Neural networks have been touted as all-powerful tools in stock-market prediction. Companies such as MJ Futures claim amazing 199.2% returns over a 2-year ...

Stock price forecasting models based on neural networks in the form of unsupervised algorithms not only save investors time in the decision-making process, ...

21 сент. 2024 г. · The main goal of using neural networks in stock market predictions is to create a model that can predict stock prices based on historical data.

Neural networks are a new, unique method of technical analysis, intended for those who take a thinking approach to their business.

This paper comprehensively reviews the literature on data-driven neural networks in the field of stock forecasting from 2015 to 2023.

In this study the ability of artificial neural network (ANN) in forecasting the daily NASDAQ stock exchange rate was investigated. Several feed forward ANNs ...

22 окт. 2024 г. · Abstract and Figures. This paper aims to develop an innovative neural network approach to achieve better stock market predictions.

18 июн. 2023 г. · This paper will analyze and implement a time series dynamic neural network to predict daily closing stock prices.

3 янв. 2024 г. · This study introduces an augmented Long-Short Term Memory (LSTM) neural network architecture, integrating Symbolic Genetic Programming (SGP),

LSTM neural network has a great advantage in dealing with time series prediction and further improves the performance of stock prediction. In order to predict ... Introduction · Related Work · Experiments and Results