The impact of macroeconomic factors on conditional stock market volatility in vietnam

1 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY - oOo - NGUYỄN THÚY VÂN THE IMPACT OF MACROECONOMIC FACTORS ON CONDITIONAL STOCK MARKET VOLATILITY IN VIETNAM MAJOR: BANKING AND FINANCE MAJOR CODE: 60.31.12 MASTER THESIS INSTRUCTOR: Doctor TRƯƠNG QUANG THÔNG Ho Chi Minh City – 2011 ACKNOWLEDGEMENT Firstly, I would like to express my sincerest gratitude to my supervisor, Dr Truong Quang Thong for his valuable guidance and helpful comments during the course of my study I also would like to thank all of my lecturers at Faculty of Banking and Finance, University of Economics Hochiminh City for their English program, knowledge and teaching during my master course at school I would like to specially express my thanks to my classmates, my friends for their support and encouragement Special thanks should go to my family for their love and support during my life ABSTRACT The study looks at the relationship between macroeconomic factors and and stock market, and determined whether inflation, movements in exchange rate, interst rate have an effect on stock market return volatility in Vietnam The Generalised Autoregressive Conditional Heteroskedascity (GARCH) models are used in establishing the relationship between these variables and stock market volatility The results confirms presence of GARCH (1,1) effect on stock return time series of Vietnam stock market It is also found that there is strong and positive relationship between inflation and stock market return volatility It means that an increase in inflation leads to an increase in stock market return volatility in the long run However, there is no enough proof to conclude that change in interest rate and exchange rate can influence market return volatility Keywords: volatility, leverage, interest rate, inflation, exchange rate, returns, Hochiminh Stock Exchange i Table of contents  CHAPTER Introduction 1.1Introduction 1.2Research problem 1.3Research objectives 1.4Research methodology 1.5Structure Of The Study CHAPTER Literature review 2.1Introduction 2.2ARCH and GARCH m 2.3The impact of macroec 2.4Application of Garch m 2.5Conclusion CHAPTER Research Methodology 3.1Introduction 3.2Research data and ii 3.3DF unit root test: 3.4Hypotheses and empirical m macroeconomic variables on stock return volatility 3.5Conclusion CHAPTER Empirical Results of the Research 4.1Introduction 4.2Descriptive statistics 4.3DF unit root test 4.4Correlation Matrix of the va 4.5Emprical result of model CHAPTER Conclusions, Limitations and recommendations 5.1Introduction 5.2Conclusions and Implication 5.3Limitations and recommenda REFERENCES APPENDIX iii Descriptive Statistics of variables 45 Monthly CPI from 2000 – 2010 (Source: GSO) .47 Unit root test 48 Data 50 Figures  Figure 3.1 The performance of VN-Index from 07/2000 – 12/2010 Figure 3.2 Inflation in Vietnam and selected countries 2000 - 2009 Figure 3.3 Vietnam‟s nominal exchange rate (VND/USD) and inflation rate 1992-2010 Tables  Table 3.1 Vietnam exchange rate arrangement 2000 - 2010 Table 4.1 Descriptive statistics of variables (07/2000 – 12/2010) Table 4.2 ADF UNIT ROOT TEST Table 4.3 Correlation Matrix of the variables Table 4.4 Result of model Table 4.5 Result of model Table 4.6 Result of model Table 4.7 Result of model Table 4.8 Result of model iv Glossary CPI: consumer price index SBV: State Bank of Vietnam GARCH: Generalized AutoRegressive Conditional Heteroskedasticity ARCH: Autoregressive Conditional Hetroskedasticity GDP: Gross Domestic Product HOSE: Hochiminh Stock Exchange CHAPTER Introduction 1.1 Introduction Stock return volatility refers to the variation in stock price changes during a period of time Normally investors and agents perceive this variation as a measure of risk The policy makers use estimate of volatility as a tool to measure the vulnerability of the stock market Since understanding the nature of stock market volatility gives important implications for policy makers and investors, movements in stock prices volatility have been the central variable of many researches There have been numerous of studies trying to answer an interesting question: what are the factors that derive stock market volatility Researchers have analyzed the relative importance of economy-wide factors, industry-specific factors, and firm-specific factors stock volatility One of the earliest studies was of Officer (1973) which related changes in stock market volatility to changes in real economic