Can investment strategies beat the market

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM NETHERLANDS VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS CAN INVESTMENT STRATEGIES BEAT THE MARKET? By HUYNH NHAT TRINH MASTER OF ARTS IN DEVELOPMENT ECONOMICS Ho Chi Minh City, August 2016 ABSTRACT Over the past three decades, many anomalies, known as investment strategies, have been documented on the global financial markets However, from 2000s to now, several scholars have shown considerable changes in the magnitude of these excess returns Therefore, the purpose of this thesis is to examine whether these investment strategies can be applied in Vietnam stock market or not In addition, this thesis also provides the explanation of difference in returns By processing the data set containing of 689 listed firms in Ho Chi Minh Stock Exchange (HOSE) and Ha Noi Stock Exchange (HNX) during the period 2006 to 2014, this thesis examines three investment strategies including value investing, momentum investing and size investing The evidences in Vietnam stock market confirms the existences of statistically value premium and size premium during the normal economic condition During the financial crisis period, the results also confirm the value and size premium but they are not significant in the statistical point of view In term of momentum investment strategy, it cannot be applied in reality when the results shown that the existences of momentum premium are not clear during the normal economic condition and financial crisis period Traditional risk based measures are also examined to find the explanation of anomalies The results indicated that volatility can be used to explain the excess return but in term of beta, it cannot be used The behavioral arguments are not covered in this thesis, so that an implication for future research refers towards the under and over-reaction in the value investment strategy, the size investment strategy, and the momentum investment strategy i ACKNOWLEDGEMENT First of all, I would like to express my utmost acknowledgement and appreciation towards my supervisor – Dr Ngo Minh Hai – for all the motivation, patience and support he has given me to complete this thesis This thesis would not have been completed without his support He supported me when I was struggling with my thesis in order to get me on the right way again and to improve it Besides, I would like to thank my family, especially my Mom, Dad and my girlfriend for the continuous support they have given me throughout my time in business school I could not have done it without them Last but not least, it has been a long and fun learning process and I would like to thank my fellow graduate students at K20 for a memorable semester Thanks to teachers and staffs in Vietnam – Netherlands Programme for their help during my process ii ABBREVIATIONS AMEX American Stock Exchange BV/MV Book value over market value ratio CAPM Capital Asset Pricing Model CF/P Cash flow to price D/P Dividend to price E/P Earning per share to price EPS Earnings per share FYE Fiscal year end GNP Gross National Product HML High Minus Low HNX Ha Noi Stock Exchange HOSE Ho Chi Minh Stock Exchange HPR Holding period return LIBOR London Interbank Offered Rate NASDAQ National Association of Securities Dealers Automated Quatations NYSE New York Stock Exchange P/B Price to book value P/E Price over earning per share U.K United Kingdom U.S United State WRSS Weighted relative strength strategy iii TABLE OF CONTENTS ABSTRACT i ACKNOWLEDGEMENT ii ABBREVIATIONS iii TABLE OF CONTENTS iv LIST OF TABLES vi CHAPTER 1: INTRODUCTION 1.1 Problem Statement Error! Bookmark not defined 1.2 Research Questions Error! Bookmark not defined 1.3 Thesis Outline Error! Bookmark not defined CHAPTER 