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Year 2018, , 38 - 57, 30.03.2018

Thu Thuy Nguyen Kadom Shubber

https://doi.org/10.17261/Pressacademia.2018.783

Abstract

References

  • Alexander, C. 1998, Risk Management and Analysis: Measuring and Modeling Financial Risk, Chichester: John Wiley & Sons Ltd.
  • Alexander, C. 2007, Market Models: A Guide to Financial Data Analysis, New York: John Wiley & Sons Ltd.
  • Bollerslev, T. 1986, Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, Vol. 31, pp. 307–328.
  • Brooks, C. & Persand, G. 2003, “The Effect of Asymmetries on Stock Index Return Value-at-Risk Estimates”, The Journal of Risk Finance, pp. 29-42.
  • Chen, N. F., Roll, R., & Ross, S. A. 1986, "Economic Forces and the Stock Market", The Journal of Business, Vol. 59, No. 3, pp. 383-403.
  • Connolly, R. A. 1989, “An Examination of the Robustness of the Weekend Effect”, Journal of Financial and Quantitative Analysis, Vol. 24, pp. 133-169.
  • Do, G. Q., Mcaleer, M., & Sriboonchitta, S. 2009, “Effects of International Gold Market on Stock Exchange Volatility: Evidence from ASEAN Emerging Stock Markets”, Economics Bulletin, Vol. 29, No. 2, pp. 599-610.
  • Enders, W. 2004, Applied Econometric Time Series, Second Edition, Wiley.
  • Enders, W. 2015, Applied Econometric Time Series, Forth Edition, Wiley.
  • Engle, R.F. 1982, “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation”, Econometrica, Vol. 50, pp. 987-1008.
  • Eviews 8 User’s Guide I & II.
  • Fama, E. F. 1970, “Efficient Capital Markets: A Review of Theory and Empirical Work”, Journal of Finance, Vol. 25, pp. 383-417.
  • Fama, E. F. & French, K. R. 1989, “Business Conditions and Expected Returns on Stocks and Bonds”, The Journal of Financial Economics, Vol. 25, pp. 23-49.
  • Fan, J. & Yao, Q. 2003, Nonlinear Time Series: Nonparametric and Parametric Methods, New York: Springer-Verlag.
  • Floros, C. 2007, “The Use of GARCH Models for the Calculation of Minimum Capital Risk Requirements: International Evidence”, International Journal of Managerial Finance, Vol. 3, No. 4, pp. 360-371.
  • French, K. R., Schwert, G. W., & Stambaugh, R. F. 1987, “Expected Stock Returns and Volatility”, Journal of Financial Economics, Vol. 19, No. 1, pp. 3-29.
  • Hsing, Y. 2011, “Impacts of Macroeconomic Variables on Stock Market in Bulgaria and Policy Implications”, East-West Journal of Economics and Business, Vol. 14, No. 2, pp. 41-53.
  • Hussainey, K. & Le, N. K. 2009, “The Impact of Macroeconomic Indicators on Vietnamese Stock Prices”, The Journal of Risk Finance, Vol. 10, Iss.4, pp. 321- 332.
  • Huynh, T. C. H., Le, T. L., Le, T. H. M., & Hoang, T. P. A. 2014, “Kiem dinh cac nhan to vi mo tac dong den thi truong chung khoan Viet Nam” (“Testing the Effects of Macroeconomic Variables on the Vietnamese Stock Market”), Scientific Journal of An Giang University (Vietnam), Vol. 3, No. 2, pp. 70-78.
  • Gao, Y., Zhang, C., & Zhang, L. 2012, “Comparison of GARCH Models based on Different Distributions”, Journal of Computers, Vol. 7, No. 8, pp.1967-1973.
  • Gelman, A. & Hill, J. 2007, Data Analysis using Regression and Multilevel/Hierarchical Models, Cambridge: Cambridge University Press.
  • Kuwornu, J. K. M. 2012, “Effect of Macroeconomic Variables on Ghanaian Stock Market Returns: A Co-integration Analysis”, Agris on-line Paper in Economics and Informatics, Vol. 4, No. 2, pp. 1-12.
  • Kuwornu, J. K. M. & Victor, Owusu-Nantwi 2011, “Macroeconomic Variables and Stock Market Returns: Full Information Maximum Likelihood Estimation”, Research Journal of Accounting and Finance, Vol. 2, No. 4, pp.49-63.
  • Le, H. P. & Dang, T. B. V. 2015, “Kiem chung bang mo hinh ARDL tac dong cua cac nhan to vi mo den chi so chung khoan Vietnam” (“Verifying the Impact of Macroeconomic Factors to the Vietnam’s Stock Index by the ARDL Model”), Journal of Development and Integration, University of Economics and Finance (Vietnam), Vol. 20, No. 30, pp. 61-66.
  • Narayan, P. K. & Narayan, S. 2010, "Modelling the impact of oil prices on Vietnam's stock prices", Applied Energy, Vol. 87, Issue 1, pp. 356361.
  • Nguyen, T. 2011, "US Macroeconomic News Spillover Effects on Vietnamese Stock Market", The Journal of Risk Finance, Vol. 12, Issue 5, pp.389-399.
  • Phan, K. C. & Zhou, J. 2014, “Market Efficiency in Emerging Stock Markets: A Case Study of Vietnam’s stock market”, Journal of Business and Management, Vol. 16, Iss. 4, Ver. IV, pp. 61-73.
  • Samadi, S., Bayani, O., & Ghalandari, M. 2012, “The Relationship between Macroeconomic Variables and Stock Returns in the Tehran Stock Exchange”, International Journal of Academic Research in Business and Social Sciences, Vol. 2, No. 6.
  • Schwert, G. W. 1989, “Why does Stock Market Volatility Change Over Time?”, The Journal of Finance, Vol. 44, No. 5, pp. 1368-1388.
  • The World Bank (WB): World Bank Open Data, viewed 15 June 2014, http://data.worldbank.org/
  • Truong, D. L., Lanjouw, G., & Lensink, R. 2010, “Stock-Market Efficiency in Thin-Trading Markets: The Case Study in Vietnam’s stock market”, Applied Economics, Vol. 42, pp. 3519-3532.
  • Zakaria, Z. & Shamsuddin, S. 2012, “Empirical Evidence on the Relationship between Stock Market Volatility and Macroeconomics Volatility in Malaysia”, Journal of Business Study Quarterly, Vol. 4, No. 2, pp. 61-71.

VIETNAM’S STOCK MARKET VOLATILITY UNDER MACROECONOMIC IMPACTS

Year 2018, , 38 - 57, 30.03.2018

Thu Thuy Nguyen Kadom Shubber

https://doi.org/10.17261/Pressacademia.2018.783

Abstract

Purpose - This study investigates whether the volatility of stock market returns is determined by macroeconomic variables either as individual or as a group, within the context of Vietnam – a frontier emerging market. Six macroeconomic factors have been selected, including economic growth (GDP), consumer price index (CPI), broad money supply (M2), interest rate (represented by refinancing rate – FR), foreign exchange rate USD/VND (EX), and foreign direct investment (FDI). 

Methodology - Using 161 monthly observations collected from August 2000 to December 2013, the paper employs general autoregressive conditional heteroskedasticity (GARCH) framework to measure stock market volatility as well as to estimate this volatility under indicated macroeconomic impacts. 

Findings - Taking the volatility clustering into account, the GARCH (1,1) models reveal that the volatility of Vietnam’s stock market returns is highly persistent, suggesting a long memory of the volatility in response of a shock. Additionally, the stock market volatility could be predicted better using previous shocks (i.e. those originating from GDP, CPI and EX) rather than the previous volatility itself.

Conclusion - The prediction of Vietnam’s stock market volatility could be better based on the selected macroeconomic indicators. A monthly change in consumer price index appears as the most essential indicator that help predicting the volatility of the Vietnam’s stock market. Any news about economic growth can be considered as the second significant factor in explaining Vietnam stock return volatility. Furthermore, the univariate analysis shows a statistical significant evidence for the impact of a change in the exchange rate (USD/VNA) on Vietnam’s stock market volatility. 

