Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/157807
Authors: 
Stübinger, Johannes
Endres, Sylvia
Year of Publication: 
2017
Series/Report no.: 
FAU Discussion Papers in Economics 10/2017
Abstract: 
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 conduct a 3-step calibration procedure to the spreads of all pair combinations in a formation period. Top pairs are selected based on their spreads' meanreversion speed and jump behavior. Afterwards, we trade the top pairs in an out-of-sample trading period with individualized entry and exit thresholds. In the back-testing study, the strategy produces statistically and economically significant returns of 60.61 percent p.a. and an annualized Sharpe ratio of 5.30, after transaction costs. We benchmark our pairs trading strategy against variants based on traditional distance and time-series approaches and find its performance to be superior relating to risk-return characteristics. The mean-reversion speed is a main driver of successful and fast termination of the pairs trading strategy.
Subjects: 
finance
statistical arbitrage
pairs trading
high-frequency data
jump-diffusion model
mean-reversion
Document Type: 
Working Paper

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