2: LITERATURE REVIEW .Error! Bookmark not defined.0 2.1 Momentum Investment Strategy And Its Explanation Error! Bookmark not defined.0 2.1.1 International Evidence of Momentum Premium Error! Bookmark not defined.0 2.1.2 Explanations of Momentum Strategy Error! Bookmark not defined.4 2.2 Value Investment Strategy and Its Explanation Error! Bookmark not defined.7 2.2.1 International Evidence of Value Premium .Error! Bookmark not defined.7 2.2.2 Explanations of Value Strategy .2Error! Bookmark not defined 2.3 Size Investment Strategy and Its Explanation 23 2.3.1 Size Effect and Its Explanations Error! Bookmark not defined.3 2.3.2 Variations of Size Effect Error! Bookmark not defined.4 2.3.3 Concentration of size effect in the smallest firms Error! Bookmark not defined.7 CHAPTER 3: DATA AND METHODOLOGY Error! Bookmark not defined 3.1 Data Source Error! Bookmark not defined.8 3.2 Methodology Error! Bookmark not defined.9 3.2.1 Value Investment Strategy .Error! Bookmark not defined.9 3.2.2 Momentum Investment Strategy 32 3.2.3 Size Investment Strategy 36 iv CHAPTER 4: Empirical Results and Discussion Error! Bookmark not defined.8 4.1 Value Investment Strategy Error! Bookmark not defined.8 4.2 Size Investment Strategy Error! Bookmark not defined 4.3 Momentum Investment Strategy Error! Bookmark not defined.2 CHAPTER 5: CONCLUSION, LIMITATION AND IMPLICATIONS FOR FUTURE RESEARCH Error! Bookmark not defined 5.1 Conclusion .Error! Bookmark not defined 5.1.1 Value Investment Strategy 44 5.1.2 Size Investment Strategy 44 5.1.3 Momentum Investment Strategy Error! Bookmark not defined 5.2 Limitations and Implication For Future Research Error! Bookmark not defined REFERENCES Error! Bookmark not defined APPENDICES 52 v LIST OF TABLES Table 2.1: Average monthly returns of small and large firms reported by Horowitz et al (2000a) Error! Bookmark not defined Table 4.1: Average monthly return and charactersitic of portfolios composed of value and growth portfolio (holding period of year) Error! Bookmark not defined Table 4.2: Average monthly return and charactersitic of portfolios composed of value and growth portfolio (holding period of years) Error! Bookmark not defined Table 4.3: Average monthly return and charactersitic of portfolios composed of large cap and small cap portfolio (holding period of year) .Error! Bookmark not defined Table 4.4: Average monthly return and charactersitic of portfolios composed of large cap and small cap portfolio (holding period of years) .Error! Bookmark not defined Table 4.5: Average monthly return and charactersitic of portfolios composed of winner and loser portfolio (6-6 month strategy) .Error! Bookmark not defined vi CHAPTER 1: INTRODUCTION 1.1 Problem statement In the view of the Market Efficiency Theory, obtaining an abnormal return would be impossible since all publicly available and private information has been already reflected into market price1 Therefore, the investors could not profit from employing any stock picking technique or investment strategy Recently, researchers have also reported a number of anomalies, which are conjectured as an evidence of mispricing, a trait of market inefficiency The mispricing is documented when a change in stocks price could not be explained or linked to any recently relevant information occurs in the market Recent findings on the debates of investment strategies have suggested that firms with some specific fundamental characteristics such as low price-to-earnings, low market capitalization, could earn an abnormal return2 These findings are therefore addressed as evidence that contrast to the efficient market theory However, the validity of evidence supporting the existence of inefficient markets is a fierce debate among researchers and hence, has not yet