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- Wiley
More About This Title Finding Alphas - A Quantitative Approach toBuilding Trading Strategies
English
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. You’ll also find details of how to use WebSim, WorldQuant’s web-based simulation platform, to test your 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.
English
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.
English
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
