Whether momentum or contrarian phenomenon exist in vietnam stock market

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY -o0o - TA THU TIN WHETHER MOMENTUM OR CONTRARIAN PHENOMENON EXIST IN 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 iii 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 iv 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 v 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 vi 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 D12: Estimation of Beta of Loser portfolio in J=3/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnL Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnL 84 Table D21: Estimation of Beta of Winner portfolio in J=6/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnW Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnW 85 Table D22: Estimation of Beta of Loser portfolio in J=6/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnL Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnL 86 Table D31: Estimation of Beta of Winner portfolio in J=9/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnW Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnW 87 Table D32: Estimation of Beta of Loser portfolio in J=9/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnL Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnL 88 Table D41: Estimation of Beta of Winner portfolio in J=12/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnW Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnW 89 Table D42: Estimation of Beta of Loser portfolio in J=12/K=3 strategy Model Summary Model R a Predictors: (Constant), ReturnVNI ANOVAb Model Regression Residual Total a Predictors: (Constant), ReturnVNI b Dependent Variable: ReturnL Coefficientsa Model (Constant) ReturnVNI a Dependent Variable: ReturnL 90 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 MCofL MCofW Paired Samples Correlations Pair MCofL & MCofW Paired Samples Test Pair MCofL MCofW 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 MCofL MCofW Paired Samples Correlations Pair MCofL & MCofW Paired Samples Test Pair MCofL MCofW 91 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 Paired Samples Correlations Pair MCofL & MCofW Paired Samples Test Pair MCofL MCofW 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 Paired Samples Correlations Pair MCofL & MCofW Paired Samples Test Pair MCofL MCofW 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 Paired Samples Statistics Pair PBofL PBofW Paired Samples Correlations Pair PBofL & PBofW Paired Samples Test Pair PBofL PBofW 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 Pair PBofL PBofW Paired Samples Correlations Pair PBofL & PBofW Paired Samples Test Pair PBofL PBofW 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 Paired Samples Statistics Pair PBofL PBofW Paired Samples Correlations Pair PBofL & PBofW Paired Samples Test Pair PBofL PBofW 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 Pair PBofL PBofW Paired Samples Correlations Pair PBofL & PBofW Paired Samples Test Pair PBofL PBofW 94 ... 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. .. 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... following research questions: Based on historical stock price data in Vietnamese stock market, would momentum (or contrarian) strategy make abnormal profit? Why does Vietnamese stock market have momentum/ contrarian