reached a consensus A potential issue is that the evidence of an existence of inefficient markets should be consistent over a long period Otherwise, these could be considered as a product of data snooping3 However, recent empirical results have reported substantial discrepancies in premium of investment strategies since the original study4 Even though, the inability to explain and the dispersion of these evidence raise the question of their validity Additionally, the reliability of these results during the financial crisis, to some degree, is unveiled Fama(1970) Basu (1977), Fama and French (1992), Lakonishok, Shleifer, Vishny (1994) In generally accepted study practice, an initial hypothesis is developed based on economic rationale Then, the statistical test is objectively conducted with selected data to confirm or reject the null hypothesis However, data snooping means that data is examined with intend to develop the hypothesis instead of developing the hypothesis first Fama (1998) Page | In order to address the issues mentioned above, this thesis aims to find rigorous empirical evidence supporting the mispricing hypothesis We imply several investment strategies with a mechanism based on the behavioral literature about the Value effect, the Momentum effect, and the Size effect in Vietnam stock market over the period from 2006 to 2014 Furthermore, the effect of the financial crisis of 2007-2009 on these investment strategies is also examined 1.2 Research questions In short, this thesis will answer the following questions: Whether could portfolios of value investing, size investing, or momentum investing generate abnormal returns on Vietnam stock market over the period from 2006 to 2014? Whether could portfolios of value investing, size investing or momentum investing be applicable during the period of financial crisis? What could be the reasonable explanations for these anomalies in Vietnamese stock market? 1.3 Thesis outline In answering the above problem statements, the thesis consists of the following chapters: Chapter 1: Introduction Chapter 2: Literature review Chapter 3: Data and methodology Chapter 4: Empirical results and discussion Chapter 5: Conclusions, limitation and implications for future research Page | CHAPTER 2: LITERATURE REVIEW 2.1 Momentum investment strategy and its explanations The early literature on market inefficiency regarding to strategies is known as relative strength strategies (momentum strategy) which takes the long position of past winners and the short position of past losers The first study about momentum was conducted by Levy’s (1967), but its results are controversial Then, many investors were still in 1990s and are still in 2010 applying the relative strength as one stock picking criteria 2.1.1 International evidence of momentum premium  Momentum returns in the U.S In 1993, an academic paper contending the idea that momentum strategy is able to produce an abnormal return is documented by Jegaddees and Titman Using the data on NYSE and AMEX stocks exchange, they conducted an examination of 32 momentum strategies with different formation periods5 and holding periods during 1965 to 1989 In their studies, it was found that the returns from all those strategies were positive and were statistically significant over to 12 holding periods This scholar also contended that generally the strategies with long formation period and short holding period generated higher return compared to others strategies Furthermore, when Jegaddees and Titman test the performance of the months/6 months strategy within sub-sample categorized by firm size (large cap, medium cap, and small cap) and by Beta (high beta, medium beta and low beta stocks), they found that all the returns were positive and had approximately