So, it is important to provide a reliable model that overwhelms the prediction complexity and capable of capturing the stock price trend in the financial market. The stochastic nature of this proposed BR-RBFN model which optimally penalises the network complexity and randomly assigns weights to the...
Short-term Stock Market Price Trend Prediction Using a Customized Deep Learning System (Doctoral dissertation, Carleton University). Srinivasan, P., & Ibrahim, P. (2010). forecasting stock market volatility of bse- 30 index using garch models. Asia Pacific Business Review, 6(3), 47–60. ...
The aims of this study are to predict the stock price trend in the stock market in an emerging economy. Using the Long Short Term Memory (LSTM) algorithm, and the corresponding technical analysis indicators for each stock code include: simple moving average (SMA), convergence divergence moving ...
This study introduces an augmented Long-Short Term Memory (LSTM) neural network architecture, integrating Symbolic Genetic Programming (SGP), with the objective of forecasting cross-sectional price returns across a comprehensive dataset comprising 4500 l
Since our proposed solution is also focusing on short-term stock price trend prediction, this work is heuristic for our system design. Meanwhile, by comparing with the popular trading strategies from investors, their work inspired us to compare the strategies used by investors with techniques used ...
sentiment analysishybrid feature selectionSentiWordNetStock trend prediction based on text has gained much attention from researchers in recent years. According ... P Meesad,J Li - IEEE 被引量: 5发表: 2015年 Stock Price Trend Prediction Using LSTM and Sentiment Analysis on News Headlines Stock ...
A novel data-driven stock price trend prediction system This paper proposes a novel stock price trend pred Zhang,Jing,Cui,... - 《Expert Systems with Application》 被引量: 3发表: 2018年 Frequency-domain enhanced bi-directional recurrent quantum network for stock price trend prediction Stock price...
Stock market has always been uncertain in terms of prediction, and it attracts the attention of all the stakeholders to predict the stock price. We have used different deep learning techniques, namely recurrent neural network (RNN) and long short-term memory (LSTM) to model our problem. The ...
stock price prediction股市预测 1.In order to overcome these disadvantages,a hybrid of genetic and back-propagation algorithms based on the predictability of stock market forstock price predictionis presented,and a neural network dealing model is developed.通过对海信电信(600060)的股票收盘价和大盘指数为...
Srivastava Stock prediction using deep learning Multimed. Tools Appl., 76 (18) (2017), pp. 18569-18584, 10.1007/s11042-016-4159-7 View in ScopusGoogle Scholar [6] J. Zhang, S. Cui, Y. Xu, Q. Li, T. Li A novel data-driven stock price trend prediction system Expert Syst. Appl.,...