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      1. Data och IT
      2. Systemvetenskap och AI

      Big Data and Machine Learning in Quantitative Investment

      AvTony Guida

      Inbunden, Engelska, 2019

      Del i serien Wiley Finance

      611 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Fler format och utgåvor

      E-bok

      715 kr

      E-bok

      715 kr

      Beskrivning

      Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investmentBig 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 sophisticatedMachine 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.

      Produktinformation

      • Utgivningsdatum:2019-02-15
      • Mått:175 x 249 x 20 mm
      • Vikt:635 g
      • Format:Inbunden
      • Språk:Engelska
      • Serie:Wiley Finance
      • Antal sidor:304
      • Förlag:John Wiley & Sons Inc
      • ISBN:9781119522195

      Utforska kategorier

      • Systemvetenskap och AI inom Data och IT
      • Databaser inom Data och IT
      • Finansiering inom Ekonomi och Ledarskap

      Mer om författaren

      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.

      Innehållsförteckning

      • CHAPTER 1 Do Algorithms Dream About Artificial Alphas? 1By Michael KolloCHAPTER 2 Taming Big Data 13By Rado Lipuš and Daryl SmithCHAPTER 3 State of Machine Learning Applications in Investment Management 33By Ekaterina SirotyukCHAPTER 4 Implementing Alternative Data in an Investment Process 51By Vinesh JhaCHAPTER 5 Using Alternative and Big Data to Trade Macro Assets 75By Saeed Amen and Iain ClarkCHAPTER 6 Big Is Beautiful: How Email Receipt Data Can Help Predict Company Sales 95By Giuliano De Rossi, Jakub Kolodziej and Gurvinder BrarCHAPTER 7 Ensemble Learning Applied to Quant Equity: Gradient Boosting in a Multifactor Framework 129By Tony Guida and Guillaume CoqueretCHAPTER 8 A Social Media Analysis of Corporate Culture 149By Andy MonizCHAPTER 9 Machine Learning and Event Detection for Trading Energy Futures 169By Peter Hafez and Francesco LautiziCHAPTER 10 Natural Language Processing of Financial News 185By M. Berkan Sesen, Yazann Romahi and Victor LiCHAPTER 11 Support Vector Machine-Based Global Tactical Asset Allocation 211By Joel GugliettaCHAPTER 12 Reinforcement Learning in Finance 225By Gordon RitterCHAPTER 13 Deep Learning in Finance: Prediction of Stock Returns with Long Short-Term Memory Networks 251By Miquel N. Alonso, Gilberto Batres-Estrada and Aymeric MoulinBiography 279
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