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The sole purpose of this repository is to help me organize recent academic papers with codes related to stock price prediction, quantitative trading, risk modeling. This is a non-exhausting list, even though I'll try to keep it updated... Feel free to suggest decent papers via a PR. If you find this repository helpful consider leaving a ⭐

Table of Contents

• About
• Table of Contents
• Sorted by Time
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • Older Papers
• Sorted by Tasks
  • Stock Price Prediction
  • Stock Trading
  • Asset Pricing
  • Risk Modeling
  • Volatility & Risk Forecasting
• Sorted by Models
  • Transformer
  • Graph Neural Networks
  • Large Language Models
  • Other Models (SSM/Mamba, MLP, MoE, Foundation, Generative)
• Sorted by Methods
  • NLP-based Methods
  • Graph Learning
  • Reinforcement-learning
  • Meta- & Multi-task Learning
  • Retrieval-Augmented
  • Factor Modeling
  • Uncertainty & Probabilistic Modeling
• Datasets & Benchmarks

Sorted by Time

Back to top

2025

• (KDD 2025) Learning Universal Multi-level Market Irrationality Factors to Improve Stock Return Forecasting [Paper][Code]
• (KDD 2025) Pre-training Time Series Models with Stock Data Customization [Paper][Code]
• (KDD 2025) Progressive Dependency Representation Learning for Stock Ranking in Uncertain Risk Contrasting [Paper][Code]
• (KDD 2025) Multi-period Learning for Financial Time Series Forecasting [Paper][Code]
• (WWW 2025) HRFT: Mining High-Frequency Risk Factor Collections End-to-End via Transformer [Paper][Code]
• (WWW 2025) MERA: Mixture of Experts with Retrieval-Augmented Representation for Modeling Diversified Stock Patterns [Paper][Code]
• (ICASSP 2025) Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction [Paper][Code]

2024

• (NeurIPS 2024) A Global Optimal Portfolio for m-Sparse Sharpe Ratio Maximization [Paper][Code]
• (NeurIPS 2024) ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making [Paper][Code]
• (KDD 2024) FNSPID: A Comprehensive Financial News Dataset in Time Series [Paper][Code]
• (KDD 2024) MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading [Paper][Code]
• (COLING 2024) AlphaFin: Benchmarking Financial Analysis with Retrieval Augmented Stock-Chain Framework [Paper][Code]
• (WWW 2024) Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools [Paper][Code]
• (WWW 2024) Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models [Paper][Code]
• (WWW 2024) FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model [Paper][Code]
• (AAAI 2024) MASTER: Market-Guided Stock Transformer for Stock Price Forecasting [Paper][Code]
• (AAAI 2024) StockMixer: A Simple yet Strong MLP-based Architecture for Stock Price Forecasting [Paper][Code]

2023

• (AAAI 2023) StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series [Paper][Code]
• (ICDE 2023) Relational Temporal Graph Convolutional Network for Ranking-based Stock Prediction [Paper][Code]
• (IJCAI 2023) StockFormer: Learning Hybrid Trading Machines with Predictive Coding [Paper][Code]
• (TKDE 2023) Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks [Paper][Code]
• (KDD 2023) DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting [Paper][Code]
• (KDD 2023) Efficient Continuous Space Policy Optimization for High-frequency Trading [Paper][Code]
• (KDD 2023)Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning [Paper][Code]
• (CIKM 2023) Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction [Paper][Code]
• (2023) FinGPT: Democratizing Internet-scale Data for Financial Large Language Models [Paper][Code]
• (2023) Generative Meta-Learning Robust Quality-Diversity Portfolio [Paper][Code]
• (2023) MOPO-LSI: A User Guide [Paper][Code]

2022

• (CIKM 2022) Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction [Paper][Code]
• (CIKM 2022) DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities [Paper][Code]
• (ICASSP 2022) Hypergraph-Based Reinforcement Learning for Stock Portfolio Selection [Paper][Code]
• (AAAI 2022) FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns [Paper][Code]
• (NeurIPS workshop 2022) FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning [Paper][Code]
• (EMNLP workshop 2022) Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model [Paper][Code]
• (2022) Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Adaptive Refined Labeling [Paper][Code]
• (2022) Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions [Paper][Code]
• (2022) Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach [Paper][Code]
• (2022) Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading [Paper][Code]

