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update trainer and README.md

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2020-11-26 12:40:50 +00:00
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@@ -45,13 +45,11 @@ For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative
At the module level, Qlib is a platform that consists of the above components. The components are designed as loose-coupled modules and each component could be used stand-alone.
| Name | Description |
| ------ | ----- |
| `Data layer` | `DataServer` focuses on providing high-performance infrastructure for users to manage and retrieve raw data. `DataEnhancement` will preprocess the data and provide the best dataset to be fed into the models. |
| `Interday Model` | `Interday model` focuses on producing prediction scores (aka. _alpha_). Models are trained by `Model Creator` and managed by `Model Manager`. Users could choose one or multiple models for prediction. Multiple models could be combined with `Ensemble` module. |
| `Interday Strategy` | `Portfolio Generator` will take prediction scores as input and output the orders based on the current position to achieve the target portfolio. |
| `Intraday Trading` | `Order Executor` is responsible for executing orders output by `Interday Strategy` and returning the executed results. |
| `Analysis` | Users could get a detailed analysis report of forecasting signals and portfolios in this part. |
| 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.