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.
Synopsis:
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 $\gamma$.
Bio:
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.
Notes:
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.