Whether momentum or contrarian phenomenon exist in vietnam stock market

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CIT -o0o - TA THU TIN WHETHER MOMENTUM OR CONTRARIAN PHENOMENON EXIST VIETNAM STOCK MARKET MAJOR: FINANCE – BANKING MAJOR CODE: 60.31.12 MASTER THESIS ADVISOR: Ph.D TRAN PHUONG NGOC THAO HO CHI MINH CITY, 2011 ACKNOWLEDGEMENT At first, I would like to express my deep gratitude to my instructor, Dr Tran Phuong Ngoc Thao for her intensive guidance and valuable suggestions during time of my study I would like to thank Dr Vo Xuan Vinh for valuable comments and suggestions he share with me In addition, I also give my appreciation to all of my lecturers at Faculty of Banking and Finance, University of Economics Hochiminh City for their teaching and knowledge during my master course My sincere thank goes to Nguyen Hiep Phat, my colleague at Au Viet Securities, he spent a lot of time to help me make a software program to process raw data in this thesis Finally, I am thankful to my family for giving me facilitation to complete my thesis i ABSTRACT This thesis investigates whether momentum or contrarian phenomenon exist on Vietnamese Stock Market over the period from January 2005 to June 2011 We employ the famous methodology by Jegadeesh and Titman (1993) to calculate the profit of momentum and contrarian strategies which were built base on the historical return of 424 stocks listed on Ho Chi Minh Stock Exchange and Ha Noi Stock Exchange We found that all 16 trading contrarian strategies always make abnormal profit with statistical significance at the level of 10% The most profitable contrarian strategy with portfolio based on month formation and month holding has a average monthly return of 2,829% (equivalent to annually return of 33,95%) with significance level of 2% Our research demonstrates that the abnormal profit on trading contrarian strategy can not be accounted for by beta-risk as well as market size But we found a evidence of P/B ratio explaining contrarian phenomenon on Vietnamese Stock Market Key words: Momentum; Contrarian strategies ii TABLE OF CONTENTS ACKNOWLEDGEMENT……………………………………………………………… i ABSTRACT…………………………………………………………………………… ii TABLE OF CONTENTS……………………………………………………………… iii LIST OF FIGURES…………………………………………………………………… vi LIST OF TABLES…………………………………………………………………… vii ABBREVIATIONS…………………………………………………………………… viii Introduction………………………………………………………………………… 1.1 Overview of Momentum and Contrarian strategies…………………………… 1.2 Research Objective……………………………………………………………… 1.3 Research Methodology and Scope……………………………………………… 1.4 Thesis Structure………………………………………………………………… 1.5 Vietnamese Stock Market……………………………………………………… Literature Review………………………………………………………………… 2.1 Efficient Market Hypothesis…………………………………………………… 2.2 Momentum Strategy…………………………………………………………… 2.3 Contrarian Strategy…………………………………………………………… 15 Data Collection and Research Method………………………………………… 18 3.1 Data Collection………………………………………………………………… 18 3.1.1 Stock Prices…………………………………….……………………… 18 3.1.2 Adjusted Stock Prices………………………………………………… 19 3.1.3 P/B ratio………………………………………………………………… 21 3.1.4 Market Capitalization…………………………………………………… 22 3.2 Research Method……………………………………………………………… 22 Empirical Result…………………………………………………………………… 24 4.1 Raw Data Processing………………………………………………………… 24 4.2 Empirical Result……………………………………………………………… 28 4.3 Why does the contrarian phenomenon exist in Vietnam stock market? .32 4.4 Some factors may account for the contrarian phenomenon in Vietnam Stock Market………………………………………………………………………… 35 4.4.1 Market Risk…………………………………………………………… 36 4.4.2 Firm Size……………………………………………………………… 39 4.4.3 Price to Book…………………………………………………………… 40 Conclusion………………………………………………………………………… 42 5.1 Main findings………………………………………………………………… 42 5.2 Implications of Research……………………………………………………… 43 5.3 Limitations of Research……………………………………………………… 44 REFERCENCES……………………………………………………………………… 