Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment
Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance.
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.
• Gain a solid reason to use machine learning
• Frame your question using financial markets laws
• Know your data
• Understand how machine learning is becoming ever more sophisticated
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.
By:
Tony Guida
Imprint: John Wiley & Sons Inc
Country of Publication: United States
Dimensions:
Height: 249mm,
Width: 175mm,
Spine: 20mm
Weight: 635g
ISBN: 9781119522195
ISBN 10: 1119522196
Series: Wiley Finance
Pages: 304
Publication Date: 15 February 2019
Audience:
Professional and scholarly
,
Undergraduate
Format: Hardback
Publisher's Status: Active
CHAPTER 1 Do Algorithms Dream About Artificial Alphas? 1 By Michael Kollo CHAPTER 2 Taming Big Data 13 By Rado Lipuš and Daryl Smith CHAPTER 3 State of Machine Learning Applications in Investment Management 33 By Ekaterina Sirotyuk CHAPTER 4 Implementing Alternative Data in an Investment Process 51 By Vinesh Jha CHAPTER 5 Using Alternative and Big Data to Trade Macro Assets 75 By Saeed Amen and Iain Clark CHAPTER 6 Big Is Beautiful: How Email Receipt Data Can Help Predict Company Sales 95 By Giuliano De Rossi, Jakub Kolodziej and Gurvinder Brar CHAPTER 7 Ensemble Learning Applied to Quant Equity: Gradient Boosting in a Multifactor Framework 129 By Tony Guida and Guillaume Coqueret CHAPTER 8 A Social Media Analysis of Corporate Culture 149 By Andy Moniz CHAPTER 9 Machine Learning and Event Detection for Trading Energy Futures 169 By Peter Hafez and Francesco Lautizi CHAPTER 10 Natural Language Processing of Financial News 185 By M. Berkan Sesen, Yazann Romahi and Victor Li CHAPTER 11 Support Vector Machine-Based Global Tactical Asset Allocation 211 By Joel Guglietta CHAPTER 12 Reinforcement Learning in Finance 225 By Gordon Ritter CHAPTER 13 Deep Learning in Finance: Prediction of Stock Returns with Long Short-Term Memory Networks 251 By Miquel N. Alonso, Gilberto Batres-Estrada and Aymeric Moulin Biography 279
TONY GUIDA 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.
