Algorithmic Trading and Quantitative Strategies

Raja Velu, Maxence Hardy, Daniel Nehren

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Hardback

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English

Chapman & Hall/CRC
06 August 2020

Economic statistics; Investment & securities; Applied mathematics

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner’s hands-on experience. The focus on empirical modeling and practical know-how makes this book a valuable resource for students and professionals.

The book starts with the often overlooked context of why and how we trade via a detailed introduction to market structure and quantitative microstructure models. The authors then present the necessary quantitative toolbox including more advanced machine learning models needed to successfully operate in the field. They next discuss the subject of quantitative trading, alpha generation, active portfolio management and more recent topics like news and sentiment analytics. The last main topic of execution algorithms is covered in detail with emphasis on the state of the field and critical topics including the elusive concept of market impact. The book concludes with a discussion of the technology infrastructure necessary to implement algorithmic strategies in large-scale production settings.

A GitHub repository includes data sets and explanatory/exercise Jupyter notebooks. The exercises involve adding the correct code to solve the particular analysis/problem.

By: Raja Velu, Maxence Hardy, Daniel Nehren
Imprint: Chapman & Hall/CRC
Country of Publication: United States
Dimensions: Height: 234mm, Width: 156mm,
Weight: 900g
ISBN: 9781498737166
ISBN 10: 1498737161
Pages: 450
Publication Date: 06 August 2020
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Hardback
Publisher's Status: Active

1. Trading Fundamentals. 2. Univariate Time Series Models 3. Multivariate Time Series Models 4. Advanced Topics5. Statistical Trading Strategies and Back-Testing 6. Dynamic Portfolio Management and Trading Strategies 7. News Analytics: From Market Attention and Sentiment to Trading 8. Modeling Trade Data 9. Market Impact Models 10. Execution Strategies 11. The Technology Stack 12. The Research Stack

Raja Velu is a professor of Finance and Analytics in Whitman School of Management at Syracuse University. He served as a Technical Architect at Yahoo! in the Sponsored Search Division and was a visiting scientist at IBM-Almaden, Microsoft Research, Google and JPMC. He has also held visiting positions at Stanford's Statistics department, Indian School of Business, the National University of Singapore, and Singapore Management University. Maxence Hardy is a Managing Director and the Head of eTrading Quantitative Research for Equities and Futures at J.P.Morgan, based in New York. Mr. Hardy is responsible for the development of agency algorithmic trading strategies for the Equities and Futures divisions globally. Daniel Nehren is a Managing Director and the Head of Statistical Modelling and Development for Equities at Barclays. Based in New York, Mr. Nehren is responsible for the development of algorithmic trading and analytics products. Mr. Nehren has more than 19 years of experience in equity trading working for some of the most prestigious financial firms including Citadel, J.P Morgan, and Goldman Sachs.

Reviews for Algorithmic Trading and Quantitative Strategies

This work does a marvelous job of emphasizing the dual significance of determining the fair value of an asset as well as designing the optimal way to interact with the markets. Optimizing valuation is equally important to optimizing order execution. Both skills must be mastered to avoid selection bias and capturing value. This book must be read! ~Peter J. Layton, Principal, Blackthorne Capital Management, LLC An outstanding and timely synthesis of the state of art algorithmic trading ideas. I will recommend it to all who is serious on the foundations. ~Guofu Zhou, Frederick Bierman and James E. Spears, Professor of Finance, Olin Business School, Washington University in St. Louis This work does a marvelous job of emphasizing the dual significance of determining the fair value of an asset as well as designing the optimal way to interact with the markets. Optimizing valuation is equally important to optimizing order execution. Both skills must be mastered to avoid selection bias and capturing value. This book must be read! ~Peter J. Layton, Principal, Blackthorne Capital Management, LLC An outstanding and timely synthesis of the state of art algorithmic trading ideas. I will recommend it to all who is serious on the foundations. ~Guofu Zhou, Frederick Bierman and James E. Spears, Professor of Finance, Olin Business School, Washington University in St. Louis