EUR/USD Exchange Rate Forecasting: A Deep Learning Approach Integrating Text Mining and Particle Swarm Optimization
Integrating textual analysis of financial news and sentiment with deep learning models, particularly LSTM optimized by PSO, significantly improves the accuracy of EUR/USD exchange rate forecasting compared to traditional methods.
A Comparative Study of Machine Learning Models for Forecasting Company Fundamentals
Deep learning models, particularly RNN variants, demonstrate superior performance in forecasting company fundamentals compared to classical statistical models, especially when considering uncertainty estimation.
Predicting Asset Return Distributions Using a Two-Stage LSTM Model with Market Data Scaling
This paper introduces a novel two-stage LSTM model for predicting asset return distributions by leveraging asset-specific features and incorporating market data scaling, demonstrating superior performance compared to linear quantile regression and a dense neural network model across various asset classes and synthetic datasets.
Comparative Analysis of GARCH-ANN, VAR, and 3D-CNN Models for S&P 500 Price Forecasting
Hybrid GARCH-LSTM models demonstrate superior performance in forecasting S&P 500 prices compared to VAR and 3D-CNN models, highlighting the importance of capturing volatility clustering and long-term dependencies in financial time series.
© 2024 by Linnk AI