Deep Investment in Financial Markets using Deep Learning Models

By Saurabh Aggarwal, Somya Aggarwal. 2017

45 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Electrical and Electronic Engineering, Management Science and 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
4. Tadaaki Hosaka
5. Sang Il Lee
6. Seong Joon Yoo

In Electrical and Electronic Engineering

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

In Management Science and Operations Research

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. A. Ozbayoglu
4. Tadaaki Hosaka
5. Sang Il Lee
6. Seong Joon Yoo
7. Weiwei Jiang
8. Longbing Cao

Citations in the corpus

• Deep Learning for Financial Applications : A Survey (2020, methodology): “Portfolio selection and smart indexing were the main focuses of [130] and [131] using AE and LSTM networks.”
• Threshold-based portfolio: the role of the threshold and its applications (2017, background): “Researchers have successfully modeled financial time series by focusing primarily on prediction accuracy or automatic trading rules [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16].”
• Bankruptcy prediction using imaged financial ratios and convolutional neural networks (2019, background): “ber of applications of deep learning to financial analysis is extremely limited except for several reports on the prediction of stock price fluctuations (Yoshihara, Fujikawa, Seki, and Uehara, 2014; Aggarwal and Aggarwal, 2016; Persio and Honchar, 2017; Chong, Han, and Park, 2017; Bao, Yue, and Rao,”