2021

• (TKDE 2021) FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks [Paper][Code]
• (TKDD 2021) Graph-Based Stock Recommendation by Time-Aware Relational Attention Network [Paper][Code]
• (CIKM 2021) Attention Based Dynamic Graph Learning Framework for Asset Pricing [Paper][Code]
• (CIKM 2021) Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion [Paper][Code]
• (KDD 2021) Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts [Paper][Code]
• (EACL 2021) FAST: Financial News and Tweet Based Time Aware Network for Stock Trading [Paper][Code]
• (NAACL 2021) Quantitative Day Trading from Natural Language using Reinforcement Learning [Paper][Code]
• (AAAI 2021) Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach [Paper][Code]
• (AAAI 2021) Universal Trading for Order Execution with Oracle Policy Distillation [Paper][Code]
• (AAAI 2021) DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding [Paper][Code]
• (UAI 2021) Modeling Financial Uncertainty with Multivariate Temporal Entropy-based Curriculums [Paper][Code]
• (WWW 2021) Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading [Paper][Code]
• (SIGIR 2021) Hyperbolic Online Time Stream Modeling [Paper][Code]
• (ICAIF 2021) FinRL: deep reinforcement learning framework to automate trading in quantitative finance [Paper][Code]
• (ACL Findings 2021) Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading [Paper][Code]
• (Pattern Recognition 2021) Temporal-Relational hypergraph tri-Attention networks for stock trend prediction [Paper][Code]
• (2021) HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information [Paper][Code]

2020

• (AAAI 2020) Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States [Paper][Code]
• (EMNLP 2020) Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations [Paper][Code]
• (ICDM 2020) Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting [Paper][Code]
• (ICDM 2020) DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis [Paper][Code]
• (ACM MM 2020) Multimodal Multi-Task Financial Risk Forecasting [Paper][Code]
• (IJCAI 2020) F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification [Paper][Code]
• (IJCAI 2020) An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization [Paper][Code]
• (CIKM 2020) Fusing Global Domain Information and Local Semantic Information to Classify Financial Documents [Paper][Code]
• (ESWA 2020) Time-driven feature-aware jointly deep reinforcement learning for financial signal representation and algorithmic trading [Paper][Code]
• (2020) Open Source Cross-Sectional Asset Pricing [Paper][Code]

Older Papers

• (IJCAI 2019) Enhancing Stock Movement Prediction with Adversarial Training [Paper][Code]
• (TIS 2019) Temporal Relational Ranking for Stock Prediction [Paper][Code]
• (2019) HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction [Paper][Code]
• (KDD 2018) Investor-Imitator: A Framework for Trading Knowledge Extraction [Paper][Code]
• (ACL 2018) Stock Movement Prediction from Tweets and Historical Prices [Paper][Code]
• (WSDM 2018) Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction [Paper][Code]
• (KDD 2017) Stock Price Prediction via Discovering Multi-Frequency Trading Patterns [Paper][Code]
• (2017) A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem [Paper][Code]

Sorted by Tasks

Back to top

Stock Price Prediction

• (ICDE 2023) Relational Temporal Graph Convolutional Network for Ranking-based Stock Prediction [Paper][Code]
• (TKDE 2023) Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks [Paper][Code]
• (KDD 2023) DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting [Paper][Code]
• (2023) Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction [Paper][Code]
• (CIKM 2022) Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction [Paper][Code]
• (2022) Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions [Paper][Code]
• (CIKM 2021) Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion [Paper][Code]
• (KDD 2021) Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts [Paper][Code]
• (2021) HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information [Paper][Code]
• (EMNLP 2020) Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations [Paper][Code]
• (ICDM 2020) Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting [Paper][Code]
• (IJCAI 2019) Enhancing Stock Movement Prediction with Adversarial Training [Paper][Code]
• (TIS 2019) Temporal Relational Ranking for Stock Prediction [Paper][Code]
• (2019) HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction [Paper][Code]
• (ACL 2018) Stock Movement Prediction from Tweets and Historical Prices [Paper][Code]
• (WSDM 2018) Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction [Paper][Code]
• (KDD 2017) Stock Price Prediction via Discovering Multi-Frequency Trading Patterns [Paper][Code]

