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qlib/docs/introduction/introduction.rst
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``Qlib``: Quantitative Library
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Introduction
===================
``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``, users can easily apply their favorite model to create better Quant investment strategy.
Framework
==================
.. image:: ../_static/img/framework.png
:alt: Framework
At module level, ``Qlib`` is a platform that consists of the above components. Each components is loose-coupling and can be used stand-alone.
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Name Description
====================== ========================================================================
`Data layer` `DataServer` focus on providing high performance infrastructure for user
to retrieve and get raw data. `DataEnhancement` will preprocess the data
and provide the best dataset to be fed in to the models.
`Interday Model` `Interday model` focus on producing forecasting signals(aka. `alpha`).
Models are trained by `Model Creator` and managed by `Model Manager`.
User could choose one or multiple models for forecasting. Multiple models
could be combined with `Ensemble` module.
`Interday Strategy` `Portfolio Generator` will take forecasting signals as input and output
the orders based on current position to achieve target portfolio.
`Intraday Trading` `Order Executor` is responsible for executing orders output by
`Interday Strategy` and returning the executed results.
`Analysis` User could get detailed analysis report of forecasting signal and portfolio
in this part.
====================== ========================================================================
- The modules with hand-drawn style is under development and will be released in the future.
- The modules with dashed border is highly user-customizable and extendible.