High-Frequency copula-based pairs trading on U.S. Goldmine Stocks

Pairs trading is an often deployed trading strategy by hedge funds which exploits relative mispricing within two assets. In the present thesis, we empirically evaluate several copula-based pairs trading variants against the two most commonly used pairs trading frameworks, the distance and the cointegration approach. Additionally, we examine the use of the non-linear correlation measures Kendall’s τ and Spearman’s ρ as pairs selection criteria- next to the conventional methods, the Euclidean distance and the degree of spread mean-reversion. Overall, we compare the performance of either strategy and selection criterion by means of a high-frequency trading strategy on U.S. goldmine stocks, covering the time between January 1998 and April 2016. Before transaction costs, we find all pairs trading method-ologies to be highly profitable with daily mean excess returns of 13 - 104 bps and annual Sharpe ratios of up to 6.25. Furthermore, neither strategy is greatly exposed to systematic risk factors, leading to economically and statistically significant alphas. The simple distance approach achieves highest excess returns, followed by the cointegration method. On the contrary, the copula based framework performs comparably poor due to falsely estimated parameter. Among the selection criteria, we find the degree of spread mean-reversion to be most lucrative, followed by Kendall’s τ. After transaction costs, however, we observe a different picture. Strongly declining returns in recent years suggest that neither of the variants remain profitable. Furthermore, both non-linear correlation measures outperform the conventional criteria in terms of lower risk and higher average returns.