Management of market risk, case study of modelling volatility in vietnam stock market

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY    MASTER OF BUSINESS ADMINISTRATION MANAGEMENT OF MARKET RISK: CASE STUDY OF MODELLING VOLATILITY IN VIETNAM STOCK MARKET    BY LAM VAN BAO DAN HO CHI MINH CITY – 2012 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY FALCULTY OF BUSINESS ADMINISTRATION    MASTER OF BUSINESS ADMINISTRATION MANAGEMENT OF MARKET RISK: CASE STUDY OF MODELLING VOLATILITY IN VIETNAM STOCK MARKET    BY LAM VAN BAO DAN SUPERVISOR VO XUAN VINH 2012 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Business Administration Master of Business Administration Lam Van Bao Dan CERTIFICATION “I certify that the substance of this thesis has not already been submitted for any degree and is not being currently submitted for any other degree I certify that, to the best of my knowledge, any help received in preparing this thesis, and all sources used have been acknowledged in this thesis” LAM VAN BAO DAN Date: 25th April, 2012 K17-EMBA Page 2012 Master of Business Administration Lam Van Bao Dan Abstract The thesis concerns with market risk management It has implications for businesses and investors, especially those hold investment in stocks In particular, the thesis investigates the technique to model stock volatility in Vietnam stock market The rapid growth of Vietnam stock market recently has received a great attraction of local and global investors However, like other emerging stock markets, this growth has accompanied with high risk Over the past thirty years, a huge number of articles have discussed the volatility of stock returns in developed and emerging capital markets Unfortunately, even though Vietnam stock market has started trading from 2000, there has been relatively little work done on modelling and forecasting the return volatility in Vietnam stock market This thesis employ the GARCH type models, both symmetric and asymmetric including ARCH (1), GARCH (1,1), GARCH-M (1,1), EGARCH (1,1) and TGARCH (1,1) to examine the sufficient models for capturing the characteristics of the return volatility in Vietnam stock market The data set of VN-Index over nine year period from March, 2002 to December, 2011 which divided into four periods including before crisis, crisis, recovering and whole period The findings suggest the sufficiency of ARCH (1), GARCH (1,1) and GARCH-M (1,1) models in capturing properties of conditional variance in Vietnam stock market The results also provide the indicator of the risk-reward relationship and show the weak evidence of asymmetry in the return series in Vietnam stock market K17-EMBA Page 2012 Master of Business Administration Lam Van Bao Dan Table of Contents Page I INTRODUCTION 1.1 Background of the Thesis 1.2 Research Questions and Objectives 11 1.3 1.2.1 Research Questions 11 1.2.2 Research Objectives and Implications 11 Vietnam Stock Market Overview 11 1.3.1 Introduction 11 1.3.2 VN-Index 16 1.4 Outline of the Thesis 20 II LITERATURE REVIEW 21 2.1 Volatility Definition 21 2.2 The Characteristics of Volatility in Financial Market 22 2.3 Literature Review 23 III DATA AND METHODOLOGY 35 3.1 Data 35 3.2 Descriptive Statistics 37 3.3 3.2.1 Histogram and Statistics Definition 37 3.2.2 Descriptive Statistics of Return Series for the Period before Crisis 39 3.2.3 Descriptive Statistics of Return Series for Crisis Period 40 3.2.4 Descriptive Statistics of Return Series for Recovering Period 41 3.2.5 Descriptive Statistics of Return Series for the Whole Period 42 3.2.6 Conclusions 43 Methodology 44 3.3.2 Testing for ARCH Effects 45 3.3.3 GARCH Models 46 K17-EMBA Page 2012 Master of Business Administration Lam Van Bao Dan IV EMPIRICAL RESULTS 53 4.1 Testing for ARCH Effect 53 4.2 Empirical Results of Different Periods 54 4.2.1 Empirical Results of the Period before Crisis 54 4.2.2 Empirical Results of the Crisis Period 57 4.2.3 Empirical Results of the Recovering Period 58 4.2.4 Empirical Results of the Whole Period of Vietnam Stock Market 59 V SUMMARY AND IMPLICATIONS 62 5.1 Summary and Implications 62 5.2 Limitations and Recommendations for Further Research 63 VI APPENDIX 65 6.1 Appendix-1: Testing for ARCH Effect 65 6.2 6.1.1 Before Crisis Period (From March, 2002 to December, 2007) 65 6.1.2 Crisis Period (From January, 2008 to December, 2009) 66 6.1.3 Recovering Period (From January, 2010 to December, 2011) 67 6.1.4 Whole Period (From March, 2002 to December, 2011) 68 Appendix-2: GARCH Models Analysis 69 6.2.1 Before Crisis Period (From March, 2002 to December, 2007) 69 6.2.2 Crisis Period (From January, 2008 to December, 2009) 74 6.2.3 Recovering Period (From January, 2010 to December, 2011) 79 6.2.4 Whole Period (From March, 2002 to December, 2011) 84 REFERENCES 89 K17-EMBA Page 2012 Master of Business Administration Lam Van Bao Dan List of Tables Table No Description Page Table Price limitations in HOSE over different periods 16 Table Summary for estimation results of before crisis period 60 Table Summary for estimation results of crisis period 60 Table Summary for estimation results of recovering period 61 Table Summary for estimation results of whole period 61 List of Figures Figure No Description Page Figure Number of listed company from 2000 to 2011 14 Figure Market capitalization from 2000 to 2011 14 Figure Number of securities companies from 2000 to 2011 15 Figure Number of trading accounts from 2000 to 2011 15 Figure