Pairs Trading; A Comparison between Student-t and Vine Copulas | ||
| تحقیقات مالی | ||
| Volume 24, Issue 1, 2022, Pages 104-133 PDF (570.64 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.22059/frj.2021.325404.1007200 | ||
| Authors | ||
| Maryam Davallou* 1; Ardavan Yazdi2 | ||
| 1Associate Prof., Department of Financial Management and Insurance, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran. | ||
| 2MSc., Department of Business Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran. | ||
| Abstract | ||
| Objective: The main purpose of the present research was to compare the performance of pairs trading based on the Vine Copula, Student's t Copula, and Distance approaches. This was done for the first time on the Tehran Stock Exchange (TSE). The main advantage of the Copula approach over other common approaches in pairs trading, such as the Distance approach, is that in this approach it is not necessary for the stock return distribution to follow the Gaussian distribution. Methods: In the Distance approach, for each sample stock, a stock with the same price behavior was selected, the undervalued stock was bought and the rest was sold. In the Copula approach, first, similar stocks were selected using the traditional and geometric approach. Then Copula functions were fitted among stocks. In Vine Copula, different families of Copula were fitted and the best Copula was determined based on the Akaike Information Criterion (AIC). Then, the pairs with the most mean-reverting characteristic was selected and transferred to the trading period, in order to execute appropriate trading positions. Finally, the return, Sharp ratio, Value at Risk (VaR), maximum drawdown of the Distance approach strategies, the Student's t Copula and the Vine Copula, were compared. The performance of the pairs trading strategy was tested according to the downtrend and non-downtrend conditions of the stock market. Results: Both Copula approach strategies produced higher returns and Sharp ratios than the Distance approach and the Tehran Stock Exchange Index (TEDPIX). However, the Distance approach had a lower performance than the TEDPIX. The annual returns of the Vine Copula strategy, Student's t Copula strategy, and Distance approach stood at 194, 171, and 20 percent, respectively. The Sharp ratios of these three strategies were 0.79, 0.70 and -0.04, respectively. Also, the performance of pairs trading strategy in non-downtrend market conditions was better than downtrend market conditions. Conclusion: As expected, due to the many advantages of the Copula approach over the Distance approach, both strategies based on the Copula approach produced higher returns and sharper ratio than the Distance approach. Also, due to the greater flexibility of the Vine Copula in modeling the dependence structure, this Copula could produce a higher return and Sharp ratio than the Student's t Copula. | ||
| Keywords | ||
| Distance approach; Pairs trading; Student’s t copula; Vine copula | ||
| References | ||
|
Asgaripor, M. & Abou, Z. (2012). Evaluation of the effectiveness of pairs trading strategy on gold coin future contracts by combining random and cointegration approaches. 3rd Conference on Financial Mathematics and Applications. Semnan University. (in Persian) Avellaneda, M. & Lee, J.-H. (2010). Statistical arbitrage in the US equities market. Quantitative Finance, 10(7), 761–782. Azizzadeh, F. & Ebadi, N. (2017). Optimal Pairs Trading strategy under Statistical Variability of the Spread Process. Financial Engineering and Portfolio Management, 8(33), 229-246. (in Persian) Bajalan, S., Eyvazlu, R. & Akbari, G. (2018). Pair Trading in Tehran Stock Exchange based on Smooth Transition GARCH Model. Iranian Journal of Finance, 2(2), 7-28. Baronyan, S. R., Boduroğlu, I. I. & Şener, E. (2010). Investigation of stochastic pairs trading strategies under different volatility regimes. The Manchester School, 78, 114-134. Bianchi, R., Drew, M. & Zhu, R. (2009). Pairs trading profits in commodity futures markets. In Proceedings of Asian Finance Association 2009 International Conference, pp. 1–26. University of Queensland. Bock, M. & Mestel, R. (2009). A regime-switching relative value arbitrage rule. In Operations Research Proceedings 2008, pp. 9–14. Springer, Berlin, Heidelberg. Bollinger, J. (1992). Using bollinger bands. Stocks & Commodities, 10(2), 47-51. Chen, H., Chen, S., Chen, Z. & Li, F. (2012). Empirical investigation of an equity pairs trading strategy. Management Science, 65(1), 370-389. Cherubini, U., Luciano, E. & Vecchiato, W. (2004). Copula methods in finance. John Wiley & Sons. Do, B. & Faff, R. (2010). Does simple pairs trading still work? Financial Analysts Journal, 66(4), 83–95. Do, B. & Faff, R. (2012). Are