Details

Finding Alphas


Finding Alphas

A Quantitative Approach to Building Trading Strategies
2. Aufl.

von: Igor Tulchinsky

37,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 01.10.2019
ISBN/EAN: 9781119571254
Sprache: englisch
Anzahl Seiten: 320

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Beschreibungen

<p><b>Discover the ins and outs of designing predictive trading models</b></p> <p>Drawing on the expertise of WorldQuant’s global network, this new edition of <i>Finding Alphas: A Quantitative Approach to Building Trading Strategies</i> contains significant changes and updates to the original material, with new and updated data and examples.</p> <p>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.</p> <p>•    Provides more references to the academic literature</p> <p>•    Includes new, high-quality material</p> <p>•    Organizes content in a practical and easy-to-follow manner</p> <p>•    Adds new alpha examples with formulas and explanations</p> <p>If you’re looking for the latest information on building trading strategies from a quantitative approach, this book has you covered. </p>
<p>Preface xi</p> <p>Preface (to the Original Edition) xiii</p> <p>Acknowledgments xv</p> <p>About the WebSim Website xvii</p> <p><b>Part I Introduction 1</b></p> <p>1 Introduction to Alpha Design 3<br /><i>By Igor Tulchinsky</i></p> <p>2 Perspectives on Alpha Research 7<br /><i>By Geoffrey Lauprete</i></p> <p>3 Cutting Losses 17<br /><i>By Igor Tulchinsky</i></p> <p><b>Part II Design and Evaluation 23</b></p> <p>4 Alpha Design 25<br /><i>By Scott Bender and Yongfeng He</i></p> <p>5 How to Develop an Alpha: A Case Study 31<br /><i>By Pankaj Bakliwal and Hongzhi Chen</i></p> <p>6 Data and Alpha Design 43<br /><i>By Weijia Li</i></p> <p>7 Turnover 49<br /><i>By Pratik Patel</i></p> <p>8 Alpha Correlation 61<br /><i>By Chinh Dang and Crispin Bui</i></p> <p>9 Backtest – Signal or Overfitting? 69<br /><i>By Zhuangxi Fang and Peng Yan</i></p> <p>10 Controlling Biases 77<br /><i>By Anand Iyer and Aditya Prakash</i></p> <p>11 The Triple-Axis Plan 83<br /><i>By Nitish Maini</i></p> <p>12 Techniques for Improving the Robustness of Alphas 89<br /><i>By Michael Kozlov</i></p> <p>13 Alpha and Risk Factors 95<br /><i>By Peng Wan</i></p> <p>14 Risk and Drawdowns 101<br /><i>By Hammad Khan and Rebecca Lehman</i></p> <p>15 Alphas from Automated Search 111<br /><i>By Yu Huang and Varat Intaraprasonk</i></p> <p>16 Machine Learning in Alpha Research 121<br /><i>By Michael Kozlov</i></p> <p>17 Thinking in Algorithms 127<br /><i>By Sunny Mahajan</i></p> <p><b>Part III Extended Topics 133</b></p> <p>18 Equity Price and Volume 135<br /><i>By Cong Li and Huaiyu Zhou</i></p> <p>19 Financial Statement Analysis 141<br /><i>By Paul A. Griffin and Sunny Mahajan</i></p> <p>20 Fundamental Analysis and Alpha Research 149<br /><i>By Xinye Tang and Kailin Qi</i></p> <p>21 Introduction to Momentum Alphas 155<br /><i>By Zhiyu Ma, Arpit Agarwal, and Laszlo Borda</i></p> <p>22 The Impact of News and Social Media on Stock Returns 159<br /><i>By Wancheng Zhang</i></p> <p>23 Stock Returns Information from the Stock Options Market 169<br /><i>By Swastik Tiwari and Hardik Agarwal</i></p> <p>24 Institutional Research 101: Analyst Reports 179<br /><i>By Benjamin Ee, Hardik Agarwal, Shubham Goyal, Abhishek Panigrahy, and Anant Pushkar</i></p> <p>25 Event-Driven Investing 195<br /><i>By Prateek Srivastava</i></p> <p>26 Intraday Data in Alpha Research 207<br /><i>By Dusan Timotity</i></p> <p>27 Intraday Trading 217<br /><i>By Rohit Kumar Jha</i></p> <p>28 Finding an Index Alpha 223<br /><i>By Glenn DeSouza</i></p> <p>29 ETFs and Alpha Research 231<br /><i>By Mark YikChun Chan</i></p> <p>30 Finding Alphas on Futures and Forwards 241<br /><i>By Rohit Agarwal, Rebecca Lehman, and Richard Williams</i></p> <p><b>Part IV New Horizon – Websim 251</b></p> <p>31 Introduction to WebSim 253<br /><i>By Jeffrey Scott</i></p> <p><b>Part V A Final Word 263</b></p> <p>32 The Seven Habits of Highly Successful Quants 265<br /><i>By Richard Hu and Chalee Asavathiratham</i></p> <p>References 273</p> <p>Index 291</p>
<p><b>IGOR TULCHINSKY</b> 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.
<p>For even the most experienced traders, designing the predictive mathematical models (alphas) at the core of quantitative trading is a complex, labor-intensive process that requires significant research and testing. Based on ever-changing data, quantitative strategies may have limited life spans; new models must be generated on a constant basis. Igor Tulchinsky, Founder, Chairman, and CEO of WorldQuant, and the team of researchers, portfolio managers, and technologists he has assembled at his global quantitative asset management firm have significant firsthand experience in this area.<i> Finding Alphas: A Quantitative Approach to Building Trading Strategies </i>draws on WorldQuant’s expertise in developing quantitative mathematical models to help you identify potentially profitable opportunities and build your own quantitative trading strategies. Covering everything from basic theory to advanced design and analysis techniques, this one-stop resource: <ul><li>Describes how to design, evaluate, and deploy quantitative trading strategies. </li> <li>Covers the development and backtesting of alphas, momentum alphas, the use of futures and forwards, institutional research in alpha development, and more.</li> <li>Explains how to use WebSim, WorldQuant’s proprietary, internet-enabled simulation platform.</li></ul>

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