the same magnitude to average return of entire sample Therefore, they concluded that the performances of momentum strategies are not limited to any specific sub-samples of stocks To evaluate the persistence of momentum effect over the medium term, Jegaddesh and Titman tracked the average performance of the portfolio in each of 36 months after formation date Stocks was selected basis of return over past J months J months is also called as formation period Page | Table 4.5: Average monthly return and characteristic of portfolios composed of winner portfolio and loser portfolio (6-6 month strategy) Rebalance year months - months strategy 2007 2008 2009 2010 2011 2012 2013 Winner portfolio (%) 61.6 -13.5 41.9 -27.9 -11.1 -1.1 18.0 Loser portfolio (%) 17.4 14.4 40.1 -19.3 -22.1 -4.2 31.0 Panle A: Return T- test statistic 4.3 -4.1 0.3 -2.2 2.4 0.9 -2.8 p-value 0.01% 0.01% 76.51% 3.01% 2.18% 36.96% 0.58% Variance - Winer Portfolio 3,792.9 1,425.1 1,763.8 978.9 985.9 614.6 1,233.6 Variance - Losser Portfolio 914.4 1,535.0 1,658.8 469.5 1,747.5 953.9 1,996.8 Beta- Winer Portoflio 0.16 0.39 0.37 0.20 0.09 0.14 0.06 Beta - Losser Portfolio 0.22 0.41 0.31 0.26 0.13 0.08 0.04 Page | 41 CHAPTER 5: CONCLUSIONS, LIMITATION AND IMPLICATIONS FOR FUTURE RESEARCH 5.1 Conclusion 5.1.1 Value Investment Strategy Previous studies documented that value portfolios generated superior returns as compared to the growth portfolios in various settings The thesis on value – growth investment strategy in Vietnam stock market confirm towards pervious evidence In other words, the value – growth investment strategy could be applied in the reality in Vietnam stock market when the value portfolios outperformed the growth portfolios during the normal economic condition During the financial crisis period, the value investing is also applicable when value premium existed However, from a statistical point of view, there is indifference in average yearly returns obtained between value and growth portfolios during the financial crisis periods, meanwhile the differences are significant for the period of a normal economic condition In summary, the portfolio manager could use the value-growth investments strategy for seeking the abnormal return but they should be careful when using this strategy during the period of financial crisis In addition, this strategy could be applied for the shortterm, middle-term and long-term investment For the explanation of value premium, the differences could be attributed to risk factors when the variances of value portfolio are higher than the growth portfolio Nonetheless, in the measurement of CAPM, it could not be used to explain the difference when the beta of growth portfolios are higher than value portfolio for the almost rebalance years from 2006 to 2013 This might be an evidence to support “beta is dead”27 5.1.2 Size investment strategy Many of the early empirical studies documented a significant and consistent size premium And the empirical research on Vietnam stock market supports this idea when the size premium exists in the period from 2006 to 2013 However, during the financial crisis (2008), the size investment strategy did not work In statistical point of view, there is an indifference in the average yearly return between the large-cap portfolios and then, it raises the concern about whether this strategy could work out of sample or not In summary, even the size premium exists for the short-term, middle-term and long-term investment, the portfolio manager should be careful when use this strategy in reality Page | 42 For the explanation of size premium, the differences could be attributed to the risk factors when the variances of large cap portfolio are higher than the small cap portfolio However, in term of beta, it