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update rule_startegy & add README, notebook for multi-level trading

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# Multi-level Trading
This worflow is an example for multi-level trading.
## Introduction
Qlib supports backtesting of various strategies, including portfolio management strategies, order split strategies, model-based strategies (such as deep learning models), rule-based strategies, and RL-based strategies.
And, Qlib also supports multi-level trading and backtesting. It means that users can use different strategies to trade at different frequencies.
This example uses a DropoutTopkStrategy (a strategy based on the daily frequency Lightgbm model) in weekly frequency for portfolio generation. And, at the daily frequency level, this example uses SBBStrategyEMA (a rule-based strategy that uses EMA for decision-making) to split orders.
## Usage
Start backtesting by running the following command:
```bash
python workflow.py
```
Also, reports is shown in workflow.ipynb