Statistical arbitrage with vine copulas

Arbeitspapier

We develop a multivariate statistical arbitrage strategy based on vine copulas - a highly flexible instrument for linear and nonlinear multivariate dependence modeling. In an empirical application on the S&P 500, we find statistically and economically significant returns of 9.25 percent p.a. and a Sharpe ratio of 1.12 after transaction costs for the period from 1992 until 2015. Tail risk is limited, with maximum drawdown at 6.57 percent. The high returns can only partially be explained by common sources of systematic risk. We benchmark the vine copula strategy against other variants relying on the multivariate Gaussian and t-distribution and we find its results to be superior in terms of risk and return characteristics. The multivariate dependence structure of the vine copulas is time-varying, and we see that the share of copulas capable of modeling upper and lower tail dependence increases well over 90 percent at times of high market turmoil.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: FAU Discussion Papers in Economics ; No. 11/2016

Classification and Topics

• Classification: Wirtschaft
• Subject: finance ; statistical arbitrage ; pairs trading ; quantitative strategies ; copulas

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Stübinger, Johannes ; Mangold, Benedikt ; Krauss, Christopher
• Event: Veröffentlichung
• (who): Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute for Economics
• (where): Nürnberg
• (when): 2016

Further information

• Handle: http://hdl.handle.net/10419/147450
• Last update: 10.03.2025, 11:43 AM CET