Speed Bumps and Swells: Rethinking Optimal Trading with Stochastic Volatility
TL;DR for operators Execution desks already know that volatility matters. The useful question is less poetic: which volatility, on what time scale, and what should the trading algorithm actually do about it? The paper by Patrick Chan, Ronnie Sircar, and Iosif Zimbidis extends the Gârleanu-Pedersen optimal trading framework from constant volatility to predictable returns, temporary transaction costs, persistent price impact, and multiscale stochastic volatility.1 That combination matters because it puts the model closer to the daily problem of a trading desk: alpha is changing, risk is changing, and the desk’s own trades are also moving the price. Delightful. The market is not merely adversarial; it is participatory. ...