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Title: GitHub - microsoft/qlib: Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

Open Graph Title: GitHub - microsoft/qlib: Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

X Title: GitHub - microsoft/qlib: Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

Description: Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process. - microsoft/qlib

Open Graph Description: Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, i...

X Description: Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, i...

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qlib@microsoft.com
qlib@microsoft.com
opencode@microsoft.com

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Linkhttps://rdagent.azurewebsites.net/factor_loop?lang=en
Linkhttps://rdagent.azurewebsites.net/factor_loop?lang=zh
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R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimizationhttps://arxiv.org/abs/2505.15155
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"Qlib: An AI-oriented Quantitative Investment Platform"https://arxiv.org/abs/2009.11189
Planshttps://github.com/microsoft/qlib#plans
Framework of Qlibhttps://github.com/microsoft/qlib#framework-of-qlib
Quick Starthttps://github.com/microsoft/qlib#quick-start
Installationhttps://github.com/microsoft/qlib#installation
Data Preparationhttps://github.com/microsoft/qlib#data-preparation
Auto Quant Research Workflowhttps://github.com/microsoft/qlib#auto-quant-research-workflow
Building Customized Quant Research Workflow by Codehttps://github.com/microsoft/qlib#building-customized-quant-research-workflow-by-code
Quant Dataset Zoohttps://github.com/microsoft/qlib#quant-dataset-zoo
Learning Frameworkhttps://github.com/microsoft/qlib#learning-framework
More About Qlibhttps://github.com/microsoft/qlib#more-about-qlib
Offline Mode and Online Modehttps://github.com/microsoft/qlib#offline-mode-and-online-mode
Performance of Qlib Data Serverhttps://github.com/microsoft/qlib#performance-of-qlib-data-server
Related Reportshttps://github.com/microsoft/qlib#related-reports
Contact Ushttps://github.com/microsoft/qlib#contact-us
Contributinghttps://github.com/microsoft/qlib#contributing
Main Challenges & Solutions in Quant Researchhttps://github.com/microsoft/qlib#main-challenges--solutions-in-quant-research
Forecasting: Finding Valuable Signals/Patternshttps://github.com/microsoft/qlib#forecasting-finding-valuable-signalspatterns
Quant Model (Paper) Zoohttps://github.com/microsoft/qlib#quant-model-paper-zoo
Run a Single Modelhttps://github.com/microsoft/qlib#run-a-single-model
Run Multiple Modelshttps://github.com/microsoft/qlib#run-multiple-models
Adapting to Market Dynamicshttps://github.com/microsoft/qlib#adapting-to-market-dynamics
Reinforcement Learning: modeling continuous decisionshttps://github.com/microsoft/qlib#reinforcement-learning-modeling-continuous-decisions
https://github.com/microsoft/qlib#plans
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reinforcement learninghttps://qlib.readthedocs.io/en/latest/component/rl.html
supervised learninghttps://qlib.readthedocs.io/en/latest/component/workflow.html#model-section
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analysishttps://qlib.readthedocs.io/en/latest/component/report.html
served onlinehttps://qlib.readthedocs.io/en/latest/component/online.html
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this data sourcehttps://github.com/chenditc/investment_data/releases
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documentationhttps://qlib.readthedocs.io/en/latest/developer/how_to_build_image.html
https://github.com/microsoft/qlib#auto-quant-research-workflow
workflow_config_lightgbm_Alpha158.yamlhttps://github.com/microsoft/qlib/blob/main/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml
docshttps://qlib.readthedocs.io/en/latest/component/strategy.html#result
workflowhttps://qlib.readthedocs.io/en/latest/component/workflow.html
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_cumulative_return.png
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_long_short.png
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_IC.png
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_monthly_IC.png
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_NDQ.png
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_auto_correlation.png
https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/report.png
Explanationhttps://qlib.readthedocs.io/en/latest/component/report.html
https://github.com/microsoft/qlib#building-customized-quant-research-workflow-by-code
Herehttps://github.com/microsoft/qlib/blob/main/examples/workflow_by_code.ipynb
https://github.com/microsoft/qlib#main-challenges--solutions-in-quant-research
https://github.com/microsoft/qlib#forecasting-finding-valuable-signalspatterns
Quant Model (Paper) Zoohttps://github.com/microsoft/qlib/blob/main/examples/benchmarks
https://github.com/microsoft/qlib#quant-model-paper-zoo
GBDT based on XGBoost (Tianqi Chen, et al. KDD 2016)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/XGBoost
