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NexQuant/docs/scens/data_copilot_fin.rst
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Xisen Wang 84d957a615 feat: Uploaded Documentation, Updated Prompts & Some Code for model demo (#144)
* Added three new keys on hypothesis reasoning

* Updated two scenario rich text

* Uploaded Documentation & Further Improved Demo of Models

* Add docs

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Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
2024-08-02 16:22:06 +08:00

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.. _data_copilot_fin:
=====================
Finance Data Copilot
=====================
Scen2:
------
📄 Research Report-Based Factor Extraction
Scen2 Intro
~~~~~~~~~~~
In this scenario, factors and hypotheses are extracted from research reports. The process includes:
- **🔍 Factor Extraction**: Extract relevant factors from research reports.
- **📝 Factor Creation**: Define these extracted factors.
- **✅ Factor Validation**: Validate the extracted factors.
- **📈 Backtesting with Qlib**:
- **Dataset**: CSI300
- **Model**: LGBModel
- **Factors**: Alpha158 +
- **Data Split**:
- **Train**: 2008-01-01 to 2014-12-31
- **Valid**: 2015-01-01 to 2016-12-31
- **Test**: 2017-01-01 to 2020-08-01
- **🔄 Feedback Analysis**: Analyze backtest results.
- **🔧 Hypothesis Refinement**: Refine hypotheses based on feedback and continue the cycle.
Scen2 Demo
~~~~~~~~~~
.. TODO
Scen2 Quick Start
~~~~~~~~~~~~~~~~~
To quickly start the factor extraction process, run the following command in your terminal within the 'rdagent' virtual environment:
.. code-block:: sh
python rdagent/app/qlib_rd_loop/factor_from_report_sh.py
Usage of modules
~~~~~~~~~~~~~~~~~
TODO: Show some examples: