The Science of Algorithmic Trading and Portfolio Management: Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques

by Robert Kissell

The Science of Algorithmic Trading and Portfolio Management , with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects.

Genres: Finance

496 pages, Hardcover

First published January 1, 2013

Reviews

[Elruin Elmsroot · Rating 2 out of 5]

This book covers algorithmic trading and portfolio management in theory, but it’s too academic and not practical for real-world trading. Examples are simplistic and offer little actionable insight for serious traders. Useful as a reference, but disappointing for implementation-focused readers.