Mathematical Finance & Financial Data Science Seminar

Optimal turnover, liquidity and autocorrelation

Speaker: Bastien Baldacci and Jerome Benveniste, Quantitative Advisory Solutions and Ritter Alpha LP

Location: Online Zoom access provided to registrants

Date: Tuesday, April 19, 2022, 5:30 p.m.


 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 $\gamma\sqrt{n_1}$ where $\gamma$ is a liquidity-adjusted notion of risk-aversion and $n$ is the ratio of mean-reversion speed to $\gamma$.


Bastien is an advisor for buy/sell side and reinsurance companies.  He holds a PhD in Applied Mathematics, with an emphasis on market-microstructure and options market-making from Ecole Polytechnique.  Bastien, along with Iuliia Manziuk, were awarded the 2021 Risk Rising Star in Quant Finance prize for their work on smart-order routing.

Jerome Benveniste is senior research scientist and co-head of Equity Statistical Arbitrage at Ritter Alpha LP and an adjunct professor of financial mathematics at NYU. He was previously co-portfolio manager of the quantitative trading group at Highbridge Capital Management. He holds a B.A. from Harvard College and a Ph. D. from the University of Chicago, both in mathematics, and was on the faculty at Stanford and Case Western Reserve Universities.



This event is free, but requires registration. Please click here to register. You will then receive the Zoom link by email about a day or so before the event.