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Title: GitHub - ProjectC/qlib: Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. · GitHub

Open Graph Title: GitHub - ProjectC/qlib: Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

X Title: GitHub - ProjectC/qlib: Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

Description: Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. - ProjectC/qlib

Open Graph Description: Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, yo...

X Description: Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, yo...

Mail addresses
qlib@microsoft.com
qlib@microsoft.com
opencode@microsoft.com

Opengraph URL: https://github.com/ProjectC/qlib

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Releasedhttps://github.com/microsoft/qlib/pull/290
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"Qlib: An AI-oriented Quantitative Investment Platform"https://arxiv.org/abs/2009.11189
Planshttps://github.com/ProjectC/qlib#plans
Framework of Qlibhttps://github.com/ProjectC/qlib#framework-of-qlib
Quick Starthttps://github.com/ProjectC/qlib#quick-start
Installationhttps://github.com/ProjectC/qlib#installation
Data Preparationhttps://github.com/ProjectC/qlib#data-preparation
Auto Quant Research Workflowhttps://github.com/ProjectC/qlib#auto-quant-research-workflow
Building Customized Quant Research Workflow by Codehttps://github.com/ProjectC/qlib#building-customized-quant-research-workflow-by-code
Quant Dataset Zoohttps://github.com/ProjectC/qlib#quant-dataset-zoo
Learning Frameworkhttps://github.com/ProjectC/qlib#learning-framework
More About Qlibhttps://github.com/ProjectC/qlib#more-about-qlib
Offline Mode and Online Modehttps://github.com/ProjectC/qlib#offline-mode-and-online-mode
Performance of Qlib Data Serverhttps://github.com/ProjectC/qlib#performance-of-qlib-data-server
Related Reportshttps://github.com/ProjectC/qlib#related-reports
Contact Ushttps://github.com/ProjectC/qlib#contact-us
Contributinghttps://github.com/ProjectC/qlib#contributing
Main Challenges & Solutions in Quant Researchhttps://github.com/ProjectC/qlib#main-challenges--solutions-in-quant-research
Forecasting: Finding Valuable Signals/Patternshttps://github.com/ProjectC/qlib#forecasting-finding-valuable-signalspatterns
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supervised learninghttps://qlib.readthedocs.io/en/latest/component/workflow.html#model-section
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https://github.com/ProjectC/qlib#data-preparation
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crawler scriptshttps://github.com/ProjectC/qlib/blob/main/scripts/data_collector
Description of datasethttps://github.com/microsoft/qlib/tree/main/scripts/data_collector#description-of-dataset
Yahoo Financehttps://finance.yahoo.com/lookup
related documenthttps://qlib.readthedocs.io/en/latest/component/data.html#converting-csv-format-into-qlib-format
https://github.com/ProjectC/qlib#automatic-update-of-daily-frequency-data-from-yahoo-finance
yahoo collectorhttps://github.com/microsoft/qlib/tree/main/scripts/data_collector/yahoo#automatic-update-of-daily-frequency-datafrom-yahoo-finance
yahoo collectorhttps://github.com/microsoft/qlib/tree/main/scripts/data_collector/yahoo#automatic-update-of-daily-frequency-datafrom-yahoo-finance
https://github.com/ProjectC/qlib#auto-quant-research-workflow
workflow_config_lightgbm_Alpha158.yamlhttps://github.com/ProjectC/qlib/blob/main/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml
Intraday Tradinghttps://qlib.readthedocs.io/en/latest/component/backtest.html
workflowhttps://qlib.readthedocs.io/en/latest/component/workflow.html
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Explanationhttps://qlib.readthedocs.io/en/latest/component/report.html
https://github.com/ProjectC/qlib#building-customized-quant-research-workflow-by-code
Herehttps://github.com/ProjectC/qlib/blob/main/examples/workflow_by_code.ipynb
https://github.com/ProjectC/qlib#main-challenges--solutions-in-quant-research
https://github.com/ProjectC/qlib#forecasting-finding-valuable-signalspatterns
Quant Model (Paper) Zoohttps://github.com/ProjectC/qlib/blob/main/examples/benchmarks
https://github.com/ProjectC/qlib#quant-model-paper-zoo
GBDT based on XGBoost (Tianqi Chen, et al. KDD 2016)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/XGBoost
GBDT based on LightGBM (Guolin Ke, et al. NIPS 2017)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/LightGBM
GBDT based on Catboost (Liudmila Prokhorenkova, et al. NIPS 2018)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/CatBoost
MLP based on pytorchhttps://github.com/ProjectC/qlib/blob/main/examples/benchmarks/MLP
LSTM based on pytorch (Sepp Hochreiter, et al. Neural computation 1997)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/LSTM
GRU based on pytorch (Kyunghyun Cho, et al. 2014)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/GRU
ALSTM based on pytorch (Yao Qin, et al. IJCAI 2017)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/ALSTM
GATs based on pytorch (Petar Velickovic, et al. 2017)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/GATs
SFM based on pytorch (Liheng Zhang, et al. KDD 2017)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/SFM
TFT based on tensorflow (Bryan Lim, et al. International Journal of Forecasting 2019)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/TFT
TabNet based on pytorch (Sercan O. Arik, et al. AAAI 2019)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/TabNet
DoubleEnsemble based on LightGBM (Chuheng Zhang, et al. ICDM 2020)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/DoubleEnsemble
TCTS based on pytorch (Xueqing Wu, et al. ICML 2021)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/TCTS
Transformer based on pytorch (Ashish Vaswani, et al. NeurIPS 2017)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/Transformer
Localformer based on pytorch (Juyong Jiang, et al.)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/Localformer
TRA based on pytorch (Hengxu, Dong, et al. KDD 2021)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/TRA
TCN based on pytorch (Shaojie Bai, et al. 2018)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/TCN
ADARNN based on pytorch (YunTao Du, et al. 2021)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/ADARNN
ADD based on pytorch (Hongshun Tang, et al.2020)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/ADD
IGMTF based on pytorch (Wentao Xu, et al.2021)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/IGMTF
HIST based on pytorch (Wentao Xu, et al.2021)https://github.com/ProjectC/qlib/blob/main/examples/benchmarks/HIST
herehttps://github.com/ProjectC/qlib/blob/main/examples/benchmarks/README.md
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Rolling Retraininghttps://github.com/ProjectC/qlib/blob/main/examples/benchmarks_dynamic/baseline
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