Papers with Code 아카이브
Stock Market Prediction
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AI4Finance-Foundation/FinRL
공식 코드FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
https://github.com/BUAA-WJR/PriceGraph
공식 코드Price graphs: Utilizing the structural information of financial time series for stock prediction
https://github.com/DMLab-Tensor/SliceNStitch
공식 코드SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams
https://github.com/HeathCiff/Multi-modal-Attention-Network-for-Stock-Movements-Prediction
공식 코드Multi-modal Attention Network for Stock Movements Prediction
https://github.com/Hongshen-Yang/pair-trading-envs
공식 코드Reinforcement Learning Pair Trading: A Dynamic Scaling approach
https://github.com/JingyiGu/IndexGAN
공식 코드Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative Network
https://github.com/MagiaSN/CommonsenseERL_EMNLP_2019
공식 코드Event Representation Learning Enhanced with External Commonsense Knowledge
https://github.com/Shanlearning/SP-500-Stock-Prediction
공식 코드S&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data
https://github.com/Srizzle/Deep-Time-Series
공식 코드https://github.com/Xinyi6/DP-LSTM-Differential-Privacy-inspired-LSTM-for-Stock-Prediction-Using-Financial-News
공식 코드DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
https://github.com/Yusufma03/pfrnns
공식 코드https://github.com/Zhihan1996/TradeTheEvent
공식 코드Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading
https://github.com/adlnlp/finllms
공식 코드https://github.com/ali-meh619/samba
공식 코드Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction
https://github.com/baidu/Senta
공식 코드SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis
https://github.com/chancefocus/pixiu
공식 코드PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
https://github.com/chancefocus/trials
공식 코드Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning
https://github.com/dmis-lab/hats
공식 코드HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction
https://github.com/fernandodemeer/rl_optimal_execution
공식 코드A Modular Framework for Reinforcement Learning Optimal Execution
https://github.com/frinkleko/finreport
공식 코드FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model
https://github.com/fxing79/ibaa
공식 코드Discovering Bayesian Market Views for Intelligent Asset Allocation
https://github.com/gon-uri/detach_rocket
공식 코드https://github.com/google-research/bert
공식 코드BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/hamid-nasiri/vmd-mfrfnn
공식 코드https://github.com/hao1zhao/bigdata23
공식 코드Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices
https://github.com/hennande/Temporal_Relational_Stock_Ranking
공식 코드https://github.com/jinanzou/astock
공식 코드Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model
https://github.com/jwwthu/DL4Stock
공식 코드Applications of deep learning in stock market prediction: recent progress
https://github.com/koa-fin/dva
공식 코드https://github.com/koa-fin/sep
공식 코드Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
https://github.com/liorsidi/StockSimilarity
공식 코드Improving S&P stock prediction with time series stock similarity
https://github.com/microsoft/qlib
공식 코드https://github.com/microsoft/qlib/tree/main/examples/benchmarks_dynamic/DDG-DA
공식 코드DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
https://github.com/namir0806/flag
공식 코드FLAG: Financial Long Document Classification via AMR-based GNN
https://github.com/oliverobst/decorating
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.