Non-linear dependence modelling with bivariate copulas: statistical arbitrage pairs trading on the S&P 100

Christopher Krauss and Johannes Stübinger

Applied Economics, 2017, vol. 49, issue 52, 5352-5369

Abstract: We develop a copula-based pairs trading framework and apply it to the S&P 100 index constituents from 1990 to 2014. We propose an integrated approach, relying on copulas for pairs selection and trading. Essentially, we fit t-copulas to all possible combinations of pairs in a formation period. Next, we trade these pairs in-sample to assess the profitability of mispricing signals derived from t-copulas. The top pairs are transferred to an out-of-sample trading period, and traded with individualized exit thresholds. In particular, we differentiate between pairs exhibiting mean-reversion and momentum effects and apply idiosyncratic take-profit and stop-loss rules. For the top 5 mean-reversion pairs, we find out-of-sample returns of 7.98% per year; the top 5 momentum pairs yield 7.22% per year. Standard deviations are low, leading to annualized Sharpe ratios of 1.52 (top 5 mean-reversion) and 1.33 (top 5 momentum), respectively.

Date: 2017
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Citations: View citations in EconPapers (7)

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DOI: 10.1080/00036846.2017.1305097

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