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, using copulas for pairs selection and trading. Essentially, we fit t-copulas to all possible combinations of pairs in a 12 month formation...

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...

This paper develops a pairs trading framework based on a mean-reverting jump-diffusion model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to 2015. The established statistical arbitrage strategy enables us to perform intraday and overnight trading. Essentially,...

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...

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, using copulas for pairs selection and trading. Essentially, we fit t-copulas to all possible combinations of pairs in a 12 month formation...

This paper develops a pairs trading framework based on a mean-reverting jump-diffusion model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to 2015. The established statistical arbitrage strategy enables us to perform intraday and overnight trading. Essentially,...