THE APPLICATION OF CUMULATIVE PROSPECT THEORY IN BUILDING OPTIMAL PORTFOLIO IN VIETNAMESE STOCK MAKRKET

1 FOREIGN TRADE UNIVERSITY FACULTY OF BUSINESS ADMINISTRATION -*** GRADUATION THESIS Major: International Business Administration THE APPLICATION OF CUMULATIVE PROSPECT THEORY IN BUILDING OPTIMAL PORTFOLIO IN VIETNAMESE STOCK MAKRKET Student name: Nguyễn Thị Thu Hằng Student code: 1001020040 Class: A8 Intake: 49 Supervisor: M.Sc Le Thi Thu Ha Noi, May 2014 ACKNOWLEDGEMENTS Firstly, I express my deep sense of gratitude to M.Sc Le Thi Thu for her inspiring guidance, scholarly interpretations and valuable criticisms throughout the course of my thesis I am gratefully obliged to the faculty of Business Administration at Foreign Trade University, for approving the title and supporting me to conduct the study I extend my sincere thanks to Ms Pham Mai Phuong Linh, Hoang Xuan Huy, Nguyen Viet Phuong, for their support Especially, I also thank my close friends Ngo Bach Thien Huong, Le Ngoc Hai, Nguyen Tung Minh, Ngo Thi Thu Huong, Nguyen Lan Anh, Pham Hai Yen and Nguyen Phuong Thanh for all their encouragement throughout the completion of the work Above all, many thanks to mom, dad, and my younger brother and sisters who always stimulate and spend all love for me Nguyen Thi Thu Hang Class: A8, Faculty of Business Administration, Intake: 49, Foreign Trade University CONTENT LIST OF ABBREVIATIONS BFT CPT EMH EU GDP PT SD VN-Index Behavioral Finance Theory Cumulative Prospect Theory Efficient Market Hypothesis Expected Utility Theory Gross Domestic Product Prospect Theory Stochastic Dominance Vietnamese Index of Stock Price LIST OF TABLES Table 5.1 Table 5.2 Table 5.3 Table 6.1 Table 7.1 Table 7.2 Table 7.3 Table 7.4 HOSE’s listing summary recorded in April 2014 HNX’s listing summary recorded in April 2014 Level of knowledge of individual investors in 2000-2007 in Viet Nam c and d List of joint hypotheses in testing the curvature of value function Result of Tasks I, II and III List of joint hypotheses in testing the curvature of probability weighting function Result of Tasks IV and V 40 41 45 54 57 58 59 59 LIST OF EXHIBITS Exhibit 2.1 Exhibit 2.2 Exhibit 2.3 Exhibit 2.4 Exhibit 2.5 Exhibit 3.1 Exhibit 5.1 Exhibit 5.2 Exhibit 5.3 The value function assumed by Prospect Theory The value function for different values of The probabilities distortion functions, and Prospect Theory S-shape function and Reverse S-shape function Schematic depiction of the class of probability weighting function The process of portfolio management VN-index in the period of 2004 to 2014 HNX-index in the period of 2004 to 2014 Dow Jones and VN-index from the end of 2008 to the end of 2010 10 15 18 26 42 42 49 CHAPTER 1: INTRODUCTION 1.1 The rationale of the research Individual wealth management, especially individual optimal portfolio has been relatively new but expanding field that attract more and more the concern of financial researchers Numerous studies regarding this domain are carried out over the world, including standard finance models and behavioral finance model The major characteristics of private investors are small capital size, lack of technology support and affected by behavioral biases Small scale of investments prevents individual investors from selecting many securities for their portfolio The shortage of supporting high-tech tools poses the problem of how individual practioners apply optimal portfolio models Lastly, behavioral biases are the indepth reason for investors’ wrong decisions and mistakes while constituting portfolio In three above features, individual behaviors is considered as the most typical difference, which divides optimal portfolio models into two approaches: one based on Standard Finance paradigm, and one based on Behavioral Finance paradigm Standard Finance paradigm proposes Markowitz Portfolio Theory, which is considered as the best mathematical model for optimizing portfolio This model of portfolio optimization bases on the assumption that individual investors are analytically sophisticated and knowledgeable about markets By assumption, private investors in such these constituted models make optimal decision in a rational manner However, MPT is strongly criticized by behavioral finance scholars According to Bernstein (1998), “evidence reveals repeated patterns of irrationality, inconsistency and incompetency in the ways human being arrive at decisions and choices when faced with uncertainty” Nofsinger (2001) asserts that assumption of rationality and unbiasedness of economic participants has been drubbed by psychologist for a long time As the mandatory