Qlib
: Quantitative Platform¶
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 try their ideas to create better Quant investment strategies.
Framework¶
At the module level, Qlib is a platform that consists of above components. The components are designed as loose-coupled modules and each component could be used stand-alone.
Name | Description |
---|---|
Infrastructure layer | Infrastructure layer provides underlying support for Quant research. DataServer provides high-performance infrastructure for users to manage and retrieve raw data. Trainer provides flexible interface to control the training process of models which enable algorithms controlling the training process. |
Workflow layer | Workflow layer covers the whole workflow of quantitative investment. Information Extractor extracts data for models. Forecast Model focuses on producing all kinds of forecast signals (e.g. _alpha_, risk) for other modules. With these signals Portfolio Generator will generate the target portfolio and produce orders to be executed by Order Executor. |
Interface layer | Interface layer tries to present a user-friendly interface for the underlying system. Analyser module will provide users detailed analysis reports of forecasting signals, portfolios and execution results |
- The modules with hand-drawn style are under development and will be released in the future.
- The modules with dashed borders are highly user-customizable and extendible.