45 APPENDIX…………………………………………………………………………… 48 Table A1: List of 424 investigated stocks……………………………………………………48 Table B1-Table B16: The average monthly return of Winner and Loser Portfolios in 16 strategies…………………………………………………………………… 59 Table C1-Table C16: The average monthly return of Loser portfolio compare to the one of Winner portfolio in 16 strategies………………………………… 75 Table D11: Estimation of Beta of Winner portfolio in J=3/K=3 strategy……………… 83 Table D12: Estimation of Beta of Loser portfolio in J=3/K=3 strategy……………… 84 Table D21: Estimation of Beta of Winner portfolio in J=6/K=3 strategy……………… 85 Table D22: Estimation of Beta of Loser portfolio in J=6/K=3 strategy……….……… 86 Table D31: Estimation of Beta of Winner portfolio in J=9/K=3 strategy……………….87 Table D32: Estimation of Beta of Loser portfolio in J=9/K=3 strategy…………………88 Table D41: Estimation of Beta of Winner portfolio in J=12/K=3 strategy…………… 89 Table D42: Estimation of Beta of Loser portfolio in J=12/K=3 strategy……………….90 Table E1: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=3/K=3 strategy………………………………… 91 Table E2: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=6/K=3 strategy………………………………… 91 Table E3: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=9/K=3 strategy………………………………… 92 Table E4: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=12/K=3 strategy……………………………… 92 Table F1: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=3/K=3 strategy……………………… 93 Table F2: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=6/K=3 strategy……………………… 93 Table F3: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=9/K=3 strategy……………………….94 Table F4: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=12/K=3 strategy…………………… 94 LIST OF FIGURES Figure 1.1 VN-Index Chart over the period from July 2000 to September 2011………….6 Figure 3.1 Formation and Holding periods in two strategies…………………………… 23 Figure 4.1 The screen of the Analyzing Stock Price Data program after importing data from Excel file…………………………………………………………….25 Figure 4.2 The screen of the Analyzing Stock Price Data after stocks are ranked in descending order on the basis of their average monthly returns…………… 26 Figure 4.3: The screen of Stock Grouping program shows the Winner and Loser portfolios, and their average returns…………………………………………… 27 LIST OF TABLES Table 3.1 Adjusting price of KDC share………………………………………………….… 20 Table 3.2 Adjusting price of OPC share………………………………………………….… 21 Table 4.1 The average return of Winner and Loser Portfolios and their difference in J=3/K=3 Strategy (Formation Period: months; Holding Period: months)…… ……28 Table 4.2 Summary of the average monthly return of loser and winner portfolio; and their differences (profitability of contrarian strategies) for 16 strategies over the period from 01/2005 to 06/2011……………………………………………….… 30 Table 4.3 Monthly and annually profitability of 16 contrarian strategies are ranking in descending and their significances……………………………………… 31 Table 4.4 Beta coefficient after perform regression……………………………………… 38 Table 4.5 The comparison in average market capitalization between loser and winner portfolios and their differences……………………………………… .39 Table 4.6 The comparison in average P/B ratio between loser and winner portfolios…41 vii ABBREVIATIONS CAPM Capital Asset Pricing Model EMH Efficient Market Hypothesis HOSE Ho Chi Minh City Stock Exchange HNX Ha Noi Stock Exchange VND Vietnam Dong viii CHAPTER 1: INTRODUCTION 1.1 Overview of Momentum and Contrarian Strategies In 1970, Efficient Market Hypothesis (EMH) developed by Professor Eugene Fama proclaimed that in the efficient market no one could consistently beat the market and stock prices follow a random walk Thus, future prices of stocks could not be predicted from their past prices, it means that the abnormal return from trading should be zero However, a lot of investors and researchers