An effective deep learning model with reduced error rate for accurate forecast of stock market direction
Prediction using ML models is not well adapted in many portions of business decision-
making due to a lack of clarity and flexibility. In order to provide a positive risk-adjusted price …
making due to a lack of clarity and flexibility. In order to provide a positive risk-adjusted price …
Enhancing efficiency in recurrent reinforcement learning for automated data-driven investment
T Witkowski - Procedia Computer Science, 2024 - Elsevier
In this study, we introduce a novel approach for training Recurrent Reinforcement Learning
(RRL) agents for automated, data-driven investment tasks. The primary goal of this paper is …
(RRL) agents for automated, data-driven investment tasks. The primary goal of this paper is …
Machine Learning Approaches for Enhanced Portfolio Optimization: A Comparative Study of Regularization and Cross-Validation Techniques
One of the ways to optimize an investment portfolio is by way of diversification across
multiple asset classes including stocks, bonds, mutual funds, etc. Machine Learning is …
multiple asset classes including stocks, bonds, mutual funds, etc. Machine Learning is …
Stock Trend Prediction Using Candlestick Pattern
D Bathla, A Garg, Sarika - … on Cybersecurity in Emerging Digital Era, 2022 - Springer
The stock market is the place where buyers and sellers come to buy and sell their stocks to
get maximum ROI. Stocks go up and down because of the law of supply and demand. The …
get maximum ROI. Stocks go up and down because of the law of supply and demand. The …