) (0.00010) (0.00110) (0.00000) (0.00000) (0.00020) (0.00000) FRI ARCH-LM test (3 lags) Prob(F-statistic)(0.08360) GARCH (1,1) Mean Equation C 0.00178 (0.21340) TUE WED THU FRI (0.78770) (0.19610) (0.46790) (0.50320) (0.56220) (0.72070) (0.33680) -0.00058 -0.00366 -0.00085 0.00133 -0.00026 (0.21670) (0.84050) (0.89440) 0.00094 -0.00244 -0.00158 0.00026 (0.23920) (0.77850) (0.63030) -0.00035 -0.00051 -0.00257 -0.00456** -0.00332** -0.00120 -0.00261 -0.00161 -0.00228 -0.00048 (0.28590) (0.12720) -0.00505***-0.00132 0.00058 (0.22680) (0.01160) -0.00203 -0.00184 0.00033 0.00144 0.00099 -0.00069 (0.01020) (0.64580) (0.29560) (0.81670) (0.01240) (0.45600) (0.12510) (0.62650) (0.37710) (0.87720) (0.51910) (0.64270) (0.60690) -0.00026 -0.00223 -0.00082 0.00511** 0.00363 0.00093 0.00035 0.00022 0.00324 (0.27860) (0.78800) (0.04080) (0.10050) (0.69320) (0.88780) (0.91660) (0.13860) (0.85380) -0.00311 0.00196 0.00358 0.00066 -0.00169 0.00085 0.00121 0.00087 -0.00038 (0.17140) (0.52690) (0.15220) (0.72690) (0.47840) (0.72490) (0.61610) (0.68040) (0.79250) -0.00117 0.00433 0.00725***0.00470** 0.00055 0.00368 0.00247 0.00403* 0.00121 (0.60110) (0.17180) (0.00660) (0.14890) (0.27630) (0.05550) (0.02390) (0.81890) (0.42030) Variance Equation ω 0.00003*** 0.00007* 0.00007** 0.00003***0.00008***0.00004***0.00003***0.00002***0.00001*** (0.00060) ∆ (0.00000) γ (0.08500) (0.01480) (0.00030) (0.00020) (0.00000) (0.00220) (0.00080) (0.00520) 0.15161*** 0.18188***0.16549***0.21356***0.23353***0.22735***0.18768***0.16865***0.18657*** (0.00390) (0.00160) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) 0.80739*** 0.75930***0.75153***0.74942***0.66964***0.73788***0.77179***0.80222***0.78610*** (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (Note: p-value are presented bellowed each coefficient of OSL, GARCH ***, ** and * denote a significance level of 1%, 5% and 10% respectively) 46 Table 12 Results from OSL & GARCH (1,1) models for thin trading adjusted returns for the day of week effects Year OSL C TUE WED THU FRI ABT TS4 FMC AGF TDH SJS ITA CII VNINDEX 0.00237 -0.00112 -0.00485* -0.00220 0.00063 -0.00074 -0.00112 -0.00185 -0.00042 (0.25940) (0.75560) (0.05170) (0.81730) (0.81610) (0.68470) (0.46380) (0.82460) (0.37430) -0.00574* -0.00327 0.00065 -0.00351 -0.00265 -0.00173 -0.00147 -0.00040 -0.00219 (0.05250) (0.85280) (0.31400) (0.48610) (0.70030) (0.70620) (0.90990) (0.41480) (0.51730) -0.00352 -0.00181 0.00773** 0.00646* 0.00052 -0.00298 0.00069 0.00298 0.00102 (0.23360) (0.71970) (0.02730) (0.06290) (0.89190) (0.50690) (0.85780) (0.39980) (0.70510) -0.00337 0.00422 0.00460 0.00151 -0.00264 0.00149 0.00182 0.00023 0.00017 (0.25610) (0.40450) (0.19000) (0.66430) (0.48810) (0.74070) (0.64060) (0.94880) (0.95000) 0.00087 0.00657 0.01125***0.00647* 0.00168 0.00705 0.00460 0.00643* 0.00315 (0.77050) (0.19520) (0.00140) (0.06430) (0.66060) (0.11830) (0.23870) (0.07060) (0.24280) (0.00480) (0.00050) (0.00000) (0.00100) (0.00000) (0.00000) (0.00020) (0.00000) ARCH-LM test (3 lags) Prob(F-statistic)(0.09200) GARCH (1,1) Mean Equation C 0.00248 -0.00404 -0.00498** -0.00274 -0.00036 -0.00397 -0.00221 -0.00350* -0.00012 (0.20130) (0.02540) (0.12770) (0.87350) (0.13880) (0.27120) (0.07330) -0.00626***-0.00158 0.00253 -0.00166 -0.00159 -0.00008 0.00247 0.00161 -0.00078 (0.00810) (0.72370) (0.42460) (0.53850) (0.59220) (0.98020) (0.41310) (0.58450) (0.69740) WED -0.00243 -0.00033 0.00780** 0.00621** 0.00229 0.00030 0.00131 0.00508* 0.00034 (0.31370) (0.94220) (0.01160) (0.48460) (0.93750) (0.64980) (0.08150) THU -0.00357 0.00456 0.00525* 0.00137 -0.00304 0.00242 0.00272 0.00129 -0.00017 (0.17730) (0.31550) (0.08980) (0.35420) (0.52000) (0.38430) (0.64050) (0.93520) -0.00144 0.00537 0.00975***0.00696** 0.00131 0.00585 0.00401 0.00571** 0.00195 (0.58550) (0.27560) (0.00380) (0.15110) (0.19400) (0.04340) (0.13720) TUE FRI (0.03180) (0.59320) (0.01580) (0.70770) (0.93530) (0.86760) (0.36930) Variance Equation ω ∆ 0.00004*** 0.00004 0.00008** 