have doubts about the efficient market hypothesis both empirically and theoretically They always try to find some abnormal returns to prove the inefficiency of the markets Consequently, forecasting the price movements in stock markets has become a major challenge for investors, brokers and speculators Studying the movement of stock prices become one of the most attractive fields of research due to its commercial applications and benefits it offers Recently, there are many researchers and traders have studied stock price predictions such as Fundamental Analysis, Technical Analysis, CANSLIM, etc… And one of the most attractive trading strategies is momentum (and contrarian) strategy The momentum strategy appeared firstly in the 1960s However, it became widely known only in the early 1990s after Narasimham Narasimhan Jegadeesh and Sheridan Titman published their study Momentum and contrarian strategies are two opposite investment strategies which use historical price/return data in order to forecast the future development of stock performance to make excess returns Momentum investing strategy, also sometimes known as “Trend following”, believes that stocks which have good performance in the past will keep doing so in the future, it buys (go long) stocks that have outperformed in the recent past, and short sell (go short) those that have underperformed over the same period In contrast, a contrarian strategy believes that stocks which have good historical performance will be bad in the future, so it suggests short selling past winning stocks and buying past losing stock The contrarian strategy was introduced first Table C15: The average monthly return of Loser portfolio compare to the one of Winner portfolio in (J=12/K=9) strategy Paired Samples Statistics Mean Pair ReturnL N 00157 -.01960 ReturnW 57 57 Std Deviation 057363 064130 Std Error Mean 007597 008494 Paired Samples Correlations N Pair ReturnL & ReturnW 57 Correlatio n 889 Sig .000 Paired Samples Test Pair Paired Differences95% Confidence Interval of the Std Std Error Difference Deviatio Mean Mean Lower Upper n ReturnL ReturnW 0211789 0293178 0038832 0133999 0289580 t 5.454 df Sig (2-tailed) 56 000 Table C16: The average monthly return of Loser portfolio compare to the one of Winner portfolio in (J=12/K=12) strategy Paired Samples Statistics Mean Pair ReturnL N 00391 -.01798 ReturnW 54 54 Std Deviation 051285 060498 Std Error Mean 006979 008232 Paired Samples Correlations N Pair ReturnL & ReturnW 54 Correlatio n 897 Sig .000 Paired Samples Test Pair Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviatio Mean Mean Lower Upper n ReturnL ReturnW 0218944 0268918 0036595 0145544 0292345 t 5.983 df 53 Sig (2tailed) 000 Table D11: Estimation of Beta of Winner portfolio in J=3/K=3 strategy Model Summary Model Adjusted R R a 751 R Square 564 Std Error of Square the 558 133270 a Predictors: (Constant), ReturnVNI ANOVA Model Sum of Regression Squares 1.60 Residual 1.24 Total 2.85 a Predictors: (Constant), ReturnVNI b df Mean Square1.60 70 018 F 90.56 Sig a 000 71 b Dependent Variable: ReturnW Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) ReturnVNI 130 1.20 a Dependent Variable: ReturnW 016 126 Coefficients Bet a t 751 8.25 9.51 Sig .000 000 Table D12: Estimation of Beta of Loser portfolio in J=3/K=3 strategy Model Summary Model Adjusted R R R Square Square 642 a 801 a Predictors: (Constant), ReturnVNI the 637 ANOVA Model Regression Sum of Squares Std Error of b df 877 490 70 1.36 a Predictors: (Constant), ReturnVNI 71 Residual 083664 Total Mean Square F 877 007 125.32 Sig a 000 b Dependent Variable: ReturnL Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) -.105 010 ReturnVNI 888 079 a Dependent Variable: ReturnL Coefficients Bet a t 801 10.615 11.19 Sig .000 000 Table D21: Estimation of Beta of Winner portfolio in J=6/K=3 strategy Model Summary Model Adjusted R R a 774 R