The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. It carries a higherrisk than any other investment area, due to its high rate of uncertainty and volatility, thus making the stock price behavior...
A DNN-based prediction model is designed based on the PSR method and a long- and short-term memory networks (LSTMs) for DL and used to predict stock prices. The proposed and some other prediction models are used to predict multiple stock indices for different periods. A comparison of the ...
IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how one can use neural networks to predict stock prices. It is built with the goal of allowing beginners to understand the fundamentals of how neural network models are built and go through the entire ...
Hansun and Young (2021) used a deep learning process based on an LSTM network to predict stock prices based on closing prices. The results of this study with LSTM used as the main forecasting tool showed reasonable predictive accuracy. Empirical results associated with the research of Zhang et ...
According to research, the accuracy of neural networks in making price predictions for stocks differs. Some models predict the correct stock prices 50 to 60% of the time. Still, others have posited that a 10% improvement in efficiency is all an investor can ask for from a neural network....
The Long short term memory (LSTM) network was used to predict values of futurity time steps of a sequence of opening and closing into Dow Jones Industrial Average stock market. The LSTM network learns to forecast the value of the next step. By train the LSTM network, we have expect the ...
Modern Deep Network method is supported by big data and high-speed data process capability. For the aspect of the data, stock market data is the natural source of the research target. Notably, we dived into the stock market data in China. To find out how the stock market works in China...
International Joint Conference on Neural Network May 2017311被引用 9笔记PDF 引用 收藏 摘要原文 Predictions on stock market prices are a great challenge due to the fact that it is an immensely complex, chaotic and dynamic environment. There are many studies from various areas aiming to take on...
Functional Link Artificial Neural Network (FLANNBack-Propagation (BP) algorithmDifferential Evolution (DELeast Mean Square(LMS) MethodThis paper presents a scheme using Differential Evolution based Functional Link Artificial Neural Network(FLANN) to predict the Indian Stock Market Indices. The Model uses ...
A multilayer perceptron (MLP) neural network model with the Back-Propagation algorithm was applied to predict the Saudi Arabia stock market prices 13. Their proposed model results from their simulation demonstrated the viability of the proposed model in predicting Saudi Arabia stock markets. A trading...