GBDT based on LightGBM (Guolin Ke, et al. NIPS 2017)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/LightGBM
GBDT based on Catboost (Liudmila Prokhorenkova, et al. NIPS 2018)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/CatBoost
MLP based on pytorchhttps://github.com/microsoft/qlib/blob/main/examples/benchmarks/MLP
LSTM based on pytorch (Sepp Hochreiter, et al. Neural computation 1997)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/LSTM
GRU based on pytorch (Kyunghyun Cho, et al. 2014)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/GRU
ALSTM based on pytorch (Yao Qin, et al. IJCAI 2017)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/ALSTM
GATs based on pytorch (Petar Velickovic, et al. 2017)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/GATs
SFM based on pytorch (Liheng Zhang, et al. KDD 2017)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/SFM
TFT based on tensorflow (Bryan Lim, et al. International Journal of Forecasting 2019)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/TFT
TabNet based on pytorch (Sercan O. Arik, et al. AAAI 2019)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/TabNet
DoubleEnsemble based on LightGBM (Chuheng Zhang, et al. ICDM 2020)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/DoubleEnsemble
TCTS based on pytorch (Xueqing Wu, et al. ICML 2021)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/TCTS
Transformer based on pytorch (Ashish Vaswani, et al. NeurIPS 2017)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/Transformer
Localformer based on pytorch (Juyong Jiang, et al.)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/Localformer
TRA based on pytorch (Hengxu, Dong, et al. KDD 2021)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/TRA
TCN based on pytorch (Shaojie Bai, et al. 2018)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/TCN
ADARNN based on pytorch (YunTao Du, et al. 2021)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/ADARNN
ADD based on pytorch (Hongshun Tang, et al.2020)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/ADD
IGMTF based on pytorch (Wentao Xu, et al.2021)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/IGMTF
HIST based on pytorch (Wentao Xu, et al.2021)https://github.com/microsoft/qlib/blob/main/examples/benchmarks/HIST
KRNN based on pytorchhttps://github.com/microsoft/qlib/blob/main/examples/benchmarks/KRNN
Sandwich based on pytorchhttps://github.com/microsoft/qlib/blob/main/examples/benchmarks/Sandwich
herehttps://github.com/microsoft/qlib/blob/main/examples/benchmarks/README.md
https://github.com/microsoft/qlib#run-a-single-model
benchmarkshttps://github.com/microsoft/qlib/blob/main/examples/benchmarks
onehttps://github.com/microsoft/qlib/blob/main/examples/workflow_by_code.py
run_all_model.pyhttps://github.com/microsoft/qlib/blob/main/examples/run_all_model.py
benchmarkshttps://github.com/microsoft/qlib/blob/main/examples/benchmarks
docstringshttps://github.com/microsoft/qlib/blob/main/examples/run_all_model.py
https://github.com/microsoft/qlib#run-multiple-models
run_all_model.pyhttps://github.com/microsoft/qlib/blob/main/examples/run_all_model.py
docstringshttps://github.com/microsoft/qlib/blob/main/examples/run_all_model.py
https://github.com/microsoft/qlib#break-change
Adapting to Market Dynamicshttps://github.com/microsoft/qlib/blob/main/examples/benchmarks_dynamic
https://github.com/microsoft/qlib#adapting-to-market-dynamics
Rolling Retraininghttps://github.com/microsoft/qlib/blob/main/examples/benchmarks_dynamic/baseline
DDG-DA on pytorch (Wendi, et al. AAAI 2022)https://github.com/microsoft/qlib/blob/main/examples/benchmarks_dynamic/DDG-DA
https://github.com/microsoft/qlib#reinforcement-learning-modeling-continuous-decisions
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https://github.com/microsoft/qlib#rl-for-order-execution
Herehttps://qlib.readthedocs.io/en/latest/component/rl/overall.html#order-execution
herehttps://github.com/microsoft/qlib/blob/main/examples/rl_order_execution
TWAPhttps://github.com/microsoft/qlib/blob/main/examples/rl_order_execution/exp_configs/backtest_twap.yml
PPO: "An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization", IJCAL 2020https://github.com/microsoft/qlib/blob/main/examples/rl_order_execution/exp_configs/backtest_ppo.yml
OPDS: "Universal Trading for Order Execution with Oracle Policy Distillation", AAAI 2021https://github.com/microsoft/qlib/blob/main/examples/rl_order_execution/exp_configs/backtest_opds.yml
https://github.com/microsoft/qlib#quant-dataset-zoo
Alpha360https://github.com/microsoft/qlib/blob/main/qlib/contrib/data/handler.py
Alpha158https://github.com/microsoft/qlib/blob/main/qlib/contrib/data/handler.py
Herehttps://qlib.readthedocs.io/en/latest/advanced/alpha.html
https://github.com/microsoft/qlib#learning-framework
herehttps://qlib.readthedocs.io/en/latest/component/model.html
herehttps://qlib.readthedocs.io/en/latest/component/rl.html
https://github.com/microsoft/qlib#more-about-qlib
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