Optimizing Paired-Stock Execution Under Cross-Impact Costs

Summary

This study extends a single-stock execution framework to trades in two stocks, accounting for cross-impact: trading one stock can move the price of the other. It represents a strategy through the stocks’ trading rates and the ratio of their execution periods, then seeks the schedule that minimizes costs attributable to those interactions.

The paper applies the model to a specific empirical case, estimating cross-impact from traded volumes and time lags to calculate execution costs and illustrate how these effects shape the preferred strategy. The document describes a framework and empirical application, but gives no detailed data, numerical findings, or comparison with alternative execution methods. Its conclusions therefore depend on the modeled cross-impact relationships and the chosen case; the brief description does not establish how well the strategy generalizes to other stocks, trading conditions, or larger portfolios.

Key ideas

• Cross-impact occurs when trading one stock changes the price of another.
• The framework extends single-stock execution scheduling to a pair of stocks.
• Trading rates and the relative execution periods describe the paired strategy.
• The schedule is chosen to minimize costs associated with cross-impact.
• An empirical case uses traded volumes and time lags to estimate cross-impact costs.

Tags

# Trading strategies for stock pairs regarding to the cross-impact cost


# Trading strategies for stock pairs regarding to the cross-impact cost









We extend the framework of trading strategies of Gatheral [2010] from single stocks to a pair of stocks. Our trading strategy with the executions of two round-trip trades can be described by the trading rates of the paired stocks and the ratio of their trading periods. By minimizing the potential cost arising from cross-impacts, i.e., the price change of one stock due to the trades of another stock, we can find out an optimal strategy for executing a sequence of trades from different stocks. We further apply the model of the strategy to a specific case, where we quantify the cross-impacts of traded volumes and of time lag with empirical data for the computation of costs. We thus picture the influence of cross-impacts on the trading strategy.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.