Machine Learning for Stock Selection-Reference-Cited by-同舟云学术

Machine Learning for Stock Selection

Published:2019-05-13 Issue:3 Volume:75 Page:70-88
ISSN:0015-198X
Container-title:Financial Analysts Journal
language:en
Short-container-title:Financial Analysts Journal

Author:

Rasekhschaffe Keywan Christian¹^ORCID,Jones Robert C.²

Affiliation:

1. Keywan Christian Rasekhschaffe is a senior quantitative strategist at Gresham Investment Management, LLC, in New York City.

2. Robert C. Jones, CFA, is chair and chief investment officer of System Two Advisors, LP, in Summit, New Jersey.

Publisher

Informa UK Limited

Subject

Economics and Econometrics,Finance,Accounting

Link

https://www.tandfonline.com/doi/pdf/10.1080/0015198X.2019.1596678

Reference24 articles.

1. Alberg, John, and Zachary Lipton. 2017. “Improving Factor-Based Quantitative Investing by Forecasting Company Fundamentals.” Working paperCornell University https://arxiv.org/abs/1711.04837v2 .

2. INVITED EDITORIAL COMMENT

3. Asness, Clifford S., R. Burt Porter, and Ross L. Stevens. 2000. “Predicting Stock Returns Using Industry-Relative Firm Characteristics.” Working paper AQR Capital Management.

4. Batres-Estrada, Gilberto. 2015. “Deep Learning for Multivariate Financial Time Series.” Master’s thesis, KTH Royal Institute of Technology https://www.math.kth.se/matstat/seminarier/ reports/M-exjobb15/150612a.pdf.

5. On Persistence in Mutual Fund Performance

Cited by 112 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Explainable deep learning model for stock price forecasting using textual analysis;Expert Systems with Applications;2024-09

2. “Darling, time horizon matters”: applying the CNN-LSTM method for predicting US equity ETFs;Applied Economics Letters;2024-08-30

3. Choices Matter When Training Machine Learning Models for Return Prediction;Financial Analysts Journal;2024-08-29

4. Predicting Corporate Bond Illiquidity via Machine Learning;Financial Analysts Journal;2024-06-24

5. State-of-the-Art;Synthesis Lectures on Technology Management & Entrepreneurship;2024-06-19