How Liquidity and Signal Autocorrelation Shape Optimal Turnover

Summary

The article derives steady-state turnover for an optimized trading strategy in a Gaussian process model. It relates turnover to asset liquidity, risk aversion, and the autocorrelation of alpha forecasts, providing a closed-form expression under the model’s assumptions. The result is intended to clarify how trading intensity changes as forecast signals mean-revert at different speeds relative to a liquidity-adjusted risk-aversion parameter.

The stated relationship makes turnover proportional to that adjusted risk-aversion measure times the square root of one plus a ratio involving signal mean-reversion speed. This gives practitioners a tractable way to connect forecast persistence and liquidity conditions with expected steady-state trading activity. The document offers a model result rather than empirical validation, and its applicability depends on the Gaussian setup and the definitions of its parameters; it does not provide a broader account of costs, constraints, or realized strategy performance.

Key ideas

• The article derives steady-state strategy turnover explicitly in a Gaussian process model.
• Turnover depends on liquidity-adjusted risk aversion and the mean-reversion speed of alpha forecasts.
• The reported formula scales with the square root of one plus the ratio of mean-reversion speed to adjusted risk aversion.
• The result connects signal persistence and liquidity to expected trading activity.
• The conclusion is model-based, and the document does not report empirical performance tests.

Tags

# Optimal Turnover, Liquidity, and Autocorrelation


# Optimal Turnover, Liquidity, and Autocorrelation









The steady-state turnover of a trading strategy is of clear interest to practitioners and portfolio managers, as is the steady-state Sharpe ratio. In this article, we show that in a convenient Gaussian process model, the steady-state turnover can be computed explicitly, and obeys a clear relation to the liquidity of the asset and to the autocorrelation of the alpha forecast signals. Indeed, we find that steady-state optimal turnover is given by $γ\sqrt{n+1}$ where $γ$ is a liquidity-adjusted notion of risk-aversion, and $n$ is the ratio of mean-reversion speed to $γ$.

Shown in full with attribution under the source's licence. Licence: abstract CC0

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