Table of Contents

Fall 2019; Volume 1,Issue 4

A

  1. Aldridge, Irene

    1. Neural Networks in Finance: Design and Performance
      Irene Aldridge and Marco Avellaneda
      The Journal of Financial Data Science Fall 2019, 1 (4) 39-62; DOI: https://doi.org/10.3905/jfds.2019.1.4.039

  2. Avellaneda, Marco

    1. Neural Networks in Finance: Design and Performance
      Irene Aldridge and Marco Avellaneda
      The Journal of Financial Data Science Fall 2019, 1 (4) 39-62; DOI: https://doi.org/10.3905/jfds.2019.1.4.039

C

  1. Cheng, Enoch

    1. Time-Series Momentum: A Monte Carlo Approach
      Clemens Struck and Enoch Cheng
      The Journal of Financial Data Science Fall 2019, 1 (4) 103-123; DOI: https://doi.org/10.3905/jfds.2019.1.012

  2. Chuanjie, Fu

    1. Automated Theme Search in ICO Whitepapers
      Fu Chuanjie, Andrew Koh and Paul Griffin
      The Journal of Financial Data Science Fall 2019, 1 (4) 140-158; DOI: https://doi.org/10.3905/jfds.2019.1.011

D

  1. DiPietro, Daniel M.

    1. Alpha Cloning: Using Quantitative Techniques and SEC 13f Data for Equity Portfolio Optimization and Generation
      Daniel M. DiPietro
      The Journal of Financial Data Science Fall 2019, 1 (4) 159-171; DOI: https://doi.org/10.3905/jfds.2019.1.008

F

  1. Fabozzi, Francesco A.

    1. Open Access
      Managing Editor’s Letter
      Francesco A. Fabozzi
      The Journal of Financial Data Science Fall 2019, 1 (4) 1-4; DOI: https://doi.org/10.3905/jfds.2019.1.4.001

  2. Firoozye, Nick

    1. Avoiding Backtesting Overfitting by Covariance-Penalties: An Empirical Investigation of the Ordinary and Total Least Squares Cases
      Adriano Koshiyama and Nick Firoozye
      The Journal of Financial Data Science Fall 2019, 1 (4) 63-83; DOI: https://doi.org/10.3905/jfds.2019.1.013

G

  1. Garvey, Gerald

    1. Reconstructing Emerging and Developed Markets Using Hierarchical Clustering
      Gerald Garvey and Ananth Madhavan
      The Journal of Financial Data Science Fall 2019, 1 (4) 84-102; DOI: https://doi.org/10.3905/jfds.2019.1.014

  2. Griffin, Paul

    1. Automated Theme Search in ICO Whitepapers
      Fu Chuanjie, Andrew Koh and Paul Griffin
      The Journal of Financial Data Science Fall 2019, 1 (4) 140-158; DOI: https://doi.org/10.3905/jfds.2019.1.011

K

  1. Koh, Andrew

    1. Automated Theme Search in ICO Whitepapers
      Fu Chuanjie, Andrew Koh and Paul Griffin
      The Journal of Financial Data Science Fall 2019, 1 (4) 140-158; DOI: https://doi.org/10.3905/jfds.2019.1.011

  2. Koshiyama, Adriano

    1. Avoiding Backtesting Overfitting by Covariance-Penalties: An Empirical Investigation of the Ordinary and Total Least Squares Cases
      Adriano Koshiyama and Nick Firoozye
      The Journal of Financial Data Science Fall 2019, 1 (4) 63-83; DOI: https://doi.org/10.3905/jfds.2019.1.013

L

  1. Lim, Bryan

    1. Enhancing Time-Series Momentum Strategies Using Deep Neural Networks
      Bryan Lim, Stefan Zohren and Stephen Roberts
      The Journal of Financial Data Science Fall 2019, 1 (4) 19-38; DOI: https://doi.org/10.3905/jfds.2019.1.015

M

  1. Madhavan, Ananth

    1. Reconstructing Emerging and Developed Markets Using Hierarchical Clustering
      Gerald Garvey and Ananth Madhavan
      The Journal of Financial Data Science Fall 2019, 1 (4) 84-102; DOI: https://doi.org/10.3905/jfds.2019.1.014

P

  1. Prado, Marcos López de

    1. Extracting Signals from High-Frequency Trading with Digital Signal Processing Tools
      Jung Heon Song, Marcos López de Prado, Horst D. Simon and Kesheng Wu
      The Journal of Financial Data Science Fall 2019, 1 (4) 124-138; DOI: https://doi.org/10.3905/jfds.2019.1.4.124

R

  1. Roberts, Stephen

    1. Enhancing Time-Series Momentum Strategies Using Deep Neural Networks
      Bryan Lim, Stefan Zohren and Stephen Roberts
      The Journal of Financial Data Science Fall 2019, 1 (4) 19-38; DOI: https://doi.org/10.3905/jfds.2019.1.015

S

  1. Simon, Horst D.

    1. Extracting Signals from High-Frequency Trading with Digital Signal Processing Tools
      Jung Heon Song, Marcos López de Prado, Horst D. Simon and Kesheng Wu
      The Journal of Financial Data Science Fall 2019, 1 (4) 124-138; DOI: https://doi.org/10.3905/jfds.2019.1.4.124

  2. Simonian, Joseph

    1. Proofs and Cross-Validations: Three Lessons for Financial Data Science
      Joseph Simonian
      The Journal of Financial Data Science Fall 2019, 1 (4) 12-18; DOI: https://doi.org/10.3905/jfds.2019.1.009

  3. Song, Jung Heon

    1. Extracting Signals from High-Frequency Trading with Digital Signal Processing Tools
      Jung Heon Song, Marcos López de Prado, Horst D. Simon and Kesheng Wu
      The Journal of Financial Data Science Fall 2019, 1 (4) 124-138; DOI: https://doi.org/10.3905/jfds.2019.1.4.124

  4. Struck, Clemens

    1. Time-Series Momentum: A Monte Carlo Approach
      Clemens Struck and Enoch Cheng
      The Journal of Financial Data Science Fall 2019, 1 (4) 103-123; DOI: https://doi.org/10.3905/jfds.2019.1.012

W

  1. Wu, Kesheng

    1. Extracting Signals from High-Frequency Trading with Digital Signal Processing Tools
      Jung Heon Song, Marcos López de Prado, Horst D. Simon and Kesheng Wu
      The Journal of Financial Data Science Fall 2019, 1 (4) 124-138; DOI: https://doi.org/10.3905/jfds.2019.1.4.124

Z

  1. Zohren, Stefan

    1. Enhancing Time-Series Momentum Strategies Using Deep Neural Networks
      Bryan Lim, Stefan Zohren and Stephen Roberts
      The Journal of Financial Data Science Fall 2019, 1 (4) 19-38; DOI: https://doi.org/10.3905/jfds.2019.1.015
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