Performance of VN-Index from 2000 to 2011 17 Figure Performance of VN-Index in 2007 18 Figure Performance of VN-Index in 2009 18 Figure Figure Figure 10 Figure 11 K17-EMBA Histogram of daily return series of VN-Index (01/03/2002 – 28/12/2007) Histogram of daily return series of VN-Index (02/01/2008 – 31/12/2009) Histogram of daily return series of VN-Index (04/01/2010 – 30/12/2011) Histogram of daily return series of VN-Index (01/03/2002 – 30/12/2011) Page 40 41 42 43 2012 Master of Business Administration Lam Van Bao Dan Acknowledgement I would like to say special thanks to my supervisor, Dr Vo Xuan Vinh for his helpful directions, encouragements and valuable comments in preparing this thesis I would like to thank all lecturers in EMBA program, especially to Dr Tran Ha Minh Quan for his help I would also like to thank all my friends in the program for supporting and encouraging me to finish this thesis Finally, special thanks also go to my wife and my family for their love and staying beside me during my study K17-EMBA Page 2012 Master of Business Administration I INTRODUCTION 1.1 Background of the Thesis Lam Van Bao Dan Investing in emerging stock markets can make a large return but also creates a big loss for businesses because of high volatility (high risk) Therefore, finding a technique to model volatility is important for businesses and investors investing in stock market This thesis will investigate the volatility models which best fits the Vietnam stock market conditions Modelling volatility will help businesses and investors understand and better manage risks involved in their investment Volatility is more and more important in financial market There are a huge number of researches and discussions for volatility in the past thirty years and especially in the recent years This is because volatility is a special indicator in financial market It is a key factor in many securities pricing formula as well as the value-at-risk models Even though volatility is unobservable, it plays an important role in making investment decision On the other hand, it is also the interest of the policy makers in financial markets The policy makers are interested in the impact of volatility on the stability of the financial market and hence on the economy Because of the above implications, volatility is the focus of several studies for estimation and forecast The volatility index (VIX) and Nasdaq Volatility Index (VXN) that defined as a weighted of prices for a range of options on the S&P 500 index and the Nasdaq 100 index have started trading from 2006 It is calculated in real time by Chicago Board Option Exchange (CBOE) These are two of the world’s most popular index of investors concerning to future stock market volatility The goal is to estimate the implied volatility of the stock market over the next 30 days It is proven that the low volatility index, the high trader confidence There are a lot of models that can be implied for modelling and forecasting volatility including ARCH/GARCH models and non-GARCH models However, ARCH model K17-EMBA Page 2012 Master of Business Administration Lam Van Bao Dan proposed by Engle (1982) and generalized by Bollerslev (1986) are said to be most sufficient for capturing the characteristics of the time varying stock return volatility From the introduction of the GARCH model, a huge number of GARCH extensions or GARCH family such as GARCH in mean (GARCH-M) (Bollerslev, 1986), EGARCH (Nelson, 1991), Threshold GARCH (TGARCH) (Glosten, Jagannathan and Runkle, 1993), Asymmetric GARCH model (AGARCH) (Engle, 1990), etc have been studied and proven to be sufficient for modelling and forecasting stock return volatility However, different papers support different models and show the conflicts in implication The empirical results argue that different models are suitable for different markets and in different time periods Therefore, we will employ several widely accepted GARCH models including ARCH, GARCH, GARCH-M, TGARCH and EGARCH to investigate the volatility of Vietnam stock market in this thesis From the results of the study, we will suggest the sufficient GARCH models for capturing the properties of return volatility in Vietnam stock market There have been numerous researches focusing on modelling stock price volatility However, most of them have discussed about the developed capital markets The emerging markets have not received much attention Recently, the emerging markets, especially the fast development countries such as China, Brazil, India, Russia, Mexico and the ASEAN countries has increasingly attracted the investors to diversify their portfolios Vietnam stock market has just been traded more than ten years It has significantly developed in recent years and has received a great attraction of many investors, both local and foreign They made considerable amount of profits during the boom time of 2006-2007 However, the market went down in 2008 and 2009 due to the effect of world financial crisis that results in a big loss for many businesses and investors K17-EMBA Page 2012 Master of Business Administration Lam Van Bao Dan TGARCH (1,1) Dependent Variable: RETURN Method: ML - ARCH (Marquardt) - Normal distribution Date: 04/01/12 Time: 11:21 Sample (adjusted): 498 Included observations: 497 after adjustments Convergence achieved after 41 iterations Presample variance: backcast (parameter = 0.7) GARCH = C(2) + C(3)*RESID(-1)^2 + C(4)*RESID(-1)^2*(RESID(-1)