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# Nested Decision Execution
This workflow is an example for nested decision execution in backtesting. Qlib supports nested decision execution in backtesting. It means that users can use different strategies to make trade decision in different frequencies.
## Weekly Portfolio Generation and Daily Order Execution
This workflow provides an example that uses a DropoutTopkStrategy (a strategy based on the daily frequency Lightgbm model) in weekly frequency for portfolio generation and uses SBBStrategyEMA (a rule-based strategy that uses EMA for decision-making) to execute orders in daily frequency.
### Usage
Start backtesting by running the following command:
```bash
python workflow.py backtest
```
Start collecting data by running the following command:
```bash
python workflow.py collect_data
```
## Daily Portfolio Generation and Minutely Order Execution
This workflow also provides a high-frequency example that uses a DropoutTopkStrategy for portfolio generation in daily frequency and uses SBBStrategyEMA to execute orders in minutely frequency.
### Usage
Start backtesting by running the following command:
```bash
python workflow.py backtest_highfreq
```