Finding Alphas

FINDING ALPHAS

A QUANTITATIVE APPROACH TO BUILDING TRADING STRATEGIES

Igor Tulchinsky et al.

WorldQuant Virtual Research Center

This edition first published 2015

© 2015 Igor Tulchinsky et al., WorldQuant Virtual Research Center

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ISBN 978-1-119-05786-4 (hbk) ISBN 978-1-119-05788-8 (ebk)

ISBN 978-1-119-05789-5 (ebk) ISBN 978-1-119-05787-1 (ebk)

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This book is a study of the process of finding alphas. The material is presented as a collection of essays, providing diverse viewpoints from successful quants on the front lines of quantitative trading.

A wide variety of topics is covered, ranging from theories about the existence of alphas, to the more concrete and technical aspects of alpha creation.

Part I presents a general introduction to alpha creation, and is followed by a brief account of the alpha life-cycle, and insights on cutting losses.

Part II focuses more on the technical side of alpha design, such as the dos and don'ts of information research, key steps to developing an alpha, and the evaluation and improvement of quality alphas. The key technical aspects discussed in this section are turnover, backtesting, fundamental analysis, equity price volume, statistical arbitrage, overfitting, and alpha diversity.

Part III explores ad hoc topics in alpha design, including alpha design for various asset classes like futures and currencies, the development of momentum alphas, and the effect of news and social media on stock returns.

In Part IV, we introduce you to WebSim™, a web-based alpha development tool. We invite all quant enthusiasts to utilize this free tool to learn about alpha backtesting (also known as alpha simulation), and ultimately to create their own alphas.

Finally, in Part V, we present an inspirational essay for all quants who are ready to explore the world of quantitative trading.

In these pages, we present readers with a collection of writings on the alchemic art of finding alphas. It is written by WorldQuant's founder, directors, managers, in-house portfolio managers, and quantitative researchers. The key objectives of this collection are twofold – to present many viewpoints as to how to define an alpha, and how to find one. At WorldQuant, we believe no viewpoint is the best and only answer, and that a variety of approaches is always superior to a single one. We also present our online financial markets simulation tool known as WebSim™, which lets users and consultants create, test, simulate, and track alphas.

WorldQuant would like to thank Rohit Agarwal, Ionut Aron, Pankaj Bakliwal, Scott Bender, Hongzhi Chen, Benjamin Ee, Zhuangxi Fang, Paul A. Griffin, Yongfeng He, Richard Hu, Yu Huang, Hammad Khan, Michael Kozlov, Geoffrey Lauprete, Cong Li, Weijia Li, Zhiyu Ma, Sunny Mahajan, Pratik Patel, Kailin Qi, Jeffrey Scott, Xinye Tang, Swastik Tiwari, Igor Tulchinsky, Peng Wan, Richard Williams, Peng Yan, and Wancheng Zhang for their contributions, polishing efforts, and time invested in making this book a reality.