ai-portfolio-selection
github.com/dongheechoi/ai-portfolio-selection ↗Artificial Intelligence (AI) based Portfolio Selection Papers
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AI + LLM Portfolio Selection PapersArtificial Intelligence (AI) based Portfolio Selection PapersAI-based TradingAI-based Stock PredictionSurveyOther Approaches
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AI-based Stock Prediction
- Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts
- A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM
- Causality-Guided Multi-Memory Interaction Network for Multivariate Stock Price Movement Prediction
- DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting
- Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction
- Enhancing Few-Shot Stock Trend Prediction with Large Language Models
Artificial Intelligence (AI) based Portfolio Selection Papers
- A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
- A Deep Temporal Factor Analysis Method for Large Scale Financial Portfolio Selection
- An Adaptive News-Driven Method for CVaR-sensitive Online Portfolio Selection in Non-Stationary Financial Markets
- Cross-Insight Trader: A Trading Approach Integrating Policies with Diverse Investment Horizons for Portfolio Management
- Curriculum learning empowered reinforcement learning for graph-based portfolio management: Performance optimization and comprehensive analysis
- Decision-focused Sparse Tangent Portfolio Optimization
AI-based Trading
- Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization
- AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks
- A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
- DeepScalper: A risk-aware reinforcement learning framework to capture fleeting intraday trading opportunities.
- EarnHFT: Efficient Hierarchical Reinforcement Learning for High Frequency Trading
- Efficient Continuous Space Policy Optimization for High-frequency Trading
Other Approaches
- A machine learning trading system for the stock market based on N-period Min-Max labeling using XGBoost
- An asset subset-constrained minimax optimization framework for online portfolio selection
- CAST: A Cross-Asset State-Space Trading System for Drawdown Control in Stock Markets
- ChatGPT Informed Graph Neural Network for Stock Movement Prediction
- FinSense: An Assistant System for Financial Journalists and Investors
- Heterogeneous Interactive Snapshot Network for Review-Enhanced Stock Profiling and Recommendation
Survey
Resources
AI + LLM Portfolio Selection Papers
Showing a sample of 89 resources. View the full list on GitHub →