could not help to explain the difference in return Again, this might be the evidence supporting the idea “beta is dead” 5.1.3 Momentum investment strategy In contrast to the value and size investment strategy, the application of this strategy in the reality is not clear when the momentum premium exists only for 2007, 2009, 2011 and 2012 For the explanation, the difference could not be explained by variance and beta Hence, it could not be attributed to the risk factors 5.2 Limitation and implications for future research In this thesis, I studied value premium, size premium and momentum premium on an equalized construction by which previous studies have researched on this subject of matter However, the markets, the economic setting and the time-frame in which this thesis occurred vary considerably One of the major limitations in this thesis is the sample size The Vietnam stock market was established for 15 years and the data set only is available from 2006 to 2013 Therefore, the period that is examined could not provide a representative sample for the Vietnam financial markets as a whole In this thesis, I used the equal-weighted approach to constructing the portfolios for value-growth investment, size, and momentum investment strategy Therefore, the domination of blue-chips is eliminated and all stocks will have the same magnitude of influences on the portfolio However, the value-weighted is used in some scholars and this method sometimes produces the different findings compared to the equal-weighted approach An implication for future research on this matter unfolds in studying portfolios based on the value-weighted approach in order to scrutinize which approach provide investors the highest returns Another limitation of the thesis is the explanation of difference in returns In this thesis, I only used the volatility and the beta to represent the risk factors Meanwhile the Fama French factors model, factors model and factors models have been not considered in this thesis Hence, the implication for future research is that we can use the Fama French model to check whether those models could be used to explain the difference in average yearly return or not In addition, the behavioral explanation of the premium is also not 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Growth Portfolio 3,142 1,309 5,614 2,042 2,826 33,071 203,651 Variance - Value Portfolio 63,549 1,053 3,600 2,644 8,288 18,735 49,483 Beta-Growth Portfolio 0.36 0.39 0.27 0.20 0.12 0.11 0.10 Beta - Value Portfolio 0.29 0.32 0.24 0.16 0.11 0.11 0.07 Sorted by P/B 2006 2007 2008 2009 2010 2011 2012 Growth portfolio (%) -17.8 -46.4 15.9 -25.5 -8.5 93.8 82.5 Value portfolio (%) 132.4 -33.6 24.2 -26.9 25.8 178.9 137.4 -3.5 -1.8 -0.6 0.2 -3.3 -4.6 -3.0 Variance - Growth Portfolio 3,151 1,483 6,100 3,506 6,229 18,993 12,285 Variance - Value Portfolio 69,305 968 5,415 1,865 7,370 29,906 38,388 Beta-Growth Portfolio 0.41 0.42 0.32 0.23 0.16 0.13 0.12 Beta - Value Portfolio 0.31 0.32 0.25 0.16 0.10 0.10 0.07 HOLDING PERIOD - YEAR 2006 2007 2008 2009 2010 2011 Growth portfolio (%) -32.3 -64.9 32.3 -27.2 -3.2 137.5 Value portfolio (%) 108.3 -59.1 37.0 8.9 81.9 177.7 -4.9 -0.7 -0.3 -3.4 -6.9 -1.3 Variance - Growth Portfolio 1,920 1,965 11,415 2,488 4,691 95,543 Variance - Value Portfolio 30,644 1,147 7,742 7,882 14,775 37,405 Beta-Growth Portfolio 0.34 0.35 0.25 0.18 0.11 0.11 Beta - Value Portfolio 0.27 0.29 0.23 0.14 0.11 0.10 Sorted by P/B 2006 2007 2008 2009 2010 2011 Growth portfolio (%) -25.3 -61.9 44.9 5.5 16.9 133.1 Value portfolio (%) 94.2 -55.2 58.3 4.1 68.9 214.9 T- test statistic -3.9 -0.9 -0.7 0.1 -4.0 -3.4 Variance - Growth Portfolio 2,398 2,019 15,573 7,812 9,218 38,660 Variance - Value Portfolio 34,142 1,022 9,863 4,424 12,858 42,201 Beta-Growth