pairs trading profits robust to trading costs? Journal of Financial Research, 35(2), 261–287. Engelberg, J., Gao, P. & Jagannathan, R. (2009). An anatomy of pairs trading: the role of idiosyncratic news, common information and liquidity. The 3rd Singapore International Conference on Finance. Engle, R. F. & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276. Fallahpour, S. & Hakimian, H. (2017). Evaluating the Performance of a Pairs Trading System in Tehran Stock Exchange: The Cointegration Approach and Sortino Ratio Analysis. Financial Engineering and Portfolio Management, 8(30), 1-17. (in Persian) Ferreira, L. (2008). New tools for spread trading. Futures: News, Analysis & Strategies for Futures, Options & Derivatives Traders, 37(12), 38–41. Fischer, M., Köck, C., Schlüter, S. & Weigert, F. (2009). An empirical analysis of multivariate copula models. Quantitative Finance, 9(7), 839-854. Gatev, E., Goetzmann, W.N. & Rouwenhorst, K.G. (2006). Pairs trading: performance of a relative-value arbitrage rule. Review of Financial Studies, 19(3), 797–827. Goldkamp, J. & Dehghani Mohammadabadi, M. (2019). Evolutionary multi-objective optimization for multivariate pairs trading. Expert Systems with Applications, 135, 113-128. Gupta, K. & Chatterjee, N. (2020). Selecting stock pairs for pairs trading while incorporating lead–lag relationship. Physica A: Statistical Mechanics and its Applications, 551, 124103. Huck, N. (2009). Pairs selection and outranking: an application to the S&P 100 index. European Journal of Operational Research, 196(2), 819–825. Huck, N. (2010). Pairs trading and outranking: the multi-step-ahead forecasting case. European Journal of Operational Research, 207(3), 1702–1716. Huck, N. and Afawubo, K. (2015). Pairs trading and selection methods: is cointegration superior? Applied Economics, 47(6), 599–613. Jacobs, H. & Weber, M. (2013). Losing sight of the trees for the forest? Attention shifts and pairs trading. Working paper, University of Mannheim. Jacobs, H. & Weber, M. (2015). On the determinants of pairs trading profitability. Journal of Financial Markets, 23, 75–97. Jalilian, J. & Asgaripor, M. (2016). Designing and Implementation of Pair Trading Strategy Software in Iran Stock Market. Journal of Financial Management Strategy, 3(4), 107-123. (in Persian) Keshavarz Haddad, G. & Talebi, H. (2021). The profitability of pair trading strategy in stock markets: Evidence from Toronto stock exchange. International Journal of Finance & Economics. Kim, T. H. & White, H. (2004). On more robust estimation of skewness and kurtosis. Finance Research Letters, 1(1), 56-73. Knoll, J., Stübinger, J. & Grottke, M. (2019). Exploiting social media with higher-order factorization machines: Statistical arbitrage on high-frequency data of the S&P 500. Quantitative Finance, 19(4), 571-585. Krauss, C. (2017). Statistical arbitrage pairs trading strategies: Review and outlook. Journal of Economic Surveys, 31(2), 513-545. Krauss, C. & Stübinger, J. (2017). Non-linear dependence modelling with bivariate copulas: Statistical arbitrage pairs trading on the S&P 100. Applied Economics, 49(52), 5352-5369. Liew, R.Q. & Wu, Y. (2013). Pairs trading: a copula approach. Journal of Derivatives & Hedge Funds, 19(1), 12–30. Lin, Y.-X., McCrae, M. & Gulati, C. (2006). Loss protection in pairs trading through minimum profit bounds: a cointegration approach. Journal of Applied Mathematics and Decision Sciences, 2006, 1–14. Mina, J. & Xiao, J. Y. (2001). Return to RiskMetrics: the evolution of a standard. RiskMetrics Group, 1, 1-11. Pakizeh, K. & Habibi, S. (2017). Comparing Profitability of the Pair Trading Strategy in Different Asset Classes. Asset Management and Financing, 4(19), 69-88. (in Persian) Papadakis, G. & Wysocki, P. (2007). Pairs trading and accounting information. Working paper, Boston University and MIT. Perlin, M. (2007). M of a kind: A Multivariate Approach at Pairs Trading. Available at SSRN 952782. Rad, H., Low, R. K. Y. & Faff, R. (2016). The profitability of pairs trading strategies: distance, cointegration and copula methods. Quantitative Finance, 16(10), 1541-1558. Stübinger, J., Mangold, B. & Krauss, C. (2018). Statistical arbitrage with vine copulas. Quantitative Finance, 18(11), 1831-1849. Trivedi, P. K. & Zimmer, D. M. (2007). Copula modeling: an introduction for practitioners. Now Publishers Inc. Vidyamurthy, G. (2004). Pairs Trading: quantitative methods and analysis (Vol. 217). John Wiley & Sons. Xie, W. & Wu, Y. (2013). Copula-based pairs trading strategy. In Asian Finance Association (AsFA) 2013 Conference. Xie, W., Liew, R. Q., Wu, Y. & Zou, X. (2016). Pairs trading with copulas. The Journal of Trading, 11(3), 41-52. | ||
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