Estimation of Performance and Execution Time Effect on High-Frequency Statistical Arbitrage Strategies

Abstract

This article is designed to help quantify one of the “slippages” that are often recognized in quant strategies. The idea is that whenever the actual executed prices are away (both time and size) from the model prices, the realized returns suffer. The slippage for a particular statistical arbitrage strategy is quantified. It is shown that a portion of the loss is due to using different prices for estimating the parameters of the strategy. The main source of the loss is the use of intraday in place of market on close prices. Five years of intraday transaction data from the NYSE TAQ database are used. Analysis shows that on average the daily loss due to intraday prices accounts for 0.03% of the initial capital. For the period 2003 through 2006, the accumulated loss is approximately 30%. The described approach can be of use to new quantitative analysts who create and backtest trading strategies. It could also be used during the due diligence process of a fund that is interested in investing in a statistical arbitrage strategy. This article recommends requiring that a backtest be done by using intraday and market on close prices in order to identify the size of such loss.