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Finding Alphas: A Quantitative Approach to Building Trading Strategies, 2nd Edition

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Finding Alphas: A Quantitative Approach to Building Trading Strategies, 2nd Edition

Igor Tulchinsky (Editor)

ISBN: 978-1-119-57125-4 October 2019 320 Pages

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Description

Discover the ins and outs of designing predictive trading models

Drawing on the expertise of WorldQuant’s global network, this new edition of Finding Alphas: A Quantitative Approach to Building Trading Strategies contains significant changes and updates to the original material, with new and updated data and examples.

Nine chapters have been added about alphas – models used to make predictions regarding the prices of financial instruments. The new chapters cover topics including alpha correlation, controlling biases, exchange-traded funds, event-driven investing, index alphas, intraday data in alpha research, intraday trading, machine learning, and the triple axis plan for identifying alphas.

•    Provides more references to the academic literature

•    Includes new, high-quality material

•    Organizes content in a practical and easy-to-follow manner

•    Adds new alpha examples with formulas and explanations

If you’re looking for the latest information on building trading strategies from a quantitative approach, this book has you covered. 

Preface xi

Preface (to the Original Edition) xiii

Acknowledgments xv

About the WebSim Website xvii

Part I Introduction 1

1 Introduction to Alpha Design 3
By Igor Tulchinsky

2 Perspectives on Alpha Research 7
By Geoffrey Lauprete

3 Cutting Losses 17
By Igor Tulchinsky

Part II Design and Evaluation 23

4 Alpha Design 25
By Scott Bender and Yongfeng He

5 How to Develop an Alpha: A Case Study 31
By Pankaj Bakliwal and Hongzhi Chen

6 Data and Alpha Design 43
By Weijia Li

7 Turnover 49
By Pratik Patel

8 Alpha Correlation 61
By Chinh Dang and Crispin Bui

9 Backtest – Signal or Overfitting? 69
By Zhuangxi Fang and Peng Yan

10 Controlling Biases 77
By Anand Iyer and Aditya Prakash

11 The Triple-Axis Plan 83
By Nitish Maini

12 Techniques for Improving the Robustness of Alphas 89
By Michael Kozlov

13 Alpha and Risk Factors 95
By Peng Wan

14 Risk and Drawdowns 101
By Hammad Khan and Rebecca Lehman

15 Alphas from Automated Search 111
By Yu Huang and Varat Intaraprasonk

16 Machine Learning in Alpha Research 121
By Michael Kozlov

17 Thinking in Algorithms 127
By Sunny Mahajan

Part III Extended Topics 133

18 Equity Price and Volume 135
By Cong Li and Huaiyu Zhou

19 Financial Statement Analysis 141
By Paul A. Griffin and Sunny Mahajan

20 Fundamental Analysis and Alpha Research 149
By Xinye Tang and Kailin Qi

21 Introduction to Momentum Alphas 155
By Zhiyu Ma, Arpit Agarwal, and Laszlo Borda

22 The Impact of News and Social Media on Stock Returns 159
By Wancheng Zhang

23 Stock Returns Information from the Stock Options Market 169
By Swastik Tiwari and Hardik Agarwal

24 Institutional Research 101: Analyst Reports 179
By Benjamin Ee, Hardik Agarwal, Shubham Goyal, Abhishek Panigrahy, and Anant Pushkar

25 Event-Driven Investing 195
By Prateek Srivastava

26 Intraday Data in Alpha Research 207
By Dusan Timotity

27 Intraday Trading 217
By Rohit Kumar Jha

28 Finding an Index Alpha 223
By Glenn DeSouza

29 ETFs and Alpha Research 231
By Mark YikChun Chan

30 Finding Alphas on Futures and Forwards 241
By Rohit Agarwal, Rebecca Lehman, and Richard Williams

Part IV New Horizon – Websim 251

31 Introduction to WebSim 253
By Jeffrey Scott

Part V A Final Word 263

32 The Seven Habits of Highly Successful Quants 265
By Richard Hu and Chalee Asavathiratham

References 273

Index 291