Asymmetric Volatility of the Thai Stock Market. Evidence from High-Frequency Data

  • Supachok THAKOLSRI Public Enterprise Policy Office, Ministry of Finance, Thailand
  • Yuthana SETHAPRAMOTE School of Development Economics National Institute of Development Administration, Thailand
  • Komain JIRANYAKUL School of Development Economics National Institute of Development Administration, Thailand

Abstract

This study employs the daily data of the Stock Exchange of Thailand to test for the leverage and volatility feedback effects. The period of investigation is during January 4, 2005 to December 27, 2013, which includes the Subprime crisis period in the US that might affect the volatility of stock market return in emerging stock markets. The results from this study show that the US subprime crisis imposes a minimal positive impact on volatility. In addition, the estimations of the three parametric asymmetric volatility models give the results showing some evidence of the volatility feedback and leverage effects. The findings give implications for portfolio diversification and risk management.

References

[1] Asongu, S.A. (2012). Globalization, financial crisis and contagion: Time-dynamic evidence from financial markets of developing countries, Journal of Advanced Studies in Finance, 3: 131-139.
[2] Bekeart, G., Wu, G. (2000). Asymmetric volatility and risk in equity markets, Review of Financial Studies, 13: 1-42.
[3] Black, F. (1976). Studies in stock price volatility changes, Proceedings of the 1976 Business Meeting of the Business and Economic Section, American Economic Association, 177-181.
[4] Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity, Econometrica, 31: 307-327.
[5] Bollerslev, T., Litvinova, J., Tauchen G. (2006). Leverage and volatility feedback effects in high-frequency data, Journal of Financial Econometrics, 4: 353-384.
[6] Brandt, M.W., Kang, Q. (2004). On the relation between the conditional mean and volatility of stock returns: A latent VAR approach, Journal of Financial Economics, 72: 217-257.
[7] Campbell, J., Hentschel, L. (1992). No news is good news: An asymmetric model of changing volatility in stock returns, Journal of Financial Economics, 31: 281-318.
[8] Christie, A. (1982). The stochastic behavior of common stock variances-value, leverage, and interest rate effects, Journal of Financial Economics, 10: 407-432.
[9] Ding, Z., Engle, R., Granger, C.W.F. (1993). A long memory property of stock market returns and a new model, Journal of Empirical Finance, 1: 83-106.
[10] Dooley, M., Hutchison, M. (2009). Transmission of the U. S. subprime crisis to emerging markets: Evidence on the decoupling-recoupling hypothesis, Journal of International Money and Finance, 28: 1331-1349.
[11] Ederington, L.H., Guan, W. (2010). How asymmetric is the US stock market volatility?, Journal of Financial Markets, 13: 225-248.
[12] Engle, R., Lilien, D., Robins, R. (1987). Estimating time varying risk premia in the term structure: The ARCH-M model, Econometrica, 55: 391-407.
[13] Engle, R., Ng, V. (1993). Measuring and testing the impact of news on volatility, Journal of Finance, 48: 1749-1778.
[14] Glosten, L., Jagannathan, R., Runkle, D. (1993). On the relation between the expected value and volatility of the nominal excess return on stocks, Journal of Finance, 48: 1779-1801.
[15] Harrison, P., Zhang, H-H. (1999). An investigation of the risk and return relation at long horizons, Review of Economics and Statistics, 81: 399-408.
[16] Hatemi-J, A., Irandoust, M. (2011). The dynamic interaction between volatility and returns in the US stock market using leveraged bootstrap simulations, Research in International Business and Finance, 25: 329-334.
[17] Mukhopdhyay, D., Sarkar, N. (2013). Stock returns under alternative volatility and distributional assumption: the case for India, International Econometric Review, 5(1): 1-19.
[18] Nelson, D. (1991). Conditional heteroskedasticity in asset returns. A new approach, Econometica, 59: 347-370.
[19] Salvadore, E., Floros, C., Arago, V. (2014). Re-examining the risk-return relationship in Europe: linear or non-linear trade-off?, Journal of Empirical Finance, 28: 60-77.
[20] Tanha, H., Dempsey, M. (2015). The asymmetric response of volatility to market changes and the volatility smile: Evidence from Australian options, Research in International Business and Finance, 34: 164-176.
[21] Xing, X., Howe, J.H. (2003). The empirical relationship between risk and return: Evidence from the UK stock market, International Review of Financial Analysis, 12: 329-346.
[22] Zakoian, J.M. (1994). Threshold heteroskedastic models, Journal of Economic Dynamic and Control, 18: 931-955.
[23] Zivot, E. (2008). Practical issues in the analysis of univariate GARCH models, Unpublished Manuscript.
Published
2017-05-09
How to Cite
THAKOLSRI, Supachok; SETHAPRAMOTE, Yuthana; JIRANYAKUL, Komain. Asymmetric Volatility of the Thai Stock Market. Evidence from High-Frequency Data. Journal of Advanced Studies in Finance, [S.l.], v. 6, n. 2, may 2017. ISSN 2068-8393. Available at: <https://journals.aserspublishing.eu/jasf/article/view/993>. Date accessed: 22 dec. 2024. doi: https://doi.org/10.14505//jasf.v6.2(12).02.
Section
Journal of Advanced Studies in Finance