Portfolio 0.39 0.38 0.294 0.21 0.15 0.12 Beta - Value Portfolio 0.28 0.28 0.224 0.13 0.10 0.09 HOLDING PERIOD - YEAR Sorted by P/E T- test statistic T- test statistic Sorted by P/E T- test statistic Page | 50 2006 2007 2008 2009 2010 Growth portfolio (%) -62.3 -58.0 88.7 -8.1 5.4 Value portfolio (%) 22.8 -50.6 86.4 55.0 107.7 T- test statistic -5.7 -0.8 0.1 -4.1 -6.1 Variance - Growth Portfolio 951 2,883 33,646 3,647 8,557 Variance - Value Portfolio 7,765 2,024 18,596 18,168 27,863 Beta-Growth Portfolio 0.32 0.32 0.22 0.17 0.10 Beta - Value Portfolio 0.25 0.26 0.20 0.13 0.10 Sorted by P/B 2006 2007 2008 2009 2010 Growth portfolio (%) HOLDING PERIOD - YEAR Sorted by P/E -49.1 -52.2 115.0 20.6 38.3 Value portfolio (%) 7.1 -48.3 116.5 42.3 92.7 T- test statistic -3.3 -0.4 0.0 -1.6 -3.1 Variance - Growth Portfolio 2,196 3,135 49,928 8,766 16,747 Variance - Value Portfolio 9,314 1,329 26,239 8,078 22,851 Beta-Growth Portfolio 0.36 0.35 0.27 0.20 0.14 Beta - Value Portfolio 0.26 0.26 0.19 0.12 0.09 HOLDING PERIOD - YEAR 2006 2007 2008 2009 Growth portfolio (%) -54.6 -37.4 143.7 0.6 Value portfolio (%) 55.9 -27.3 144.3 94.4 T- test statistic -3.5 -0.7 0.0 -4.1 Variance - Growth Portfolio 1,640 5,881 42,325 5,931 Variance - Value Portfolio 36,378 5,273 30,002 41,459 Beta-Growth Portfolio 0.30 0.30 0.21 0.16 Beta - Value Portfolio 0.24 0.24 0.19 0.12 Sorted by P/E Sorted by P/B 2006 2007 2008 2009 Growth portfolio (%) -30.3 -29.1 177.2 33.7 Value portfolio (%) 38.7 -32.3 187.2 71.2 T- test statistic -2.0 0.2 -0.2 -2.1 Variance - Growth Portfolio 5,777 6,908 88,229 16,617 Variance - Value Portfolio 41,380 2,144 45,354 14,105 Beta-Growth Portfolio 0.34 0.33 0.25 0.20 Beta - Value Portfolio 0.24 0.23 0.18 0.11 Page | 51 2006 2007 2008 Growth portfolio (%) -35.8 -25.4 186.3 Value portfolio (%) 119.3 -0.5 198.4 -4.7 -1.5 -0.2 Variance - Growth Portfolio 3,857 5,112 100,417 Variance - Value Portfolio HOLDING PERIOD - YEAR Sorted by P/E T- test statistic 38,431 8,164 78,669 Beta-Growth Portfolio 0.28 0.28 0.20 Beta - Value Portfolio 0.22 0.22 0.17 Sorted by P/B 2006 2007 2008 Growth portfolio (%) 5.4 -18.7 197.2 Value portfolio (%) 76.9 -17.7 243.9 T- test statistic -1.9 -0.1 -0.9 Variance - Growth Portfolio 15,822 7,467 126,560 Variance - Value Portfolio 41,844 3,382 65,027 Beta-Growth Portfolio 0.32 0.31 0.24 Beta - Value Portfolio 0.22 0.21 0.16 HOLDING PERIOD - YEAR 2006 2007 Growth portfolio (%) -14.4 -13.1 Value portfolio (%) 161.6 20.3 Sorted by P/E T- test statistic -4.5 -1.5 Variance - Growth Portfolio 5,871 12,163 Variance - Value Portfolio 53,001 14,167 Beta-Growth Portfolio 0.27 0.27 Beta - Value Portfolio 0.20 0.20 Sorted by P/B 2006 2007 Growth portfolio (%) 26.9 -12.7 Value portfolio (%) 114.2 0.9 -2.0 -0.7 Variance - Growth Portfolio 20,331 14,238 Variance - Value Portfolio 57,583 6,034 Beta-Growth Portfolio 0.30 0.30 Beta - Value Portfolio 0.20 0.19 T- test statistic Page | 52 HOLDING PERIOD - YEAR 2006 Sorted by P/E Growth portfolio (%) Value portfolio (%) T- test statistic -2.8 167.1 -4.6 Variance - Growth Portfolio 7,232 Variance - Value Portfolio 45,474 Beta-Growth Portfolio 0.25 Beta - Value Portfolio 0.19 Sorted by P/B 2006 Growth portfolio (%) 47.0 Value portfolio (%) 125.4 T- test statistic -1.7 Variance - Growth Portfolio 31,666 Variance - Value Portfolio 46,818 Beta-Growth Portfolio 0.29 Beta - Value Portfolio 0.18 APPENDIX 2: Average monthly return and characteristic of portfolios composed of large cap and small cap portfolio 2006 2007 2008 2009 2010 2011 2012 Large Cap portfolio (%) -15.3 -46.6 10.4 -27.1 -0.8 108.4 84.0 Small Cap portfolio (%) 152.3 -38.0 14.0 -21.9 12.5 160.8 171.7 -4.1 -1.1 -0.3 -0.7 -1.3 -2.6 -2.2 Variance - Large Cap Portfolio 2,806 1,504 5,186 2,877 5,293 17,835 15,609 Variance - Small