requirement of financial research, behavioral finance researchers advance substitute models of individual portfolio management The major studies specializing in portfolio optimization emphasize that (i) investors are normal (Statman, 2005); (ii) they use S-shape utility function (Kahneman and Tversky, 1979) that reflects their attitudes toward risk; (iii) investors are also affected by their emotions (Lopes, 1987) Derived from these realistic assumptions, a vast number of researches regarding individual portfolio have conducted in over the world The principal contribution of individual optimal portfolio is with no doubt Cumulative Prospect Theory initiated by Kahneman and Tversky (1992) – the keystone of Behavioral Finance Theory Moving focus on Vietnamese stock market, due to the great number of private investors to the financial market, individual wealth management is still a pivotal domain According to the interview result of Tran Dac Sinh – chairman of HOSE, by the end of the year 2013, there were 1.3 million trading accounts comprise 1,282,071 accounts of domestic individual investors compared with 5,081 accounts of domestic institutional investors, 13,950 accounts of foreign individual investors and the 1,631 remaining of foreign institutional investors In addition, during the development of the Vietnamese stock market, there is an increasing number of private investors picking stock and allocating their portfolio instead of short-term trading Nevertheless, in reality, Vietnamese individual investors are not equipped by strategic models helping them to overcome their emotional and cognitive biases Many of them simplify portfolio selection process by using heuristics approach because they find models of optimal portfolio sophisticate and difficult to apply Other individual investors designing portfolio based on available models are still unable to optimize their wealth because of models’ implausible assumption of rationality This status is one of the reasons causing the speculative bubble crash in 2007, even maybe threatening the sustainability of Vietnamese stock market Thus, the matter of wrong individual portfolio investment decisions affecting on the sustainability and the enhancement of Vietnamese stock market is the rationale of my thesis “The application of Cumulative Prospect Theory in building optimal portfolio for individual investors in Vietnamese stock market” 1.2 Objectives of the research Behavioral Finance paradigm is a theoretical and empirical system that includes numerous sub-theories such as Heuristics, Prospect Theory, Cumulative Prospect Theory, behavioral biases, disposition effect, etc Each relative theory, which has its mathematic forms, can be a base constructing models of portfolio optimization Due to limited time and a lack of research capacity, my thesis will only concentrate on Cumulative Prospect Theory – the keystone of Behavioral Finance Theory, and the most simple model, which is so-called “Static Portfolio Optimization model”, with one risky asset and one free-risk asset in one-period economy My thesis aims to answer two key research questions Are hypotheses of Cumulative Prospect Theory compatible with Vietnamese individual investors’ characteristics? If the model is suitable for privately applying, are there any recommendations to realize the models in practical investments? 1.3 Scope of the research Individual investors were picked up for the survey since they were more likely to have limited knowledge about application of the Behavioral Finance or Cumulative Prospect Theory in portfolio construction, hence prone to make psychological mistakes The influence has primarily analyzed in term of whether behavioral factors affect the portfolio management behavior of individual investors 1.4 Research methodology This study follows the methodology of survey research design of which data processing was supported by quantitative approach As Holme and Solvang (1996), a quantitative method is formalized, structured and is characterized by selectivity as well as a distance from the source of information The approach concentrates on numerical observations and attempts to generalize a phenomenon through formalized analysis of observed data where statistic indicators are indispensable parts On the other hand, a qualitative approach is formalized to a lesser extent is directed at testing whether the information is valid The typical feature of this method is the use of verbal description instead of purely numerical data and aims at creating a common understanding of the subject in research In my thesis, by using descriptive survey, primary