Abstract
Pair trading is a popular strategy. The concept of pair trading consists of two processes. First, find two stocks whose prices tend to move together. Second, short the overvalued stock and buy the undervalued stock simultaneously when the spread between the prices diverges. A profit between the prices will be made if the prices converge again. The return from the strategy is often uncorrelated with market return because the market risk can be eliminated by shorting the overvalued stock and buying the undervalued stock simultaneously. Therefore, the results of the strategy must have a lower risk than trading each stock in the market. The purpose of this study is to find the trading signal for the pair-trading strategy in Stock Exchange of Thailand (SET). The proposed trading signal for pair-trading strategy can generate a higher return when compared with trading in individual stocks. The investors can employ it to gain the better profit in their portfolios. We propose Markov-switching GARCH model for pair-trading strategy. The model is considered with two regimes which have different variance in each regime. The average of the two variances is used as trading signal. We apply the pair-trading strategy to SET100 index based on the most 100 liquid stocks. The pairs formation period is over 1 January 2016 to 12 December 2016 and the trading period is over 2 January 2017 to 29 December 2017. The empirical results show that the trading signals of the Markov-switching GARCH model generate positive return for all selected pairs and provide the highest return of up to 14.267%. The return from pair-trading strategy is higher than the return from trading in individual stocks.
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References
Bock, M., Mestel, R.: A regime-switching relative value arbitrage rule. In: Operations Research Proceedings 2008, pp. 9–14. Springer, Heidelberg (2009)
Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. J. Econ. 31(3), 307–327 (1986)
Chen, C.W., Chen, M., Chen, S.Y.: Pairs trading via three-regime threshold autoregressive GARCH models. In: Modeling Dependence in Econometrics, pp. 127–140. Springer, Cham (2014)
Chen, C.W., Wang, Z., Sriboonchitta, S., Lee, S.: Pair trading based on quantile forecasting of smooth transition GARCH models. N. Am. J. Econ. Financ. 39, 38–55 (2017)
Chodchuangnirun, B., Zhu, K., Yamaka, W.: Pairs trading via nonlinear autoregressive GARCH models. In: International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, pp. 276–288. Springer, Cham, March 2018
Do, B., Faff, R., Hamza, K.: A new approach to modeling and estimation for pairs trading. In: Proceedings of 2006 Financial Management Association European Conference, pp. 87–99, May 2006
Do, B., Faff, R.: Does simple pairs trading still work? Financ. Anal. J. 66(4), 83–95 (2010)
Elliott, R.J., Van Der Hoek, J., Malcolm, W.P.: Pairs trading. Quant. Financ. 5(3), 271–276 (2005)
Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econ. J. Econ. Soc. 50, 987–1007 (1982)
Engle, R.F., Granger, C.W.: Co-integration and error correction: representation, estimation, and testing. Econ. J. Econ. Soc. 55, 251–276 (1987)
Gatev, E., Goetzmann, W.N., Rouwenhorst, K.G.: Pairs trading: performance of a relative-value arbitrage rule. Rev. Financ. Stud. 19(3), 797–827 (2006)
Haas, M., Mittnik, S., Paolella, M.S.: A new approach to Markov-switching GARCH models. J. Financ. Econ. 2(4), 493–530 (2004)
Hamilton, J.D.: A new approach to the economic analysis of nonstationary time series and the business cycle. Econ. J. Econ. Soc. 57, 357–384 (1989)
Hamilton, J.D.: Time Series Analysis, vol. 2, pp. 690–696. Princeton University Press, Princeton (1994)
Vidyamurthy, G.: Pairs Trading: Quantitative Methods and Analysis, vol. 217. John Wiley & Sons (2004)
Yang, J.W., Tsai, S.Y., Shyu, S.D., Chang, C.C.: Pairs trading: the performance of a stochastic spread model with regime switching-evidence from the S&P 500. Int. Rev. Econ. Financ. 43, 139–150 (2016)
Zhu, K., Yamaka, W., Sriboonchitta, S.: Pair trading rule with switching regression GARCH model. In: International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, pp. 586–598. Springer, Cham, November 2016
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Namwong, N., Yamaka, W., Tansuchat, R. (2019). Trading Signal Analysis with Pairs Trading Strategy in the Stock Exchange of Thailand. In: Kreinovich, V., Sriboonchitta, S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Computational Intelligence, vol 808. Springer, Cham. https://doi.org/10.1007/978-3-030-04263-9_29
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DOI: https://doi.org/10.1007/978-3-030-04263-9_29
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