Deep Learning and the Cross-Section of Stock Returns: Neural Networks Combining Price and Fundamental Information

By Bo Zhou. 2019

10 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Economics & Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Omer Berat Sezer
2. A. Ozbayoglu
3. M. Ugur Gudelek

In Management Science and Operations Research

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. A. Ozbayoglu
4. Weiwei Jiang
5. Longbing Cao

In Economics & Operations Research

1. A. Ozbayoglu
2. M. Ugur Gudelek
3. Omer Berat Sezer

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “In [109], next month’s return was predicted and top to be performed portfolios were constructed.”
• Deep Learning for Financial Applications : A Survey (2020, methodology): “[134] Stocks in NYSE, AMEX, NASDAQ, TAQ intraday trade 1993-2017 Price, 15 firm characteristics LSTM+MLP Monthly return, SR Python,Keras, Tensorflow in AWS”