Investment Performance of Machine Learning: Analysis of S&P 500 Index
This study aims to explore the prediction of S&P 500 stock price movement and conduct an analysis of its investment performance. Based on the S&P 500 index, the study compares three machine learning models: ANN, SVM, and Random Forest. With a performance evaluation of S&P 500 index hist...
Main Authors: | Chia-Cheng Chen, Chun-Hung Chen, Ting-Yin Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
EconJournals
2019-12-01
|
Series: | International Journal of Economics and Financial Issues |
Online Access: | https://www.econjournals.com/index.php/ijefi/article/view/8925 |
Similar Items
-
Investment Performance of Machine Learning: Analysis of S&P 500 Index
by: Chia-Cheng Chen, et al.
Published: (2019-12-01) -
Investment Performance of Machine Learning: Analysis of S&P 500 Index
by: Chia-Cheng Chen, et al.
Published: (2019-12-01) -
LSTM in Algorithmic Investment Strategies on BTC and S&P500 Index
by: Jakub Michańków, et al.
Published: (2022-01-01) -
An Analysis on Investment Performance of Machine Learning: An Empirical Examination on Taiwan Stock Market
by: Chia-Cheng Chen, et al.
Published: (2019-07-01) -
Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index
by: Nguyen Vo, et al.
Published: (2022-01-01)