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Finding Alphas: A Quantitative Approach to Building Trading Strategies



Finding Alphas seeks to teach you how to do one thing and do it well – design alphas. For financial engineers, quantitative researchers, investment analysts, and those aspiring to be quants, this is the guidebook for reliable, up-to-date coverage on the ins and outs of alpha design.

The collection of essays inside explores how to hone and retain a cutting-edge when trying to make sense of the ever-increasing amount of quantifiable changes happening during trading. From abstract theory to concrete technical methods, Finding Alphas illuminates basic techniques as well as unique approaches to alpha design, helping you to develop your own design style. A fascinating range of methods for uncovering the signals in data are explored. On your way to mastering alpha design, this robust training tool will equip you with:

  • The seven habits of highly-effective quants.
  • A full treatment of all the key technical aspects of alpha design.
  • The know-how to develop a disciplined process for alpha discovery and securities trading.
  • A web-based simulator, WebSim ®, for creating and fine-tuning successful alphas.

As the amount of data continues to grow in the financial industry, the advantage will go to the trader who can see the whole picture, who can combine millions and billions of subtle and illusive signals, and who has honed their skill set with the information provided by Finding Alphas.

IGOR TULCHINSKY is the Founder and CEO of WorldQuant, LLC, a private institutional investment management complex with offices worldwide. He is also Founder of the WorldQuant Foundation, which offers scholarships to outstanding students committed to pursuing higher education in the fields of science and quantitative studies. Based on the belief that education should be free for all, he has also founded WorldQuant University, which offers a tuition free open online master degree program in quantitative finance.

Preface xi

Acknowledgments xiii

About the WebSim? Website xv

Part I Introduction 1

1 Introduction to Alpha Design 3

By Igor Tulchinsky

2 Alpha Genesis Life-Cycle of a Quantitative

Model Financial Price Prediction 7

By Geoffrey Lauprete

3 Cutting Losses 13

By Igor Tulchinsky

Part II Design and Evaluation 19

4 Alpha Design 21

By Scott Bender/Yongfeng He

5 How to Develop an Alpha. I: Logic with an Example 27

By Pankaj Bakliwal

6 How to Develop an Alpha. II: A Case Study 31

By Hongzhi Chen

7 Fundamental Analysis 43

By Xinye Tang/Kailin Qi

8 Equity Price and Volume 49

By Cong Li

9 Turnover 51

By Pratik Patel

10 Backtest ? Signal or Overfitting 55

By Peng Yan

11 Alpha and Risk Factors 61

By Peng Wan

12 The Relationship between Alpha and Portfolio Risk 65

By Ionut Aron

13 Risk and Drawdowns 71

By Hammad Khan

14 Data and Alpha Design 79

By Weijia Li

15 Statistical Arbitrage, Overfitting, and Alpha Diversity 85

By Zhuangxi Fang

16 Techniques for Improving the Robustness of Alphas 89

By Michael Kozlov

17 Alphas from Automated Search 93

By Yu Huang

18 Algorithms and Special Techniques in Alpha Research 97

By Sunny Mahajan

Part III Extended Topics 101

19 Impact of News and Social Media on Stock Returns 103

By Wancheng Zhang

20 Stock Returns Information from the Stock Options Market 109

By Swastik Tiwari

21 Introduction to Momentum Alphas 117

By Zhiyu Ma

22 Financial Statement Analysis 119

By Paul A. Griffin

23 Institutional Research 101 127

By Benjamin Ee

24 Introduction to Futures Trading 145

By Rohit Agarwal

25 Alpha on Currency Forwards and Futures 151

By Richard Williams

Part IV New Horizon WebSim 155

26 Introduction to WebSim 157

By Jeffrey Scott

27 Alphas and WebSim Fundamentals 165

28 Understanding How WebSim Works 169

29 API Reference 179

30 Interpreting Results and Alpha Repository 187

31 Alpha Tutorials 199

32 FAQs 211

33 Suggested Reading 223

Part V - A Final Word 229

34 The Seven Habits of Highly Successful Quants 231

By Richard Hu

References 235

Index 245