Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/147450
Authors: 
Stübinger, Johannes
Mangold, Benedikt
Krauss, Christopher
Year of Publication: 
2016
Series/Report no.: 
FAU Discussion Papers in Economics 11/2016
Abstract: 
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.
Subjects: 
finance
statistical arbitrage
pairs trading
quantitative strategies
copulas
Document Type: 
Working Paper

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