Finding Alphas - A Quantitative Approach to Building Trading Strategies

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.

Sommario

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

Info autore

IGOR TULCHINSKY is the Founder, Chairman, and CEO of WorldQuant, a global quantitative asset management firm, based in Old Greenwich, Connecticut, that he established in 2007 following 12 years as a statistical arbitrage portfolio manager at Millennium Management. Before joining Millennium, Tulchinsky was a venture capitalist, scientist at AT&T Bell Laboratories, video game programmer, and author. He holds a master's degree in Computer Science from the University of Texas, Austin, completed in a then-record nine months, and an MBA in Finance and Entrepreneurship from the Wharton School at the University of Pennsylvania. A strong believer in education, Tulchinsky is the founder of WorldQuant University, which offers an entirely free online MSc degree in financial engineering and an applied data science module.

Riassunto

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.

Dettagli sul prodotto

• Autori: I Tulchinsky, Igor Tulchinsky
• Con la collaborazione di: Igo Tulchinsky (Editore), Igor Tulchinsky (Editore), Tulchinsky Igor (Editore)
• Editore: Wiley, John and Sons Ltd
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 31.08.2019
• EAN: 9781119571216
• ISBN: 978-1-119-57121-6
• Pagine: 320
• Serie: The Wiley Finance Series; The Wiley Finance Series
• Categorie: Scienze sociali, diritto, economia > Economia > Economia aziendale; Finanzwesen, Finance & Investments, Finanz- u. Anlagewesen, Spezialthemen Finanz- u. Anlagewesen, Finance & Investments Special Topics