Cap Portfolio 63,600 1,368 4,411 2,899 8,423 38,630 217,430 Beta- Large Cap Portfolio 0.44 0.46 0.36 0.27 0.21 0.19 0.17 Beta - Small Cap Portfolio 0.25 0.24 0.16 0.10 0.06 0.05 0.03 HOLDING PERIOD - YEAR 2006 2007 2008 2009 2010 2011 Large Cap portfolio (%) -27.2 -62.1 43.8 -0.4 23.9 126.8 Small Cap portfolio (%) 106.7 -62.8 38.1 13.4 49.2 196.2 -4.7 0.1 0.4 -1.1 -1.9 -2.9 Variance - Large Cap Portfolio 2,125 1,956 10,468 5,778 7,712 28,079 Variance - Small Cap Portfolio 30,040 905 7,548 8,827 14,133 50,065 Beta- Large Cap Portoflio 0.43 0.42 0.33 0.25 0.20 0.18 Beta - Small Cap Portfolio 0.23 0.21 0.14 0.09 0.06 0.04 HOLDING PERIOD - YEAR Sorted by Size T- test statistic Sorted by Size T- test statistic Page | 53 2006 2007 2008 2009 2010 Large Cap portfolio (%) -48.5 -49.8 101.8 23.7 34.9 Small Cap portfolio (%) 12.3 -57.4 87.3 51.3 75.5 T- test statistic -3.8 0.9 0.5 -1.7 -2.4 Variance - Large Cap Portfolio 2,169 3,086 27,802 7,379 12,911 Variance - Small Cap Portfolio 8,055 843 25,195 15,926 23,902 Beta- Large Cap Portoflio 0.40 0.39 0.31 0.24 0.19 Beta - Small Cap Portfolio 0.21 0.19 0.12 0.08 0.05 HOLDING PERIOD - YEAR 2006 2007 2008 2009 Large Cap portfolio (%) -27.8 -28.0 145.5 39.4 Small Cap portfolio (%) 41.5 -41.7 158.2 82.7 T- test statistic -2.1 1.1 -0.4 -1.9 Variance - Large Cap Portfolio 5,758 6,813 33,759 15,687 Variance - Small Cap Portfolio 36,655 1,495 49,853 31,687 Beta- Large Cap Portoflio 0.38 0.37 0.29 0.24 Beta - Small Cap Portfolio 0.20 0.17 0.11 0.07 HOLDING PERIOD - YEAR 2006 2007 2008 Large Cap portfolio (%) 9.2 -13.0 187.5 Small Cap portfolio (%) 89.7 -20.0 228.0 T- test statistic -2.2 0.5 -0.7 Variance - Large Cap Portfolio 15,891 7,888 95,296 Variance - Small Cap Portfolio 37,692 4,039 119,302 Beta- Large Cap Portoflio 0.36 0.35 0.28 Beta - Small Cap Portfolio 0.18 0.15 0.10 HOLDING PERIOD - YEAR Sorted by Size Sorted by Size Sorted by Size 2006 2007 Large Cap portfolio (%) 34.1 -6.6 Small Cap portfolio (%) 145.4 5.6 -2.4 -0.6 Variance - Large Cap Portfolio 20,260 14,142 Variance - Small Cap Portfolio 61,350 8,949 Beta- Large Cap Portoflio 0.34 0.34 Beta - Small Cap Portfolio 0.17 0.14 HOLDING PERIOD - YEAR Sorted by Size T- test statistic Page | 54 HOLDING PERIOD - YEAR 2006 Sorted by Size Large Cap portfolio (%) 48.9 Small Cap portfolio (%) 158.4 T- test statistic -2.4 Variance - Large Cap Portfolio 32,425 Variance - Small Cap Portfolio 47,719 Beta- Large Cap Portoflio 0.33 Beta - Small Cap Portfolio 0.16 APPENDIX 3: Average monthly return and characteristic of portfolios composed of winner and loser portfolio Rebalance year months - months strategy 2007 2008 2009 2010 2011 2012 2013 Winner portfolio (%) 61.6 -13.5 41.9 -27.9 -11.1 -1.1 18.0 Loser portfolio (%) 17.4 14.4 40.1 -19.3 -22.1 -4.2 31.0 Panle A: Return T- test statistic 4.3 -4.1 0.3 -2.2 2.4 0.9 -2.8 p-value 0.01% 0.01% 76.51% 3.01% 2.18% 36.96% 0.58% Variance - Winner Portfolio 3,792.9 1,425.1 1,763.8 978.9 985.9 614.6 1,233.6 Variance - Loser Portfolio 914.4 1,535.0 1,658.8 469.5 1,747.5 953.9 1,996.8 Beta- Winner Portoflio 0.16 0.39 0.37 0.20 0.09 0.14 0.06 Beta - Loser Portfolio 0.22 0.41 0.31 0.26 0.13 0.08 0.04 Page | 55 ... the magnitude of these excess returns Therefore, the purpose of this thesis is to examine whether these investment strategies can be applied in Vietnam stock market or not In addition, this thesis... premium of investment strategies since the original study4 Even though, the inability to explain and the dispersion of these evidence raise the question of their validity Additionally, the reliability... stocks price also was existing over the long term, at least based on their study on the American market  Momentum returns on European market For the European market, the first study was acknowledged