variables He noted that variability in stock prices was unusually high during the period of great depression i e 1929-1939 compared with pre-and postdepression periods Schwert (1989) was a classic study which intended to verify Officer‟s (1973) findings and explored the relationship between stock prices volatility and macroeconomic variables This issue has been studied by numerous researches and their findings are not the same Many papers of Engle and Rangel (2005), Campbell (1987) and Shanken (1990)…confirmed that macroeconomic factors had significant effect on stock market volatility Contrary to this, Davis and Kutan (2003), Schwert (1989) evidenced that macroeconomic variables had weak predictive power for explaining variability of stock market prices and returns volatility Inconsistent results depend on different characteristics of every countries as well as different time periods Since ARCH model was proposed by Engle (1982) and generalized by Bollerslev (1986) and Taylor (1986), the models have been proved to be sufficient in capturing properties of time varying stock return volatility Literatures have found evidence in support the capability of GARCH models in volatility estimation as well as volatility forecast Vietnam stock market was newly established in 2000 in Ho Chi Minh City on 28 July 2000 (Hochiminh Stock Exchange – HOSE) In the first trading session there were only two stocks with a total market capitalization of 270 billion VND Although the market has significantly grown over ten years of operation (until at the end of 2010), it is still rather small and incomplete in comparison to other stock markets in the Asian region Moreover, interest rate, inflation, exchange rate and stock market are hot subjects attracting attention of the government, investors and corporations in recent years Relationship among these macroeconomic variables as well as their effect on stock market has been discussed every day In fact, in Vietnam, inflation, interest rate and exchange rate impact on stock market? Can we measure this impact? 1.2 Research problem Research and practice have proved the important role of macroeconomic variables on the economy Stock market volatility is known as one of the most important phenomena that determine the amount of risk faced by investors The impact of macroeconomic factors on stock market including market volatility is a major question to be posed and tested in many countries around the world However, as far as the author is concerned, in Vietnam there were not many researches exploring this issue In addition, unlike the stock market in the developed countries, Vietnam's stock market is not really operating under the law of supply and demand but it is influenced by herb behavior and "crowd effect" Therefore, no one can confidently confirm that changes in macroeconomic factors impact to the entire stock market Moreover, inflation, exchange rate, interest rate and stock market are hot topics in recent years As the importance of volatility as a proxy of risk, the advantages of GARCH family and Vietnam stock market‟s particular situation mentioned above, the paper chooses to study the impact of inflation, exchange rate and interest rate to stock market volatility by applying GARCH models My study will try to answer the following questions: What macroeconomic determinants of stock market volatility in Vietnam are? And how they specifically affect the stock market? 1.3 Research objectives The main purpose of this study is to identify factors that impact stock market conditional volatility using the data from Hochiminh Stock Exchange The present study contributes to the literature in three ways Firstly, the present study will shed some light on the depth of the stock market activities especially in emerging market in addition to identifying and relating the changes in economic factors to the changes in stock market movements It is necessary to have more and more researches about Vietnam stock market so that we can understand and develop our immature stock market Secondly, the findings of this investigation should enable the investors to know about stock market volatility as a measure of risk and make their decision Finally, the study will help the policy makers in seeing the effect of their policy to stock market and choosing in which way they should adjust their policy 1.4 Research methodology and scope To achieve the above mentioned objectives, the author employs quantitative research by using data of Hochiminh Stock Exchange Index (VNIndex), inflation, 40 is coincident with greater stock market risk This is consistent with the previous researches in other developing countries Thirdly, we not find enough evidence to conclude that interest rate change, exchange rate change have impacts on conditional variance of stock market return The reasons led to this result are that maybe interest rate and exchange rate are official figures that did not reflect all sensitive change in market or monthly data is not suitable Implications: This study provides better understanding on the depth of the stock market activities by identifying the changes in economic factors with the changes in stock market movements For investors, this investigation should enable the investors to know more about stock market volatility as a measure of risk and make their decision They should therefore pay attention to macroeconomic factors, especially for inflation as a mean for choosing and adjusting their investment The study will help the policy makers in seeing the effect of their policy to stock market and choosing which way they should adjust their policy Academics-wise, this is the first step to explore the relationship between macroeconomic factors and stock market return volatility It is suggested base on this study that other researchers can use other data and periods of time to study other the macroeconomic determinants of stock market volatility My expectation is that there will have more further researches relating to this topic 5.3 Limitations and recommendations: Although I try my best, my study still has some limitations: Firstly, the research just uses data of Hochiminh stock market and not consider data of Ha Noi Stock Exchange (HNX) 41 Secondly, this paper is analyzed based on monthly data and results reflect that there is no relationship between stock market return volatility and interest rate as well as exchange rate Maybe daily data is more suitable For future researches, I recommend the following subjects: - Will this result conducting by data of HOSE be consistent with data of Ha Noi Stock Exchange (HNX)? - What are other determinants of stock market return volatility such as other macroeconomic variables or corporation characteristics? - Can we find any relationship between stock market return volatility and exchange rate, interest rate by changing methods of data collecting such as daily? - How these variables effect to individual stocks and to sectorial portfolios? 42 REFERENCES Adjasi, C., Harvey, S K., & Coast, C (2008) EFFECT OF EXCHANGE RATE VOLATILITY ON THE GHANA STOCK EXCHANGE Banking, 3(3), 28-47 Affairs, S (2009) IMPACT OF MACROECONOMIC INDICATORS ON VIETNAMESE STOCK PRICES Finance, Aliyu, S U R (2012) Does inflation have an impact on stock returns and volatility? Evidence from Nigeria and Ghana Applied Financial Economics, 22(6), 427-435 doi:10.1080/09603107.2011.617691 Aggarwal, R, C Inclan, and R Leal, 1999 "Volatility in Emerging Markets", Journal of Financial and Quantitative Analysis 34, pp 33-55 Bahmani-Oskooee and Sohrabian (1992) Stock prices and the effect exchange rate of the dollar, Applied Economics 24, 459-464 Beltratti, A., & Morana, C (2006) Breaks and persistency: macroeconomic causes of stock market volatility Journal of Econometrics, 131(1-2), 151-177 Elsevier Binti, H., Kadir, A., Selamat, Z., Masuga, T., & Taudi, R (2011) Predictability Power of Interest Rate and Exchange Rate Volatility on Stock Market Return and Volatility : Evidence from Bursa Malaysia Finance, 4, 199-202 Bollerslev, T (1986) Generalized autoregressive conditional heteroskedasticity Journal of econometrics, 31(3), 307-327 Campbell, J Y., 1987, «Stock Returns and the Term Structure», Journal of Financial Economics 18, 373-399 Chang, H.-ling (2009) Asymmetric Price Transmissions between the Exchange Rate and Stock Market in Vietnam Finance and Economics, 23(23) Choi, J.J., Elyasiani, E., and Kopecky, K.J., 1992 “The sensitivity of bank stock returns to market, interest and exchange rate risks”, Journal of Banking Finance 16, pp 983–1004 Davis, N., & Kutan, A M (2003) Inflation and output as predictors of stock returns and volatility: international evidence Applied Financial Economics, 13(9), 693-700 Taylor & Francis 43 Engle, R F (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation Econometrica: Journal of the Econometric Society, 987-1007 JSTOR Engle, R F., & Patton, A J (2001) What good is a volatility model? 