data is collected for quantitative and qualitative analyses Stochastic Dominance is used to interpret individual decisions between two options 1.5 Research structure Except Introduction, Conclusion and Appendices, the thesis is structured as follows: • Chapter 2: Cumulative Prospect Theory • Chapter 3: Building Optimal Portfolio for individual investors • Chapter 4: Static Portfolio Optimization Model Under Cumulative Prospect Theory • Chapter 5: Introduction to Vietnamese individual investors in the stock market • Chapter 6: Data and Methodology • Chapter 7: Empirical results • Chapter 8: Recommendations CHAPTER 2: CUMULATIVE PROSPECT THEORY 2.1 Introduction to Cumulative Prospect Theory Cumulative Prospect Theory (Kahneman and Tversky, 1992) is one of the most important theories of Behavioral Finance Paradigm CPT has assistance for behavioral researchers to understand and explain individual decision-making process under uncertainty Hence, CPT has many important implications in constructing portfolio Cumulative Prospect Theory is the second version of Prospect Theory (Kahneman and Tversky, 1979) Both of them are considered as two of the best theories to explain individual decision under risk In essence, there are many such relative theories as Expected Value, Expected Utility having great contribution to the financial decision-making process under conditions of risk, but each of them has its own limitations Expected value is calculated by multiplying its payoff with its probability This model fails in predicting the final choice because the value was not always directly related to its precise monetary worth, but rather dependent on other psychological factors Daniel Bernoulli (1738) releases works discovering this contradiction and advancing an alternative to the expected value notion Throughout his experiments, Bernoulli recognizes that the value a person attaches to an outcome can be influenced by such factors as the likelihood of winning, or probability, etc Expected Utility, however, the notion of Expected Utility also fails in predicting allloss choices In 1979, Kahneman and Tversky provided an alternative, empirically supported theory of choice, so-called Prospect Theory, one that accurately describes how people actually go about making their decision In short, the theory predicts that individuals tend to be risk averse in a domain of gains and relatively risk-seeking in a domain of losses However, there are some theoretical problems in PT The main problem is that the functional form of PT violates “stochastic dominance” (Kahneman and Tversky, 1979, pp 283±284) Stochastic dominance requires that a shift of probability mass from bad outcomes to better outcomes leading to an products – Small supply and large demand – Leader or Laggard – Institutions’ sponsorship – Market direction) CAN SLIM, developed by William O’Neil – the co-founder of Investor’s Business Daily, is a philosophy of screening, purchasing and selling common stocks This investment method is describe in his highly recommended book “How to make money in stock” O’Neil emphasizes the importance of choosing stocks of which earnings per share ratio (EPS) in in the most recent quarters have grown on throughout the last year The growth rate of a company‘s EPS is heated controversial debate, but the CAN SLIM system proposes no less than 18-20% By using statistic analysis method, O’Neil found that in the period of 1953 to 1993, three-quarters of the 500 topperforming securities in the US stock market showed a 70% increase in quarterly EPS prior to a major price rise O’Neil also says that: “18-20% growth is just a rule of thumb, the truly spectacular earners usually demonstrate growth of 50% or more.” Nonetheless, some cautions must be mentioned – for example: shenanigans or red flags The system strongly asserts that investors should know how to recognize the manipulation of company performance, thus, investors must have underlying understanding about the company CAN SLIM also thanks to the importance of annual earnings growth The system indicates that a growing company should present high annual earnings growth rates (annual EPS) in each of the last five years It is pivotal for fundamental investors who adopt the mindset that investing of buying a piece of a business, becoming an owner of it Annual earnings growth within the 25-50% range is plausible for value investors in their long-term investment O'Neil's third criterion for a good company is that it has recently undergone a change, which is often necessary for a company to become successful Whether it is a new management team, a new product, a