Stock Trading

• (KDD 2024) MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading [Paper][Code]
• (WWW 2024) Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools [Paper][Code]
• (KDD 2023) Efficient Continuous Space Policy Optimization for High-frequency Trading [Paper][Code]
• (KDD 2023)Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning [Paper][Code]
• (CIKM 2022) DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities [Paper][Code]
• (2022) Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading [Paper][Code]
• (ESWA 2020) Time-driven feature-aware jointly deep reinforcement learning for financial signal representation and algorithmic trading [Paper][Code]
• (IJCAI 2020) An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization [Paper][Code]
• (AAAI 2021) Universal Trading for Order Execution with Oracle Policy Distillation [Paper][Code]

Asset Pricing

• (KDD 2025) Learning Universal Multi-level Market Irrationality Factors to Improve Stock Return Forecasting [Paper][Code]
• (CIKM 2021) Attention Based Dynamic Graph Learning Framework for Asset Pricing [Paper][Code]
• (2020) Open Source Cross-Sectional Asset Pricing [Paper][Code]
• (AAAI 2022) FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns [Paper][Code]

Risk Modeling

• (WWW 2025) HRFT: Mining High-Frequency Risk Factor Collections End-to-End via Transformer [Paper][Code]
• (CIKM 2022) DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities [Paper][Code]
• (2022) Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading [Paper][Code]

Volatility & Risk Forecasting

• (WWW 2025) HRFT: Mining High-Frequency Risk Factor Collections End-to-End via Transformer [Paper][Code]
• (ACM MM 2020) Multimodal Multi-Task Financial Risk Forecasting [Paper][Code]
• (UAI 2021) Modeling Financial Uncertainty with Multivariate Temporal Entropy-based Curriculums [Paper][Code]

Sorted by Models

Back to top

Transformer

• (AAAI 2024) MASTER: Market-Guided Stock Transformer for Stock Price Forecasting [Paper][Code]
• (IJCAI 2023) StockFormer: Learning Hybrid Trading Machines with Predictive Coding [Paper][Code]
• (KDD 2021) Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts [Paper][Code]

Graph Neural Networks

• (ICDE 2023) Relational Temporal Graph Convolutional Network for Ranking-based Stock Prediction [Paper][Code]
• (TKDE 2023) Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks [Paper][Code]
• (CIKM 2022) Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction [Paper][Code]
• (2022) Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions [Paper][Code]
• (2021) HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information [Paper][Code]
• (ICDM 2020) Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting [Paper][Code]
• (2019) HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction [Paper][Code]

Large Language Models

• (2023) FinGPT: Democratizing Internet-scale Data for Financial Large Language Models [Paper][Code]
• (WWW 2024) Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models [Paper][Code]
• (COLING 2024) AlphaFin: Benchmarking Financial Analysis with Retrieval Augmented Stock-Chain Framework [Paper][Code]

Other Models (SSM/Mamba, MLP, MoE, Foundation, Generative)

• (ICASSP 2025) Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction [Paper][Code]
• (AAAI 2024) StockMixer: A Simple yet Strong MLP-based Architecture for Stock Price Forecasting [Paper][Code]
• (WWW 2025) MERA: Mixture of Experts with Retrieval-Augmented Representation for Modeling Diversified Stock Patterns [Paper][Code]
• (KDD 2025) Pre-training Time Series Models with Stock Data Customization [Paper][Code]
• (2023) Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction [Paper][Code]
• (AAAI 2022) FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns [Paper][Code]

Sorted by Methods

Back to top

NLP-based Methods

• (COLING 2024) AlphaFin: Benchmarking Financial Analysis with Retrieval Augmented Stock-Chain Framework [Paper][Code]
• (WWW 2024) Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models [Paper][Code]
• (WWW 2024) FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model [Paper][Code]
• (AAAI 2023) StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series [Paper][Code]
• (TKDE 2023) Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks [Paper][Code]
• (2023) FinGPT: Democratizing Internet-scale Data for Financial Large Language Models [Paper][Code]
• (EMNLP workshop 2022) Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model [Paper][Code]
• (NAACL 2021) Quantitative Day Trading from Natural Language using Reinforcement Learning [Paper][Code]
• (ACL Findings 2021) Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading [Paper][Code]
• (EMNLP 2020) Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations [Paper][Code]
• (IJCAI 2020) F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification [Paper][Code]
• (CIKM 2020) Fusing Global Domain Information and Local Semantic Information to Classify Financial Documents [Paper][Code]
• (ACL 2018) Stock Movement Prediction from Tweets and Historical Prices [Paper][Code]

