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Stock Price Prediction

Stock Price Prediction is the task of forecasting future stock prices based on historical data and various market indicators. It involves using statistical models and machine learning algorithms to analyze financial data and make predictions about the future performance of a stock. The goal of stock price prediction is to help investors make informed investment decisions by providing a forecast of future stock prices.

Papers

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Showing 111–120 of 137 papers

TitleStatusHype
A Dynamic Approach to Stock Price Prediction: Comparing RNN and Mixture of Experts Models Across Different Volatility Profiles—0
A Fast Evidential Approach for Stock Forecasting—0
A Generalization Bound of Deep Neural Networks for Dependent Data—0
A Hybrid Deep Learning Framework for Stock Price Prediction Considering the Investor Sentiment of Online Forum Enhanced by Popularity—0
An Advanced Ensemble Deep Learning Framework for Stock Price Prediction Using VAE, Transformer, and LSTM Model—0
Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models—0
An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework—0
A novel improved fuzzy support vector machine based stock price trend forecast model—0
Risk-Adjusted Performance of Random Forest Models in High-Frequency Trading—0
A Stock Price Prediction Approach Based on Time Series Decomposition and Multi-Scale CNN using OHLCT Images—0
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