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Forecasting the Stock Exchange of Thailand uses Day of the Week Effect and Markov Regime Switching GARCH

Author

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  • P. Sattayatham
  • N. Sopipan
  • B. Premanode

Abstract

Problem statement: We forecast return and volatility of the Stock Exchange of Thailand (SET) Index. Approach: In this study, we modeled the SET Index returns using mean equation with day of the week effect and autoregressive moving-average. Next we forecast the volatility of the SET Index by using the GARCH-type model and the Markov Regime Switching GARCH (MRS-GARCH) model. Results: When we model the SET Index by the ARMA (3, 3) process, we find that Friday is the day of the effect of the SET Index. The empirical analysis demonstrates that the MRS-GARCH models outperform all GARCH-type models in forecasting volatility at long term horizons (two weeks and a month). Conclusion: The ARMA (3, 3) and the Friday is the day of the effect of the SET Index return. The MRS-GARCH models outperform at long term horizons.

Suggested Citation

  • P. Sattayatham & N. Sopipan & B. Premanode, 2012. "Forecasting the Stock Exchange of Thailand uses Day of the Week Effect and Markov Regime Switching GARCH," American Journal of Economics and Business Administration, Science Publications, vol. 4(1), pages 84-93, March.
    • Handle: RePEc:abk:jajeba:ajebasp.2012.84.93
    DOI: 10.3844/ajebasp.2012.84.93
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    1. Marcucci Juri, 2005. "Forecasting Stock Market Volatility with Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-55, December.
    2. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    3. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    4. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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