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Finding Alphas - A ­Quantitative Approach to ­Building Trading Strategies,­ Second Edition
By Igor Tulchinsky (Edited by)

Rating
Format
Hardback, 320 pages
Published
United States, 27 September 2019

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

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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

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Product Details
EAN
9781119571216
ISBN
1119571219
Dimensions
23.4 x 15.8 x 2.3 centimeters (0.67 kg)

Table of Contents

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

About the Author

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.

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