mirror of
https://github.com/NicolasBohn/NexQuant.git
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Xisen Wang
84d957a615
* Added three new keys on hypothesis reasoning * Updated two scenario rich text * Uploaded Documentation & Further Improved Demo of Models * Add docs --------- Co-authored-by: Young <afe.young@gmail.com> Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
49 lines
1.2 KiB
ReStructuredText
49 lines
1.2 KiB
ReStructuredText
.. _data_agent_fin:
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=====================
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Finance Data Agent
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=====================
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Scen1
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-----
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🤖 Knowledge-Based Hypothesis Generation and Iteration
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Scen1 Intro
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~~~~~~~~~~~
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In this scenario, our model autonomously generates and tests hypotheses using a knowledge base. The process involves:
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- **🔍 Hypothesis Generation**: The model proposes new hypotheses.
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- **📝 Factor Creation**: Write and define new factors.
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- **✅ Factor Validation**: Validate the factors quantitatively.
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- **📈 Backtesting with Qlib**:
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- **Dataset**: CSI300
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- **Model**: LGBModel
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- **Factors**: Alpha158 +
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- **Data Split**:
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- **Train**: 2008-01-01 to 2014-12-31
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- **Valid**: 2015-01-01 to 2016-12-31
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- **Test**: 2017-01-01 to 2020-08-01
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- **🔄 Feedback Analysis**: Analyze backtest results.
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- **🔧 Hypothesis Refinement**: Refine hypotheses based on feedback and repeat.
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Scen1 Demo
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~~~~~~~~~~
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.. TODO
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Scen1 Quick Start
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~~~~~~~~~~~~~~~~~
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To quickly start the factor extraction process, run the following command in your terminal within the 'rdagent' virtual environment:
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.. code-block:: sh
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python rdagent/app/qlib_rd_loop/factor.py
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Usage of modules
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~~~~~~~~~~~~~~~~~
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TODO: Show some examples:
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