liuyu/qlib

mirror of https://github.com/microsoft/qlib.git synced 2026-07-01 10:01:19 +08:00

Files

Pengrong Zhu c276de4040 Fix backtest (#719 )

* modify FileStorage to support multiple freqs

* modify backtest's sample documentation

* change the logging level of read data exception from error to debug

* fix the backtest exception when volume is 0 or np.nan

* fix test_storage.py

* add backtest_daily

* modify backtest_daily's docstring

* add __repr__/__str__ to Position

* fix the bug of nested_decision_execution example

Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>

2021-12-07 19:04:23 +08:00

README.md

fix comments & add VAStrategy & add trade indicator

2021-06-14 21:32:18 +08:00

workflow.py

Fix backtest (#719 )

2021-12-07 19:04:23 +08:00

README.md

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:

    python workflow.py backtest

Start collecting data by running the following command:

    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:

    python workflow.py backtest_highfreq