new market, or a new high in stock price, O'Neil found that 95% of the companies he studied had experienced something new The S in CAN SLIM stands for supply and demand, which refers to the laws that govern all market activities The analysis of supply and demand in the CAN SLIM method maintains that, all other things being equal, it is easier for a smaller firm, with a smaller number of share outstanding, to show outstanding gains The reasoning behind this is that a large cap company requires much more demand than a smaller cap one to demonstrate the same gains Besides, O'Neil explores this further and explains how the lack of liquidity of large institutional investors restricts them to buying only large-cap, blue-chip companies, leaving these large investors at a serious disadvantage that small private investors can capitalize on Because of supply and demand, the large transactions that institutional investors make can inadvertently affect share price, especially if the stock's market capitalization is smaller Because individual investors invest a relatively small amount, they can get in or out of a smaller company without pushing share price in an unfavorable direction In support of that, in his study, O'Neil found that 95% of the companies displaying the largest gains in share price had fewer than 25 million shares outstanding when the gains were realized In this part of CAN SLIM analysis, distinguishing between market leaders and market laggards is of key importance In each industry, there are always those that lead, providing great gains to shareholders, and those that lag behind, providing return that are mediocre at best The idea is to separate the contenders from the pretenders Firstly, The relative price strength of a stock can range from to 99, where a rank of 75 means the company, over a given period of time, has outperformed 75% of the stocks in its market group CAN SLIM requires a stock to have a relative price strength of at least 70 However, O'Neil states that stocks with relative price strength in the 80–90 range are more likely to be the major gainers O’Neil’s system strongly reminds that Do not let your emotions pick stock A company may seem to have the same product and business model as others in its industry, but not invest in that company simply because it appears cheap or evokes your sympathy Cheap stocks are cheap for a reason, usually because they are market laggards You may pay more now for a market leader, but it will be worth it in the end Next, CAN SLIM recognizes the importance of companies having some institutional sponsorship Basically, this criterion is based on the idea that if a company has no institutional sponsorship, all of the thousands of institutional money managers have passed over the company CAN SLIM suggests that a stock worth investing in has at least three to 10 institutional owners However, be wary if a very large portion of the company's stock is owned by institutions CAN SLIM acknowledges that a company can be institutionally over-owned and, when this happens, it is too late to buy into the company If a stock has too much institutional ownership, any kind of bad news could spark a spiraling sell-off O'Neil also explores all the factors that should be considered when determining whether a company's institutional ownership is of high quality Even though institutions are labeled "smart money", some are a lot smarter than others Last but not least, the final CAN SLIM criterion is market direction When picking stocks, it is important to recognize what kind of a market you are in, whether it is bear or bull Although O'Neil is not a market timer, he argues that if investors don't understand market direction, they may end up investing against the trend and thus compromise gains or even lose significantly Moreover, CAN SLIM maintains that the best way to keep track of market conditions is to watch the daily volumes and movements of the markets This component of CAN SLIM may require the use of some technical analysis tools, which are designed to help investors/traders discern trends 8.2 Financial institutions and investment service suppliers 8.2.1 Provide instruments for constituting and managing portfolio Even though the Static portfolio optimization model is easy to use and understand, individual investors need more investment services to support their long-term decision and portfolio allocation The major securities screening is carried out on several investment service websites such as cophieu68.com, bloomberg.vn, mms.com.vn, etc, but the inefficiency of tools is clearly proved My thesis will offer an adequate explanation