Details

Big Data and Machine Learning in Quantitative Investment


Big Data and Machine Learning in Quantitative Investment


Wiley Finance 1. Aufl.

von: Tony Guida

42,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 12.12.2018
ISBN/EAN: 9781119522218
Sprache: englisch
Anzahl Seiten: 304

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

<p><b>Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment</b></p> <p><i>Big Data and Machine Learning in Quantitative Investment </i>is not just about demonstrating the maths or the coding. Instead, it’s a book <i>by</i> practitioners <i>for</i> practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance.</p> <p>The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning.</p> <p>•    Gain a solid reason to use machine learning</p> <p>•    Frame your question using financial markets laws</p> <p>•    Know your data<br /><br />•    Understand how machine learning is becoming ever more sophisticated</p> <p>Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment — and this book shows you how.</p>
<p>CHAPTER 1 Do Algorithms Dream About Artificial Alphas? 1<br /><i>By Michael Kollo</i></p> <p>CHAPTER 2 Taming Big Data 13<br /><i>By Rado Lipuš and Daryl Smith</i></p> <p>CHAPTER 3 State of Machine Learning Applications in Investment Management 33<br /><i>By Ekaterina Sirotyuk</i></p> <p>CHAPTER 4 Implementing Alternative Data in an Investment Process 51<br /><i>By Vinesh Jha</i></p> <p>CHAPTER 5 Using Alternative and Big Data to Trade Macro Assets 75<br /><i>By Saeed Amen and Iain Clark</i></p> <p>CHAPTER 6 Big Is Beautiful: How Email Receipt Data Can Help Predict Company Sales 95<br /><i>By Giuliano De Rossi, Jakub Kolodziej and Gurvinder Brar</i></p> <p>CHAPTER 7 Ensemble Learning Applied to Quant Equity: Gradient Boosting in a Multifactor Framework 129<br /><i>By Tony Guida and Guillaume Coqueret</i></p> <p>CHAPTER 8 A Social Media Analysis of Corporate Culture 149<br /><i>By Andy Moniz</i></p> <p>CHAPTER 9 Machine Learning and Event Detection for Trading Energy Futures 169<br /><i>By Peter Hafez and Francesco Lautizi</i></p> <p>CHAPTER 10 Natural Language Processing of Financial News 185<br /><i>By M. Berkan Sesen, Yazann Romahi and Victor Li</i></p> <p>CHAPTER 11 Support Vector Machine-Based Global Tactical Asset Allocation 211<br /><i>By Joel Guglietta</i></p> <p>CHAPTER 12 Reinforcement Learning in Finance 225<br /><i>By Gordon Ritter</i></p> <p>CHAPTER 13 Deep Learning in Finance: Prediction of Stock Returns with Long Short-Term Memory Networks 251<br /><i>By Miquel N. Alonso, Gilberto Batres-Estrada and Aymeric Moulin</i></p> <p>Biography 279</p>
<p><b>TONY GUIDA</b> is a senior investment manager in quantitative equity at the investment manager of a major UK pension fund in London, where he manages multifactor systematic equity portfolios. During his career, he held such positions as senior consultant for smart beta and risk allocation at EDHEC RISK Scientific Beta and senior research analyst at UNIGESTION. He is a former member of the research and investment committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients, and a regular speaker at quant conferences. Tony is chair of machineByte ThinkTank EMEA.
<p>Praise for <b>Big Data and Machine Learning in Quantitative Investment</b> <p>"Alternative data and machine learning are about to become essential components of the modern investment process. This excellent book offers practitioners a rich collection of case studies written by some of the most capable quants in the world today. It will be on our shelves here at Quandl for sure."</br> <b>—Tammer Kamel,</b> CEO and founder, Quandl, Toronto <p>"Tony Guida has managed to cover an impressive list of recent topics in Financial Machine Learning and Big Data, such as deep learning, reinforcement learning or natural language processing, in this book. It is accessible and rich with real-world applications, written in readable style. It will appeal to quants, students and regulators at all levels, and will undoubtedly become a reference textbook, one of the few not to be missed by anybody interested in Machine Learning and Big Data applications."</br> <b>—Ahcene Gareche,</b> Head of Quantitative Strategies, AXA IM Chorus, Hong Kong <p>"Artificial intelligence and machine learning, big and alternative data, are unequivocally buzz words of our times and quantitative finance is not exempt from that. However, not all datasets are necessarily useful for financial applications and not all ML techniques can be applied on a "plug-and-play" basis. Importantly, the industry needs specialised guidance on how different datasets and ML techniques should be used for quantitative investments. The new book, edited by Tony Guida, is here to address this need by providing a diverse collection of 13 self-contained chapters written by practitioners who offer different perspectives and use cases of big data and ML techniques in finance and investments. Some chapters are more philosophical, providing guidance and perspective. Others are more practical focusing either on the manipulation of big data or on the specifics of particular ML approaches when employed for financial applications. All in all, for the investment professional who is either experienced or new entrant in the ML/big data in quantitative investing space, Tony Guida has made a remarkable attempt to provide a holistic view of the landscape. It is worth a read."</br> <b>—Nick Baltas,</b> Head of R&D - Systematic Trading Strategies, Goldman Sachs, London

Diese Produkte könnten Sie auch interessieren:

Make Change Work
Make Change Work
von: Randy Pennington
PDF ebook
14,99 €
Nonprofit Law Made Easy
Nonprofit Law Made Easy
von: Bruce R. Hopkins
EPUB ebook
53,99 €
Trading Psychology 2.0
Trading Psychology 2.0
von: Brett N. Steenbarger
PDF ebook
42,99 €