Disentangling alpha from impact using causal machine learning
Kevin Webster (Columbia University)
Thursday 1 June 2023 @ 18:00
Brokers face an essential challenge in Transaction Cost Analysis (TCA): correctly estimating price impact considering a client’s alpha. Using live trading experiments, causal regularization estimates price impact when client alpha is unknown. In addition to satisfying best execution requirements, such an analysis empowers trading algorithms that rely on price impact models, such as Almgren and Chriss’ shortfall execution algorithm. Using a realistic order simulator, the paper quantifies these benefits for a canonical live trading experiment. This is joint work with Nick Westray.
About the speaker
Kevin Webster is an adjunct assistant professor at Columbia University and a visiting reader at Imperial College, London. He has ten years of experience building large-scale, systematic, and model-driven frameworks for trading and has deployed algorithms for top-tier financial institutions such as Citadel, Deutsche Bank, and BNP Paribas. Kevin graduated with a Ph.D. from Princeton University's Operations Research and Financial Engineering Department (ORFE), where he studied mathematical models applied to high-frequency trading, emphasizing price impact and market making. Kevin Webster authored the Handbook of Price Impact Modeling. His research papers include "Do You Really Know Your P&L? The Importance of Impact-Adjusting the P&L," with Petter Kolm, "Stochastic Liquidity as a Proxy for Nonlinear Price Impact," with Johannes Muhle-Karbe and Zexin Wang, "Getting More for Less - Better A/B Testing via Causal Regularization," with Nick Westray, and "The Self-Financing Equation in High Frequency Markets," with Rene Carmona.
Citi Stirling Square, 5-7 Carlton Gardens, London SW1Y 5AD
The seminar begins at 6:00 PM. Seating cannot be guaranteed for late arrivals.
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