Finding Alphas: A Quantitative Approach to Building Trading Strategies

by Igor Tulchinsky

Design more successful trading systems with this practical guide to identifying alphas Finding Alphas seeks to teach you how to do one thing and do it design alphas. Written by experienced practitioners from WorldQuant, including its founder and CEO Igor Tulchinsky, this book provides detailed insight into the alchemic art of generating trading signals, and gives you access to the tools you need to practice and explore. Equally applicable across regions, this practical guide provides you with methods for uncovering the hidden signals in your data. A collection of essays provides diverse viewpoints to show the similarities, as well as unique approaches, to alpha design, covering a wide variety of topics, ranging from abstract theory to concrete technical aspects. You'll learn the dos and don'ts of information research, fundamental analysis, statistical arbitrage, alpha diversity, and more, and then delve into more advanced areas and more complex designs. The companion website, www.worldquantchallenge.com, features alpha examples with formulas and explanations. Further, this book also provides practical guidance for using WorldQuant's online simulation tool WebSim® to get hands-on practice in alpha design. Alpha is an algorithm which trades financial securities. This book shows you the ins and outs of alpha design, with key insight from experienced practitioners. Finding Alphas is the detailed, informative guide you need to start designing robust, successful alphas.

Genres: Finance

331 pages, Kindle Edition

First published August 28, 2015

Reviews

[Max Bolingbroke]

Two books in one.

The first is a shallow overview of some potential alphas that doesn’t go much beyond a few sentences of description and motivation for each. You could get a better understanding of this topic by just spending half a day on SSRN.

The second book is a tutorial and FAQ for their WebSim backtesting platform. This seems to be squarely aimed at potential users such as university students, and was mostly interesting for me to the extent that it revealed how unsophisticated WebSim is.

[Jack]

This book focuses on equities and I found it informative.

For me its biggest strength is the breadth of data sources (non alternative) it explores for alpha discovery including price and volume signals, fundamental data, options data, analyst coverage, and earnings call language processing. I liked how this books consistently refers to academic research that evaluated the predictive power of each of these information sources. I also liked the chapter on avoiding overfitting, it concisely goes over different methods available to navigate the tradeoff between alpha discovery and in sample model overfitting.

While the chapter on factor models was very useful it felt incomplete because it lacked the mathematical notation of Barra style factor models and didn't discuss how the process of discovering alpha orthogonal fits in such a framework. Though readers with prior knowledge of factor models / hedge fund betas can fill in this gap, it prevented the book from being a 5/5.

[Juan Pablo]

Working for worldquant, the company of the author of this book revolutionaze the way I saw the stock market. This book has good material for algorithmic trading. The downside is that you have to connect the dots and most of the book must be implemented in their platform.

[Anthony]

Felt like an interesting split for people familiar with investing but not familiar with alpha generation. Papers and a tease into how structured and foundational alpha generation has to be when you start thinking of scale. Valuable for those getting into the mix.

[Kevin Peng]

good broad collection of quant subjects

Not too deep and understandable. Written by portfolio manager who don't B's. They give me insight even though not alpha they are using.

[Vasile-Simion Sularea]

Good overall intro into how you could approach this issue. The latter half of the book is just a manual for a proprietary tool

[Hüseyin Çötel]

Meh cogu quant kitabina gore daha basit yazilmis ama iverigi zayif.

[Diniar]

I want to start reading this book

[Hongliang Ma]

good introductory book for alpha researchers