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Evidence and Analysis Umr, C (2008) Modelling Volatility Using GARCH Models : Evidence from Vietnam Africa, (2005) Gulin Vardar (2008) Effect of Interest and Exchange Rate on Volatility and Return of Sector Price Indices at Istanbul Stock Exchange, European Journal of Economics, Finance and Administrative Sciences Issue 11 (2008) Zafar, N., Urooj, F S., & Durrani, K T (2008) Interest Rate Volatality and stock Return and Volatality European Journal of Economics,Finance and Administratie Science 45 APPENDIX Descriptive Statistics of variables Series: R Sample 2000M08 2010M12 Observations 125 Mean Median Maximum Minimum Std Dev Skewness Kurtosis Jarque-Bera Probability 1.250777 0.044043 32.57549 -42.07289 12.23161 -0.222739 3.786231 4.253176 0.119243 Series: IR Sample 2000M08 2010M12 Observations 125 Mean Median Maximum Minimum Std Dev Skewness Kurtosis Jarque-Bera Probability 1.086111 0.000000 24.18357 -41.93405 7.283562 -1.112734 14.69327 737.9436 0.000000 46 Series: ER Sample 2000M08 2010M12 Observations 125 Mean Median Maximum Minimum Std Dev Skewness Kurtosis Jarque-Bera Probability Series: IF Sample 2000M08 2010M12 Observations 125 Mean Median Maximum Minimum Std Dev Skewness Kurtosis Jarque-Bera Probability 0.641619 0.399202 3.825871 -0.803217 0.865995 1.321997 4.982351 56.87720 0.000000 0.236140 0.091948 5.412291 -1.019314 0.715633 4.556076 28.25407 3754.165 0.000000 47 Monthly CPI from 2000 – 2010 (Source: GSO) 2000 Last month = 100% January 100.40 February 101.60 March 98.90 April 99.30 May 99.40 June 99.50 July 99.40 August 100.10 September 99.80 October 100.10 November 100.90 December 100.10 48 Unit root test + STOCK RETURN Null Hypothesis: R has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dickey-Fuller test statistic Test critical values: *MacKinnon (1996) one-sided p-values + EXCHANGE RATE Null Hypothesis: ER has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dickey-Fuller test statistic Test critical values: *MacKinnon (1996) one-sided p-values + INFLATION 49 Null Hypothesis: IF has a unit root Exogenous: Constant Lag Length: 12 (Automatic based on SIC, MAXLAG=12) Augmented Dickey-Fuller test statistic Test critical values: *MacKinnon (1996) one-sided p-values + INTEREST RATE: Null Hypothesis: IR has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dickey-Fuller test statistic Test critical values: *MacKinnon (1996) one-sided p-values 50 Data Column1 M7 2000 M8 2000 M9 2000 M10 2000 M11 2000 M12 2000 M1 2001 Officia (VND 14093 14121 14215 14378 14499 14514 14546 M2 2001 M3 2001 M4 2001 M5 2001 M6 2001 M7 2001 M8 2001 M9 2001 M10 2001 M11 2001 M12 2001 M1 2002 M2 2002 M3 2002 M4 2002 M5 2002 M6 2002 M7 2002 M8 2002 M9 2002 M10 2002 M11 2002 14565 14545 14567 14662 14845 14941 14994 15003 15033 15068 15084 15117 15192 15250 15249 15261 15321 15321 15331 15347 15364 15385 M12 2002 M1 2003 M2 2003 M3 2003 M4 2003 M5 2003 M6 2003 15403 15411 15415 15443 15459 15476 15499 51 M7 2003 M8 2003 M9 2003 M10 2003 M11 2003 M12 2003 M1 2004 M2 2004 M3 2004 M4 2004 15517 15522 15557 15645 15630 15646 15696 15758 15724 15721 M5 2004 M6 2004 M7 2004 M8 2004 M9 2004 M10 2004 M11 2004 M12 2004 M1 2005 M2 2005 M3 2005 M4 2005 M5 2005 M6 2005 M7 2005 M8 2005 M9 2005 M10 2005 M11 2005 M12 2005 M1 2006 M2 2006 15745 15723 15752 15764 15755 15748 15762 15777 15832 15803 15823 15832 15851 15857 15884 15878 15895 15905 15916 15916 15922 15910 M3 2006 M4 2006 M5 2006 M6 2006 M7 2006 M8 2006 M9 2006 15927 15934 15959 15996 16007 16014 16055 52 M10 2006 M11 2006 M12 2006 M1 2007 M2 2007 M3 2007 M4 2007 M5 2007 M6 2007 M7 2007 M8 2007 M9 2007 M10 2007 M11 2007 M12 2007 M1 2008 M2 2008 M3 2008 M4 2008 M5 2008 M6 2008 M7 2008 M8 2008 M9 2008 M10 2008 M11 2008 M12 2008 M1 2009 M2 2009 M3 2009 M4 2009 M5 2009 M6 2009 M7 2009 M8 2009 M9 2009 M10 2009 M11 2009 M12 2009 53 M1 2010 M2 2010 M3 2010 M4 2010 M5 2010 M6 2010 M7 2010 M8 2010 M9 2010 M10 2010 M11 2010 M12 2010 (Source: IFS and Hochiminh stock exchange website) ... economy Stock market volatility is known as one of the most important phenomena that determine the amount of risk faced by investors The impact of macroeconomic factors on stock market including... Measuring the Impact of Inflation on Conditional Stock Market Volatility in Pakistan : An Application of IGARCH Model Finance and Economics, 13(13) 44 Sadorsky, P (2003) The macroeconomic determinants... that the inflation significantly and positive impacts on conditional variance of stock market return The finding suggests that the higher rate of inflation is, the greater stock market volatility