t9_Creating a Backtester in Python_hdf_h5py_tables_dataframe_PostgreSQL_thread_no attribute ‘cursor‘

构建Python回测系统：HDF5、数据库与时间序列

最新推荐文章于 2024-07-11 22:48:14 发布

LIQING LIN

最新推荐文章于 2024-07-11 22:48:14 发布

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分类专栏： pythonForFinance2 文章标签： python big data 大数据

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本章介绍了如何创建回测系统，探讨了内样本与外样本数据、纸面交易、原始数据存储以及使用HDF5和数据库存储时间序列的重要性。回测对于交易策略的验证和优化至关重要，它使用历史数据评估策略的盈利能力，并避免实际资金损失。文章还讨论了事件驱动和基于循环的回测系统的优缺点，并提供了动量交易策略的回测示例。

By now, we know how to implement a trading strategy idea. We learned how to write the code to make it run in a trading system. The final step before going live with a trading strategy is backtesting. Whether you want to be more confident in the performance of your strategy or you want to show your managers how well your trading idea performs, you will have to use a backtester using a large amount of historical data.

In this chapter, you will learn how to create a backtester. You will improve your trading algorithm by running different scenarios with large amounts of data to validate the performance