for this phenomenon Firstly, individual investors with the low degree of awareness and knowledge cannot design a criterion system to filter Furthermore, even when investors are professional experts and economists, there is no system providing stock screening to defend their emotional and cognitive biases Eventually, after picking stock, they have no awareness of applying model of asset allocating for their portfolio Thus, in light of the above reasons, investment tools deal with seemingly distorted and crippled enhancement These difficulties are not insurmountable, even opening more opportunities for investment service suppliers More training courses of stock market and investment should be introduced to attract investors’ attention for knowledge improvement The content of lectures should be brief, concise and well-rounded Especially, behavioral finance theory needs focusing in these courses with useful advices to avoid behavioral biases such as herding, anchoring, loss aversion, regret aversion, etc Furthermore, instructors can introduce some models of picking stock (the implication of CAPM and Fama Three Factors model), or portfolio optimization The second obstacle can be overcome with investment instruments assisting investors to detect behavior mistake and provide recommendations Based on studies of behavioral biases and their remedies introduced by Pompian (2006) for instance, financial institutions supplying investment tools are able to design modern screening systems that incorporate biases These new systems will open a new era of technological tools controlling emotions and cognitions Finally, financial support tool suppliers can design a system allowing people to remove complicated calculations when constituting portfolios For example, an investor, by answering a questionnaire, can be determined his principal biases On the basis of main biases, several model of portfolio optimization recommended to him, and Static portfolio optimization for instance To summarize, the development of behavioral finance branch has creates more and more opportunities for financial service organizations to assist investors in constituting portfolios in one period 8.2.2 Provide biases defense for private clients Psychological factors are still green in financial academic and practical fields, hence, even though the behavioral finance domain induces more and more scholars with a vast of studies and empirical researches, there is few security companies having awareness of the importance of designing a defense protecting customers from wrong and regret decisions As Pompian (2006), there are more than twenty biases affecting investment decision of private investors The figure shows the big problem that everyone has to face to daily trading session In order for better clients’ performance, service suppliers should construct biases defense system for their customers By using this defense system, customers have capacity at avoiding unexpected mistakes CONCLUSION Individual domestic investors have important contribution to the enhancement of Vietnamese stock market However, there is seemingly no effective portfolio optimization model benefiting Vietnamese investors This status leads to many serious consequence on the enhancement of the stock market, that is major reason for implementing my thesis The main body of this thesis consists of four chapters dealing with selected topic in the field of behavioral portfolio allocation A detailed summary of the results and concluding remarks are presented as follows: Chapter ONE illustrates the theoretical framework and literature of one instrument of Behavioral finance paradigm - Cumulative Prospect Theory, which is the key base for Static portfolio optimization This section also provides general approaches to test hypotheses of Cumulative Prospect Theory, particularly Stochastic Dominance conditions Chapter TWO deals with a theoretical issue of the portfolio optimization models In this chapter, by comparing several approaches to resolve the problem of portfolio maximum, my thesis shows the outstanding features of Cumulative Prospect Theory approach over other approaches The central objective of this chapter is to demonstrate the Static portfolio optimization model which also criticized with some limitations In chapter THREE, my thesis summarizes the overall viewpoint about the Vietnamese stock market with great movements throughout years from 2007 Then, characteristics of investors in constituting portfolio are named such as lack of knowledge, lack of technological investment tools and affected by such behavioral biases as loss