This research compares the effectiveness of neural network models in predicting the S&P500 index, recognising that a critical component of financial decision ...

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.

In this paper, we are using four types of deep learning architectures i.e Multilayer Perceptron (MLP), Recurrent Neural Networks (RNN), Long Short-Term Memory ...

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 ...

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

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

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

22 дек. 2023 г. · CNN (Convolutional Neural Networks): Effective in extracting spatial patterns from data, CNNs can be employed to analyze stock market images or ...

6 сент. 2024 г. · We introduce a novel predictive statistical mod-eling technique called Hybrid Radial Basis Function Neural Networks (HRBF-NN) as a forecaster.

In this paper represents how to predict a NASDAQ's stock value using ANNs with a given input parameters of share market.