Square 599 Std Error of Square the 593 124380 a Predictors: (Constant), ReturnVNI ANOVA Model Sum of Regression Squares 1.54 Residual 1.03 Total 2.58 a Predictors: (Constant), ReturnVNI b df Mean Square1.54 67 015 F 100.09 Sig a 000 68 b Dependent Variable: ReturnW Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) ReturnVNI 089 1.18 a Dependent Variable: ReturnW 015 118 Coefficients Bet a t 774 5.90 10.00 Sig .000 000 Table D22: Estimation of Beta of Loser portfolio in J=6/K=3 strategy Model Summary Model Adjusted R R a 825 R Square Std Error of Square 680 the 675 080793 a Predictors: (Constant), ReturnVNI ANOVA Model Mean Square 929 437 67 007 1.36 a Predictors: (Constant), ReturnVNI 68 Sum of Regression Squares 929 b Residual df Total F 142.31 Sig a 000 b Dependent Variable: ReturnL Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) -.069 010 ReturnVNI 914 077 a Dependent Variable: ReturnL Coefficients Bet a t 825 7.108 11.92 Sig .000 000 Table D31: Estimation of Beta of Winner portfolio in J=9/K=3 strategy Model Summary Model Adjusted R R a 758 R Square 575 Std Error of Square the 568 130335 a Predictors: (Constant), ReturnVNI ANOVA Model Sum of Regression Squares 1.46 Residual 1.08 Total 2.55 a Predictors: (Constant), ReturnVNI b df Mean Square1.46 64 017 F 86.41 Sig a 000 65 b Dependent Variable: ReturnW Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) ReturnVNI 084 1.15 a Dependent Variable: ReturnW 016 124 Coefficients Bet a t 758 5.21 9.29 Sig .000 000 Table D32: Estimation of Beta of Loser portfolio in J=9/K=3 strategy Model Summary Model Adjusted R R a 840 R Square 705 Std Error of Square the 701 080927 a Predictors: (Constant), ReturnVNI ANOVA Model Sum of Regression Squares 1.00 Residual 419 b df Total 1.42 a Predictors: (Constant), ReturnVNI Mean Square1.00 64 007 F 153.12 Sig a 000 65 b Dependent Variable: ReturnL Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) -.064 010 ReturnVNI 956 077 a Dependent Variable: ReturnL Coefficients Bet a t 840 6.454 12.37 Sig .000 000 Table D41: Estimation of Beta of Winner portfolio in J=12/K=3 strategy Model Summary Model Adjusted R R a 851 R Square 725 Std Error of Square the 720 097188 a Predictors: (Constant), ReturnVNI ANOVA Model Sum of Regression Squares 1.51 Residual 576 b df Total 2.09 a Predictors: (Constant), ReturnVNI Mean Square1.51 61 009 F 160.67 Sig a 000 62 b Dependent Variable: ReturnW Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) ReturnVNI 076 1.17 a Dependent Variable: ReturnW 012 093 Coefficients Bet a t 851 6.19 12.67 Sig .000 000 Table D42: Estimation of Beta of Loser portfolio in J=12/K=3 strategy Model Summary Model Adjusted R R a 801 R Square Std Error of Square 641 the 635 091797 a Predictors: (Constant), ReturnVNI ANOVA Model Mean Square 918 514 61 008 1.43 a Predictors: (Constant), ReturnVNI 62 Sum of Regression Squares 918 b Residual df Total F 108.95 Sig a 000 b Dependent Variable: ReturnL Coefficients Model Standardized Unstandardized Coefficients B Std Error a (Constant) -.056 012 ReturnVNI 916 088 Coefficients Bet a t 801 a Dependent Variable: ReturnL 90 4.836 10.43 Sig .000 000 Table E1: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=3/K=3 strategy Paired Samples Statistics Pair Mea n 1289.444 1430.366 MCofL MCofW N Std Std Error Deviation Mean 1596.163 192.155 1435.878 172.859 69 69 Paired Samples Correlations N Pair MCofL & MCofW Correlatio n -.190 69 Sig .118 Paired Samples Test Pair Mean MCofL MCofW 140.9217 Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviation Mean Lower Upper 2341.095 281.834 703.3143 t 421.470 df -.500 68 Sig (2tailed) Table E2: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=6/K=3 strategy Paired Samples Statistics Pair Mea n 1400.753 MCofL N 66 1402.674 MCofW Std Std Error Deviation 1405.245 Mean 172.973 1282.203 66 157.828 Paired Samples Correlations N Pair MCofL & MCofW 66 Correlatio