The Journal of Financial Data Science

Deep Learning for Portfolio Optimization
Zihao Zhang, Stefan Zohren and Stephen Roberts
Machine Trading: Theory, Advances, and Applications
Dilip B. Madan and Yazid M. Sharaiha
It’s All About Data: How to Make Good Decisions in a World Awash with Information
Mehrzad Mahdavi and Hossein Kazemi
Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies
Derek Snow
Proofs and Cross-Validations: Three Lessons for Financial Data Science
Joseph Simonian
Industry Return Predictability: A Machine Learning Approach
David E. Rapach, Jack K. Strauss, Jun Tu and Guofu Zhou

Latest Articles

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Portfolio Construction Using First Principles Preference Theory and Machine Learning
Zava Aydemir

The Journal of Financial Data Science Fall 2020, 2 (4) 105-123; DOI: https://doi.org/10.3905/jfds.2020.2.4.105
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Forecast Optimization via Parameter Tuning: Performance Gain and Overfit
Ilya Soloveychik

The Journal of Financial Data Science Fall 2020, 2 (4) 71-84; DOI: https://doi.org/10.3905/jfds.2020.1.044
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Volatility Prediction and Risk Management: An SVR-GARCH Approach
Abdullah Karasan and Esma Gaygisiz

The Journal of Financial Data Science Fall 2020, 2 (4) 85-104; DOI: https://doi.org/10.3905/jfds.2020.1.046
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Neural Embeddings of Financial Time-Series Data
Alik Sokolov, Jonathan Mostovoy, Brydon Parker and Luis Seco

The Journal of Financial Data Science Fall 2020, 2 (4) 33-43; DOI: https://doi.org/10.3905/jfds.2020.1.041
Open Access
Managing Editor’s Letter
Francesco A. Fabozzi

The Journal of Financial Data Science Fall 2020, 2 (4) 1-3; DOI: https://doi.org/10.3905/jfds.2020.2.4.001
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European Floating Strike Lookback Options: Alpha Prediction and Generation Using Unsupervised Learning
Tristan Lim, Chin Sin Ong and Aldy Gunawan

The Journal of Financial Data Science Fall 2020, 2 (4) 59-70; DOI: https://doi.org/10.3905/jfds.2020.1.043

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In our series of videos, the authors of research published in The Journal of Financial Data Science, discuss the findings of their article, offering more in-depth analysis around it and explain how the conclusions can be implemented in practice.