Modeling Stock Market Impact Costs in Portfolio Optimization

Summary

This research summary describes an A-share market-impact model intended to narrow the gap between simulated strategy returns and realized portfolio returns. It argues that applying one fixed slippage rate cannot reflect how impact varies across stocks, dates, and order sizes. The proposed approach fits a power-function relationship between active order amount and impact cost using historical active buy and sell order data, with stock liquidity, volatility, and market activity identified as relevant influences.

The report then incorporates estimated impact costs into a portfolio optimization objective and compares simulated portfolios at several initial capital levels. Its stated finding is that accounting for impact can reduce theoretical alpha while improving realized, after-impact returns, with larger portfolios benefiting more. The document provides only a high-level summary: it omits the model specification, fitted parameter values, sample design, detailed performance results, and robustness checks. Its conclusions should therefore be read as a report synopsis rather than enough information to reproduce or independently assess the model.

Key ideas

• A single fixed slippage assumption may not capture variation in market impact across stocks, dates, and order sizes.
• The proposed power-function model relates active trade amount to stock impact costs.
• The summary identifies liquidity, volatility, and market activity as factors associated with impact.
• Including impact estimates in portfolio optimization may lower modeled alpha while improving realized returns.
• The reported benefit is described as more pronounced for larger portfolios, but supporting details are not included.

Tags

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