Graph Learning

• (ICASSP 2025) Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction [Paper][Code]
• (ICDE 2023) Relational Temporal Graph Convolutional Network for Ranking-based Stock Prediction [Paper][Code]
• (TKDE 2023) Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks [Paper][Code]
• (CIKM 2022) Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction [Paper][Code]
• (ICASSP 2022) Hypergraph-Based Reinforcement Learning for Stock Portfolio Selection [Paper][Code]
• (2022) Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions [Paper][Code]
• (TKDE 2021) FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks [Paper][Code]
• (TKDD 2021) Graph-Based Stock Recommendation by Time-Aware Relational Attention Network [Paper][Code]
• (CIKM 2021) Attention Based Dynamic Graph Learning Framework for Asset Pricing [Paper][Code]
• (AAAI 2021) Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach [Paper][Code]
• (WWW 2021) Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading [Paper][Code]
• (SIGIR 2021) Hyperbolic Online Time Stream Modeling [Paper][Code]
• (2021) HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information [Paper][Code]
• (ICDM 2020) Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting [Paper][Code]
• (2019) HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction [Paper][Code]

Reinforcement-learning

• (NeurIPS 2024) ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making [Paper][Code]
• (2023) MOPO-LSI: A User Guide [Paper][Code]
• (KDD 2024) MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading [Paper][Code]
• (WWW 2024) Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools [Paper][Code]
• (KDD 2023) Efficient Continuous Space Policy Optimization for High-frequency Trading [Paper][Code]
• (KDD 2023)Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning [Paper][Code]
• (CIKM 2022) DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities [Paper][Code]
• (ICASSP 2022) Hypergraph-Based Reinforcement Learning for Stock Portfolio Selection [Paper][Code]
• (NeurIPS workshop 2022) FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning [Paper][Code]
• (2022) Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading [Paper][Code]
• (NAACL 2021) Quantitative Day Trading from Natural Language using Reinforcement Learning [Paper][Code]
• (AAAI 2021) Universal Trading for Order Execution with Oracle Policy Distillation [Paper][Code]
• (AAAI 2021) DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding [Paper][Code]
• (ICAIF 2021) FinRL: deep reinforcement learning framework to automate trading in quantitative finance [Paper][Code]
• (AAAI 2020) Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States [Paper][Code]
• (IJCAI 2020) An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization [Paper][Code]
• (ESWA 2020) Time-driven feature-aware jointly deep reinforcement learning for financial signal representation and algorithmic trading [Paper][Code]
• (2017) A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem [Paper][Code]

Meta- & Multi-task Learning

• (KDD 2023) DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting [Paper][Code]
• (2023) Generative Meta-Learning Robust Quality-Diversity Portfolio [Paper][Code]
• (2022) Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach [Paper][Code]
• (ACM MM 2020) Multimodal Multi-Task Financial Risk Forecasting [Paper][Code]

Retrieval-Augmented

• (WWW 2025) MERA: Mixture of Experts with Retrieval-Augmented Representation for Modeling Diversified Stock Patterns [Paper][Code]
• (COLING 2024) AlphaFin: Benchmarking Financial Analysis with Retrieval Augmented Stock-Chain Framework [Paper][Code]
• (WWW 2024) Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models [Paper][Code]

Factor Modeling

• (KDD 2025) Learning Universal Multi-level Market Irrationality Factors to Improve Stock Return Forecasting [Paper][Code]
• (WWW 2025) HRFT: Mining High-Frequency Risk Factor Collections End-to-End via Transformer [Paper][Code]
• (AAAI 2022) FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns [Paper][Code]

Uncertainty & Probabilistic Modeling

• (2023) Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction [Paper][Code]
• (AAAI 2022) FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns [Paper][Code]
• (UAI 2021) Modeling Financial Uncertainty with Multivariate Temporal Entropy-based Curriculums [Paper][Code]

Datasets & Benchmarks

• (KDD 2024) FNSPID: A Comprehensive Financial News Dataset in Time Series [Paper][Code]
• (NeurIPS workshop 2022) FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning [Paper][Code]