mpf9_Backtesting_mean-reverting_threshold_model_Survivorship bias_sklearn打印默认参数_Gini_k-mean_knn_CART

最新推荐文章于 2022-10-04 19:45:25 发布

LIQING LIN

最新推荐文章于 2022-10-04 19:45:25 发布

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

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本文介绍了如何设计和实现一个事件驱动的回测系统，讨论了回测中的关注点，如数据质量、交易成本等。通过模拟投资策略对历史数据的反应，探讨了k-means聚类、K最近邻（KNN）和分类回归树（CART）等算法在回测中的应用，并强调了避免回测偏见和模型风险的重要性。

A backtest is a simulation of a model-driven investment strategy's response to historical data. While working on designing and developing a backtest, it would be helpful to think in terms of the concept of creating video games.

In this chapter, we will design and implement an event-driven backtesting system using an object-oriented approach. The resulting profits and losses of our trading model may be plotted on to a graph to help visualize the performance of our trading strategy. However, is this sufficient enough to determine whether it is a good model?

There are many concerns to be addressed in backtesting—for example, the effects of transaction costs, exec