Stock Trend Prediction
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Benchmarks
FI-2010
Most implemented
Recurrent Highway Networks with Grouped Auxiliary Memory
Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction
Stock trend prediction using news sentiment analysis
Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
Dynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations
FLAG: Financial Long Document Classification via AMR-based GNN
Papers
MaGNet: A Mamba Dual-Hypergraph Network for Stock Prediction via Temporal-Causal and Global Relational Learning
Stock trend prediction is crucial for profitable trading strategies and portfolio management yet remains challenging due to market volatility, complex temporal dynamics and multifaceted inter-stock relationships. Existin…
Stock Trend PredictionRelational ReasoningFinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph
Individual investors are significantly outnumbered and disadvantaged in financial markets, overwhelmed by abundant information and lacking professional analysis. Equity research reports stand out as crucial resources, of…
Stock Trend PredictionA Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
Stock trend prediction involves forecasting the future price movements by analyzing historical data and various market indicators. With the advancement of machine learning, graph neural networks (GNNs) have been extensiv…
Graph Neural NetworkPredictionStock PredictionStock Trend PredictionPerforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
The neurons of artificial neural networks were originally invented when much less was known about biological neurons than is known today. Our work explores a modification to the core neuron unit to make it more parallel …
Drug DiscoveryLanguage ModelingModel CompressionStock Trend PredictionDynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations
Temporal Graph Learning (TGL) is crucial for capturing the evolving nature of stock markets. Traditional methods often ignore the interplay between dynamic temporal changes and static relational structures between stocks…
Contrastive LearningGraph LearningStock Trend PredictionA Stock Price Prediction Approach Based on Time Series Decomposition and Multi-Scale CNN using OHLCT Images
Recently, deep learning in stock prediction has become an important branch. Image-based methods show potential by capturing complex visual patterns and spatial correlations, offering advantages in interpretability over t…
Stock PredictionStock Price PredictionStock Trend PredictionTime Series