0.00005***0.000079***0.00004***0.00006***0.00004***0.00002** (0.00080) (0.02820) (0.00190) (0.00170) (0.00490) (0.00610) (0.00290) (0.01440) 0.15517*** 0.11389***0.14242***0.18490***0.17152*** 0.17051***0.18313***0.16893***0.17876*** (0.00000) γ (0.28450) (0.00020) (0.00140) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) 0.80070*** 0.87500***0.78884***0.78013***0.77580*** 0.81589***0.78161***0.80258***0.79703*** (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) (0.00000) ( Note: p-value are presented bellowed each coefficient of OSL, GARCH model ***, ** and * denote a significance level of 1%, 5% and 10% respectively) 47 CONCLUSION This study has explored the weak form efficiency in Vietnam stock market by using daily, weekly return of market index and eight selected stocks of two sectors including real estate and seafood processing companies for the period from 2007 to 2010 We also follow the model proposed by Miller et al (1994) to remove the problem of thin or infrequent trading which could seriously bias the results of empirical studies on market efficiency in this research By utilizing the parametric and non parametric tests, we find that Vietnam stock market is in the weak form inefficiency with daily data even in case of return adjusted for thin trading However, with weekly data, the hypothesis of weak form efficiency is not rejected for run test and autocorrelation test when returns are adjusted for thin trading While the result of variance ratio test fully fails to support the null hypothesis of random walk These findings not completely consistent with the findings of Loc (2006) who found that Vietnam stock market is in the weak form inefficiency under both daily and weekly data for all test results Our findings for day of week effect show, with the exception of ABT, FMC, AGF and CII, that there is no such effect on the other studied stocks Though, each individual stock has each day which return is positive or negative Hence one of the most important findings is that in most cases the daily anomalies documented on selected stocks with relative high correlation are not the same Furthermore, no common daily can be observed among the selected stocks The above findings imply that patterns of daily effects discovered in the selected stocks partly depend on the data itself For that reason the findings are mixing and no clear evidence to conclude the calendar effect has been existed in Vietnam stock markets These findings not conform to the previous study of Loc (2006), suggesting that the return on Tuesday is significant negative 48 One of the most interesting in our findings that all tests’ results of four sub periods including the data of 2007, 2008, 2009 and 2010 have been consistent with the finding of full sample period The findings of four sub periods once again consolidate our findings as the weak form inefficiency Vietnam stock market In conclusion, the predominant outcome of this research is that the Vietnam stock market is inefficient in the weak form, even in case, the calendar effect does not clearly exist Moreover, information in the inefficiency market does not reflect in prices as it should be Hence, many information intermediaries will gather information and make profit as there is a big demand for information In addition, the perception that prices not fully reflect some available information can lead investors to adopting portfolio strategies designed to reap abnormal profits exploiting the information inefficiency The limitation of our study is that this does not cover all of the stocks listed on HOSE Hence, further studies might choose to expand the number of stocks in the sample and consider different frequency data like 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level of 1%, 5% and 10% respectively Table A Summary Results of all tests for daily thin adjusted returns in 2007 Stock ABT TS4 Autocorrelation Run test Variance ratio test OSL GARCH (1,1) Return homoscedasticity heteroscedasticity No *** *** *** Positive in Tue Positive in Tue ** *** *** *** No No Negative in Mon, FMC No *** *** *** Positive