aversion, anchoring – adjustment and herding bias Chapter FOUR studies the main question whether the model is possible to be applied in Vietnamese stock market The major aim is the test of assumptions of Cumulative Prospect Theory in Vietnamese stock market The result implies the plausibility of applying this model in Vietnam Based on these finding and analysis, the last chapter provides recommendations for both individual investors and investment service suppliers in order for applying and effectively using the Static model in practical world The main advices for private investors are to improve knowledge and skills, design plausible strategy, filter information, apply the models of optimization in reality and use CAN SLIM system for portfolio choice And, service suppliers are recommended to provide more investment tools such as biases defense system, training courses, portfolio systems in order for better client’s performances This research determines that the assumptions of CPT cannot be rejected in Vietnamese stock market Additionally, my thesis introduce a new model of asset allocation of Bernard and Ghossoub (2009) for biased investors as well as the theoretical framework of stochastic dominance approach Moreover, my recommendations in designing and managing portfolio are useful for about 85% of domestic investors in HOSE Research result can be considered as empirical basis for the next deep research in behavioral finance in Vietnam, especially for portfolio issues Due to the lack of time and research capacity, my thesis is not without its limitations, I express my deep appreciation for contributions to complete my work Finally, I would like to acknowledge again my tutor M.Sc Le Thi Thu, my family and my friends for their encouragements during the completion of the thesis Ha Noi, 20 May, 2014 Nguyen Thi Thu Hang Class: A8, faculty of Business Administration, Intake: 49, Foreign Trade University REFERENCE Andersen, Jorgen Vitting, 2010, Detecting Anchoring in Financial Market, Journal of Behavioral Finance, Vol.11, No.2, 129-133 Barberis Nicholas and Thaler Richard, 2003, A survey of behavioral finance, handbook of the Economics of Finance, Elsevier Science B.V: 1054-1056 Baucells M and Heukamp F., 2006, Stochastic Dominance and Cumulative Prospect Theory, Management Science, Vol 52, No 9, page 1409-1423 Bernstein, Peter L., 1998, Against the Gods: the remarkable story of risk, USA: John Wiley & Sons Inc Han Bleichrodt and Jose Luis Pinto, 1995, An Experimental Test of Loss Aversion and Scale Compatibility, working paper, University Pompeu Fabra Erikson L., Wiedersheim –Paul F., 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44 The official website of Ho Chi Minh Stock Exchange: www.hsx.vn 45 The official website of Ha Noi Stock Exchange: www.hnx.vn 46 www.behaviouralfinance.net 47 http://www.investopedia.com/ APPENDIX A: SURVEY Suppose you decide to invest $10000 in below portfolios Which portfolios you choose, X or Y? when it is given that the dollar gain or loss one month from now will be as follows” TASK I: X Y GAIN/LOSS PROB GAIN/LOSS PROB 1000 2000 3000 10% 40% 40% 10% 50% 3000 50% TASK II: X Y GAIN/LOSS PROB GAIN/LOSS PROB -3000 50% 50% -3000 -2000 -1000 10% 40% 40% 10% TASK III: X Y GAIN/LOSS PROB GAIN/LOSS PROB -6000 3000 4500 1/3 ½ 1/6 -6000 -3000 4500 1/6 1/3 1/2 TASK IV: X Y GAIN/LOSS PROB GAIN/LOSS PROB 1000 2000 3000 10% 40% 40% 10% 50% 3000 50% TASK V: X Y GAIN/LOSS PROB GAIN/LOSS PROB -3000 50% 50% -3000 -2000 -1000 10% 40% 40% 10% APPENDIX B: MATHEMATICAL BACKGROUND Theorem: Suppose, then portfolio is preferred to portfolio if either w is absolutely dominant over w or w (see the proof in Appendix B) Proof of theorem: Because if either is absolutely dominant over, then w (as), it is necessary to prove only that if w then portfolio is preferred to portfolio Thus, if (or , then: , or is preferred to Theorem: Suppose that (implying that investors prefer more to less) and (implying that investor is risk averse), is preferred to if is second - order stochastically dominant over, or: Proof of the theorem: Because and , is a positive strictly decreasing function, therefore, the limit exists Because; so, it implies that : , then (as desired) ... 0.58 11.11 30,314,902.9 30,199,292.1 45,417.53 70,092.3 100,00 99.62 0.15 0.23 309,457,334.2 301, 993, 930.9 454,175.30 7,009,228.0 100,00 97.59 0.15 2.27 Percentage (%) (Source: www.hsx.vn, the official... 16,606,128.32 8,895,613.57 5,720,220.83 1,990, 293. 92 Percentage (%) 100 53.57 34.45 11.99 Listed Value (VND million) 680,801,162.7 88,956,135.68 572,022,088 19,902 ,939 Percentage (%) 100 13.06 84.01 2.92