Pairs trading with a mean-reverting jump-diffusion model on high-frequency data

Johannes Stübinger and Sylvia Endres

No 10/2017, FAU Discussion Papers in Economics from Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics

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.

Keywords: finance; statistical arbitrage; pairs trading; high-frequency data; jump-diffusion model; mean-reversion (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-mst
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Citations: View citations in EconPapers (5)

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