Statistical Arbitrage: Medium Frequency Portfolio Trading

27 Pages Posted: 25 Jun 2013 Last revised: 9 Jul 2013

Date Written: July 9, 2013

Abstract

Medium frequency trading strategies include all trading activities, that do not require market microstructure analysis on one side and signi cantly depend on market impact on the other side. The most important di erence from high frequency trading is the ability to analyze big amount of data using complex algorithms. Portfolio management in this case is the dynamic process, combination of signal (alpha) discovery and optimal execution on the level of trading scheduling. We used close price and trading volume time series for the list of S&P 500 companies that exist in an index since the beginning of 2008 at least. In this paper we present signal generation approaches as well as optimization of portfolio transactions. Formally the performances of medium frequency statistical arbitrage strategies are much better than the performance of their benchmarks, but they are very sensitive to the quality of trading engine and optimization software. In this minor revision we added the results of out-of-sample tests and explanations of terms and methodology.

Keywords: statistical arbitrage, market impact, trading strategy, optimization

JEL Classification: C22, C44, C52, C61, G11

Suggested Citation

Skachkov, Igor, Statistical Arbitrage: Medium Frequency Portfolio Trading (July 9, 2013). Available at SSRN: https://ssrn.com/abstract=2284577 or http://dx.doi.org/10.2139/ssrn.2284577

Register to save articles to
your library

Register

Paper statistics

Downloads
1,724
Abstract Views
6,155
rank
9,276
PlumX Metrics