n -.217 Sig .080 Paired Samples Test Pair MCofL MCofW Mean Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviation Mean Lower Upper 1.9209 2097.925 258.236 517.6553 513.813 t -.007 df 65 Sig (2tailed) 994 619 Table E3: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=9/K=3 strategy Paired Samples Statistics Pair MCofL MCofW Mea n 1465.792 1587.707 N 63 63 Std Std Error Deviation Mean 1370.127 172.619 1313.207 165.448 Paired Samples Correlations N Pair MCofL & MCofW Correlatio n -.268 63 Sig .033 Paired Samples Test Pair Mean MCofL MCofW 121.9156 Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviation Mean Lower Upper 2137.173 269.258 660.1557 416.324 t -.453 df 62 Sig (2tailed) 652 Table E4: Average Market Capitalisation of Loser portfolio compare to Market Capitalisation of Winner portfolio in J=12/K=3 strategy Paired Samples Statistics Pair MCofL MCofW Mea n 1468.525 N 60 1653.206 Std Std Error Deviation 1377.376 Mean 177.818 1406.394 60 181.564 Paired Samples Correlations N Pair MCofL & MCofW 60 Correlatio n -.262 Sig .043 Paired Samples Test Mean Pair MCofL MCof 184.6811 Paired Differences 95% Confidence Interval of the Std Std Difference Lower Upper Deviation Error Mean 2211.609 285.517 386.638 756.0005 t -.647 df 59 Sig (2tailed) 520 Table F1: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=3/K=3 strategy Paired Samples Statistics Mean Pair PBofL N 1.99833 2.92003 PBofW 57 57 Std Std Error Deviation Mean 1.365765 185857 1.647080 224139 Paired Samples Correlations N Pair PBofL & PBofW 57 Correlatio n 740 Sig .000 Paired Samples Test Mean Pair PBofL PBofW -.921700 Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviation Mean Lower Upper 1.117211 1520332 1.226640 -.616760 t -6.062 df 56 Sig (2tailed) 000 Table F2: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=6/K=3 strategy Paired Samples Statistics Mean Pair PBofL PBofW N 1.90377 3.21502 54 54 Std Std Error Deviation Mean 1.055387 143620 1.875397 255209 Paired Samples Correlations N Pair PBofL & PBofW 54 Correlatio n 791 Sig .000 Paired Samples Test Mean Pair PBofL PBof 1.311250 Paired Differences 95% Confidence Interval of the Std Std Error Deviatio Mean Lower Upper n 1.223925 -.977182 1665551 1.645317 t -7.873 df 53 Sig (2tailed) 000 Table F3: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=9/K=3 strategy Paired Samples Statistics Mean Pair PBofL N 1.84920 3.34068 PBofW 51 51 Std Std Error Deviation Mean 998641 139837 2.153513 301552 Paired Samples Correlations N Pair PBofL & PBofW 51 Correlatio n 842 Sig .000 Paired Samples Test Mean Pair PBofL PBofW 1.491476 Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviatio Mean Lower Upper n 1.418890 1986843 1.890545 1.092407 t -7.507 df Sig (2- 50 000 Table F4: The average P/B ratio of Loser portfolio compare to the average P/B ratio of Winner portfolio in J=12/K=3 strategy Paired Samples Statistics Mean Pair PBofL N 1.91292 3.48364 PBofW 48 Std Std Error Deviation 1.101871 Mean 48 2.224323 159041 321053 Paired Samples Correlations N Pair PBofL & PBofW 48 Correlatio n 881 Sig .000 Paired Samples Test Mean Pair PBofL PBofW 1.570720 Paired Differences 95% Confidence Interval of the Std Std Error Difference Deviatio Mean Lower Upper n 1.357217 1958975 1.964815 1.176625 t -8.018 df 47 Sig (2tailed) 000 ... three main following objectives: Investigating whether the momentum or contrarian phenomenon exist on the Vietnamese Stock Market? Determining factors account for the momentum or contrarian phenomenon. .. month formation period 4.3 Why does the contrarian phenomenon exist in Vietnam stock market? Both the investigated period and present time, in Vietnam stock market almost individual investors tend... main factors that can be used to explain for this finding 4.4 Some factors may account for the contrarian phenomenon in Vietnam Stock Market In this thesis we propose three alternative tests for