The Journal of Financial Data Science: 2 (1)

Winter 2020; Volume 2,Issue 1

Managing Editor’s Letter

Open Access
Managing Editor’s Letter
Francesco A. Fabozzi

The Journal of Financial Data Science Winter 2020, 2 (1) 1-4; DOI: https://doi.org/10.3905/jfds.2020.2.1.001

Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies

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Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies
Derek Snow

The Journal of Financial Data Science Winter 2020, 2 (1) 10-23; DOI: https://doi.org/10.3905/jfds.2019.1.021

The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach

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The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach
Gueorgui Konstantinov and Mario Rusev

The Journal of Financial Data Science Winter 2020, 2 (1) 24-44; DOI: https://doi.org/10.3905/jfds.2019.1.017

Constructing Equity Portfolios from SEC 13F Data Using Feature Extraction and Machine Learning

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Constructing Equity Portfolios from SEC 13F Data Using Feature Extraction and Machine Learning
Alexander Fleiss, Han Cui, Sasha Stoikov and Daniel M. DiPietro

The Journal of Financial Data Science Winter 2020, 2 (1) 45-60; DOI: https://doi.org/10.3905/jfds.2019.1.022

Beyond the Black Box: An Intuitive Approach to Investment Prediction with Machine Learning

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Beyond the Black Box: An Intuitive Approach to Investment Prediction with Machine Learning
Yimou Li, David Turkington and Alireza Yazdani

The Journal of Financial Data Science Winter 2020, 2 (1) 61-75; DOI: https://doi.org/10.3905/jfds.2019.1.023

Mitigating Overfitting on Financial Datasets with Generative Adversarial Networks

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Mitigating Overfitting on Financial Datasets with Generative Adversarial Networks
Fernando De Meer Pardo and Rafael Cobo López

The Journal of Financial Data Science Winter 2020, 2 (1) 76-85; DOI: https://doi.org/10.3905/jfds.2019.1.019

Crowdsourced Investment Research Through Tournaments

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Crowdsourced Investment Research Through Tournaments
Marcos López de Prado and Frank J. Fabozzi

The Journal of Financial Data Science Winter 2020, 2 (1) 86-93; DOI: https://doi.org/10.3905/jfds.2019.1.016

Deep Learning Classifier with Piecewise Linear Activation Function: An Empirical Evaluation with Intraday Financial Data

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Deep Learning Classifier with Piecewise Linear Activation Function: An Empirical Evaluation with Intraday Financial Data
Soham Banerjee and Diganta Mukherjee

The Journal of Financial Data Science Winter 2020, 2 (1) 94-115; DOI: https://doi.org/10.3905/jfds.2019.1.018

Teaching Machines to Understand Chinese Investment Slang

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Teaching Machines to Understand Chinese Investment Slang
Mike Chen, Jaime Lee and George Mussalli

The Journal of Financial Data Science Winter 2020, 2 (1) 116-125; DOI: https://doi.org/10.3905/jfds.2019.1.020

Pairs Trading Strategy with Geolocation Data—The Battle between Under Armour and Nike

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Pairs Trading Strategy with Geolocation Data—The Battle between Under Armour and Nike
Jim Kyung-Soo Liew, Tamas Budavari, Zixiao Kang, Fengxu Li, Xuzhi Wang, Shihao Ma and Brandon Fremin

The Journal of Financial Data Science Winter 2020, 2 (1) 126-143; DOI: https://doi.org/10.3905/jfds.2019.1.024

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The Journal of Financial Data Science

Table of Contents

Managing Editor’s Letter

Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies

The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach

Constructing Equity Portfolios from SEC 13F Data Using Feature Extraction and Machine Learning

Beyond the Black Box: An Intuitive Approach to Investment Prediction with Machine Learning

Mitigating Overfitting on Financial Datasets with Generative Adversarial Networks

Crowdsourced Investment Research Through Tournaments

Deep Learning Classifier with Piecewise Linear Activation Function: An Empirical Evaluation with Intraday Financial Data

Teaching Machines to Understand Chinese Investment Slang

Pairs Trading Strategy with Geolocation Data—The Battle between Under Armour and Nike

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Table of Contents

Managing Editor’s Letter

Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies

The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach

Constructing Equity Portfolios from SEC 13F Data Using Feature Extraction and Machine Learning

Beyond the Black Box: An Intuitive Approach to Investment Prediction with Machine Learning

Mitigating Overfitting on Financial Datasets with Generative Adversarial Networks

Crowdsourced Investment Research Through Tournaments

Deep Learning Classifier with Piecewise Linear Activation Function: An Empirical Evaluation with Intraday Financial Data

Teaching Machines to Understand Chinese Investment Slang

Pairs Trading Strategy with Geolocation Data—The Battle between Under Armour and Nike

Explore our content to discover more relevant research

In this issue

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