Keywords

Stock market volatility macroeconomic factors GARCH emerging markets

References

  • Alexander, C. 1998, Risk Management and Analysis: Measuring and Modeling Financial Risk, Chichester: John Wiley & Sons Ltd.
  • Alexander, C. 2007, Market Models: A Guide to Financial Data Analysis, New York: John Wiley & Sons Ltd.
  • Bollerslev, T. 1986, Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, Vol. 31, pp. 307–328.
  • Brooks, C. & Persand, G. 2003, “The Effect of Asymmetries on Stock Index Return Value-at-Risk Estimates”, The Journal of Risk Finance, pp. 29-42.
  • Chen, N. F., Roll, R., & Ross, S. A. 1986, "Economic Forces and the Stock Market", The Journal of Business, Vol. 59, No. 3, pp. 383-403.
  • Connolly, R. A. 1989, “An Examination of the Robustness of the Weekend Effect”, Journal of Financial and Quantitative Analysis, Vol. 24, pp. 133-169.
  • Do, G. Q., Mcaleer, M., & Sriboonchitta, S. 2009, “Effects of International Gold Market on Stock Exchange Volatility: Evidence from ASEAN Emerging Stock Markets”, Economics Bulletin, Vol. 29, No. 2, pp. 599-610.
  • Enders, W. 2004, Applied Econometric Time Series, Second Edition, Wiley.
  • Enders, W. 2015, Applied Econometric Time Series, Forth Edition, Wiley.
  • Engle, R.F. 1982, “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation”, Econometrica, Vol. 50, pp. 987-1008.
  • Eviews 8 User’s Guide I & II.
  • Fama, E. F. 1970, “Efficient Capital Markets: A Review of Theory and Empirical Work”, Journal of Finance, Vol. 25, pp. 383-417.
  • Fama, E. F. & French, K. R. 1989, “Business Conditions and Expected Returns on Stocks and Bonds”, The Journal of Financial Economics, Vol. 25, pp. 23-49.
  • Fan, J. & Yao, Q. 2003, Nonlinear Time Series: Nonparametric and Parametric Methods, New York: Springer-Verlag.
  • Floros, C. 2007, “The Use of GARCH Models for the Calculation of Minimum Capital Risk Requirements: International Evidence”, International Journal of Managerial Finance, Vol. 3, No. 4, pp. 360-371.
  • French, K. R., Schwert, G. W., & Stambaugh, R. F. 1987, “Expected Stock Returns and Volatility”, Journal of Financial Economics, Vol. 19, No. 1, pp. 3-29.
  • Hsing, Y. 2011, “Impacts of Macroeconomic Variables on Stock Market in Bulgaria and Policy Implications”, East-West Journal of Economics and Business, Vol. 14, No. 2, pp. 41-53.
  • Hussainey, K. & Le, N. K. 2009, “The Impact of Macroeconomic Indicators on Vietnamese Stock Prices”, The Journal of Risk Finance, Vol. 10, Iss.4, pp. 321- 332.
  • Huynh, T. C. H., Le, T. L., Le, T. H. M., & Hoang, T. P. A. 2014, “Kiem dinh cac nhan to vi mo tac dong den thi truong chung khoan Viet Nam” (“Testing the Effects of Macroeconomic Variables on the Vietnamese Stock Market”), Scientific Journal of An Giang University (Vietnam), Vol. 3, No. 2, pp. 70-78.
  • Gao, Y., Zhang, C., & Zhang, L. 2012, “Comparison of GARCH Models based on Different Distributions”, Journal of Computers, Vol. 7, No. 8, pp.1967-1973.
  • Gelman, A. & Hill, J. 2007, Data Analysis using Regression and Multilevel/Hierarchical Models, Cambridge: Cambridge University Press.
  • Kuwornu, J. K. M. 2012, “Effect of Macroeconomic Variables on Ghanaian Stock Market Returns: A Co-integration Analysis”, Agris on-line Paper in Economics and Informatics, Vol. 4, No. 2, pp. 1-12.
  • Kuwornu, J. K. M. & Victor, Owusu-Nantwi 2011, “Macroeconomic Variables and Stock Market Returns: Full Information Maximum Likelihood Estimation”, Research Journal of Accounting and Finance, Vol. 2, No. 4, pp.49-63.
  • Le, H. P. & Dang, T. B. V. 2015, “Kiem chung bang mo hinh ARDL tac dong cua cac nhan to vi mo den chi so chung khoan Vietnam” (“Verifying the Impact of Macroeconomic Factors to the Vietnam’s Stock Index by the ARDL Model”), Journal of Development and Integration, University of Economics and Finance (Vietnam), Vol. 20, No. 30, pp. 61-66.
  • Narayan, P. K. & Narayan, S. 2010, "Modelling the impact of oil prices on Vietnam's stock prices", Applied Energy, Vol. 87, Issue 1, pp. 356361.
  • Nguyen, T. 2011, "US Macroeconomic News Spillover Effects on Vietnamese Stock Market", The Journal of Risk Finance, Vol. 12, Issue 5, pp.389-399.
  • Phan, K. C. & Zhou, J. 2014, “Market Efficiency in Emerging Stock Markets: A Case Study of Vietnam’s stock market”, Journal of Business and Management, Vol. 16, Iss. 4, Ver. IV, pp. 61-73.
  • Samadi, S., Bayani, O., & Ghalandari, M. 2012, “The Relationship between Macroeconomic Variables and Stock Returns in the Tehran Stock Exchange”, International Journal of Academic Research in Business and Social Sciences, Vol. 2, No. 6.
  • Schwert, G. W. 1989, “Why does Stock Market Volatility Change Over Time?”, The Journal of Finance, Vol. 44, No. 5, pp. 1368-1388.
  • The World Bank (WB): World Bank Open Data, viewed 15 June 2014, http://data.worldbank.org/
  • Truong, D. L., Lanjouw, G., & Lensink, R. 2010, “Stock-Market Efficiency in Thin-Trading Markets: The Case Study in Vietnam’s stock market”, Applied Economics, Vol. 42, pp. 3519-3532.
  • Zakaria, Z. & Shamsuddin, S. 2012, “Empirical Evidence on the Relationship between Stock Market Volatility and Macroeconomics Volatility in Malaysia”, Journal of Business Study Quarterly, Vol. 4, No. 2, pp. 61-71.
There are 32 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Thu Thuy Nguyen This is me 0000-0001-8001-037X

Kadom Shubber This is me 0000-0002-3915-8003

Publication Date March 30, 2018
Published in Issue Year 2018

Cite

APA Nguyen, T. T., & Shubber, K. (2018). VIETNAM’S STOCK MARKET VOLATILITY UNDER MACROECONOMIC IMPACTS. Journal of Economics Finance and Accounting, 5(1), 38-57. https://doi.org/10.17261/Pressacademia.2018.783

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