in Potive in Wed, Mon, Wed, Fri Thu, Fri AGF TDH SJS ITA ** * *** ** No * *** No *** *** *** *** *** *** *** *** Positive in Wed, Fri No No No CII ** VNINDEX *** * No *** *** *** *** Positive in Positive in Fri Wed, Fri No No Positive in Wed, Fri No No No Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively 56 Table A Summary Results of all tests for daily returns in 2008 Stock Autocorrelation Run test Variance ratio test OSL GARCH (1,1) Price Return homoscedasticity heteroscedasticity ABT *** *** *** *** *** No No TS4 *** *** *** *** *** No Negative in Mon FMC *** *** *** *** *** No Negative in Mon AGF *** *** *** *** *** Negative in Mon Negative in Mon TDH *** *** *** *** *** Negative in Mon Negative in Mon SJS *** *** *** *** *** No Negative in Mon ITA *** *** *** *** *** No No CII *** *** *** *** *** No No VNINDEX *** *** *** *** *** No Negative in Mon Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively Table A Summary Results of all tests for daily thin adjusted returns in 2008 Stock ABT TS4 Autocorrelation Run test Variance ratio test OSL Return homoscedasticity heteroscedasticity No *** *** *** Negative in Tue * *** *** *** No GARCH (1,1) Negative in Tue Negative in Mon No ** * *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** Negative in Mon Negative in Mon Positive in Positive in Wed,Fri Wed,Thu, Fri Positive in Wed, Fri Positive in Wed, Fri No No No No No No CII ** VNINDEX No *** *** *** *** *** *** Positive in Fri No FMC AGF TDH SJS ITA Negative in Mon Positive in Wed,Fri No Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively 57 Table A Summary Results of all tests for daily returns in 2009 Stock Autocorrelation Run test Variance ratio test OSL GARCH (1,1) Price Return homoscedasticity heteroscedasticity ABT *** * No *** *** No No TS4 *** *** *** *** *** No No FMC *** * ** *** *** No No AGF *** *** *** *** *** No No TDH *** ** * *** *** No No SJS *** *** *** *** *** No No ITA *** *** *** *** *** No No CII *** *** *** *** *** No No VNINDEX *** *** *** *** *** No No Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively Table A Summary Results of all tests for daily thin adjusted returns in 2009 Stock ABT TS4 FMC AGF TDH SJS ITA Autocorrelation Run test Variance ratio test OSL Return homoscedasticity heteroscedasticity No No *** *** Negative in Tue No *** *** *** Positive in Fri No ** * *** ** CII * VNINDEX * GARCH (1,1) Negative in Tue Positive in Fri ** *** * *** *** *** *** *** *** *** *** *** *** *** *** Negative in Mon Positive in Wed & Negative in Mon Positive in Wed & Fri Thu &Fri Positive in Wed & Fri Positive in Wed & Fri No No No No No No *** No *** *** *** *** Positive in Fri No Negative in Mon Positive in Wed & Fri No Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively 58 Table A Summary Results of all tests for daily returns in 2010 Stock Autocorrelation Run test Variance ratio test OSL GARCH (1,1) Price Return homoscedasticity heteroscedasticity ABT No No No *** *** No TS4 *** *** *** *** *** Negative in Wed Negative in Wed FMC ** No No *** *** Positive in Fri AGF ** No No *** *** Negative in Tue No TDH ** No No *** *** No No SJS ** No No *** *** No No ITA No No No *** *** No Negative in Mon CII No No No *** *** No No * *** *** No No VNINDEX ** *** Negative in Wed Positive in Fri Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively Table A Summary Results of all tests for daily thin adjusted returns in 2010 Stock ABT TS4 FMC AGF TDH SJS ITA Autocorrelation Run test Variance ratio test OSL Return homoscedasticity heteroscedasticity No No *** *** Negative in tue No *** *** *** No No *** * ** ** CII ** VNINDEX *** No No No No No No *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** GARCH (1,1) Negative in Tue Negative in Wed Negative in Mon Negative in Mon Positive in Wed & Positive in Wed & Fri Thu& Fri Positive in Wed &Fri Positive in Wed &Fri No No No No No No Positive in Fri No Negative in Mon Positive in Wed & Thu& Fri No Note: ***, ** and * denote a significance level of 1%, 5% and 10% respectively 59