Product Description
by Kevin T. Webster (Author)
Handbook of Price Impact Modeling provides practitioners and students with a mathematical framework grounded in academic references to apply price impact models to quantitative trading and portfolio management. Automated trading is now the dominant form of trading across all frequencies. Furthermore, trading algorithm rise introduces new questions professionals must answer, for instance:
- How do stock prices react to a trading strategy?
- How to scale a portfolio considering its trading costs and liquidity risk?
- How to measure and improve trading algorithms while avoiding biases?
Price impact models answer these novel questions at the forefront of quantitative finance. Hence, practitioners and students can use this Handbook as a comprehensive, modern view of systematic trading.
For financial institutions, the Handbook's framework aims to minimize the firm's price impact, measure market liquidity risk, and provide a unified, succinct view of the firm's trading activity to the C-suite via analytics and tactical research.
The Handbook's focus on applications and everyday skillsets makes it an ideal textbook for a master's in finance class and students joining quantitative trading desks. Using price impact models, the reader learns how to:
- Build a market simulator to back test trading algorithms
- Implement closed-form strategies that optimize trading signals
- Measure liquidity risk and stress test portfolios for fire sales
- Analyze algorithm performance controlling for common trading biases
- Estimate price impact models using public trading tape
Finally, the reader finds a primer on the database kdb+ and its programming language q, which are standard tools for analyzing high-frequency trading data at banks and hedge funds.
Authored by a finance professional, this book is a valuable resource for quantitative researchers and traders.
Author Biography
Dr. Kevin Webster graduated with a PhD from Princeton University Operations Research and Financial Engineering Department (ORFE). At ORFE, he studied mathematical models applied to high-frequency trading, emphasizing price impact, and market-making models. He previously worked at Deutsche Bank and Citadel and is currently a Visiting Assistant Professor (Visiting Reader) in the Department of Mathematics at Imperial College London.
Dr. Webster created and taught the course, ORF 474 High-Frequency Markets: Models and Data Analysis, as a Visiting Lecturer at Princeton in 2015. His publications include, The Self-Financing Equation in High Frequency Markets, Information and Inventories in High Frequency Trading, A Portfolio Manager's Guidebook to Trade Execution, and High Frequency Market Making.
