November 2022
Intermediate to advanced
392 pages
10h 8m
Chinese
Content preview from Python算法交易
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通过机器学习预测市场动向
｜
171
5.2.4
方法通用化
“分类算法回测类”介绍了一个
Python
模块，其中包含一个类，用于基于
scikit-
learn
的线性模型对策略进行向量化回测。尽管仅实现了线性回归和逻辑回
归，但是可以轻松增加模型数量。原则上，
ScikitVectorBacktester
类可以从
LRVectorBacktester
继承选定的方法，虽然它是以独立的方式呈现的。这样可以更
轻松地增强此类并将其重用于实际应用。
基于
ScikitBacktesterClass
，可以对基于逻辑回归的策略进行样本外评估。该示
例使用
EUR/USD
汇率作为基础工具。
图
5-15
说明了该策略在样本外期间（跨越
2019
年）的表现优于基本工具，但未像
以前那样考虑交易成本：
In [123]: import ScikitVectorBacktester as SCI
In [124]: scibt = SCI.ScikitVectorBacktester('EUR=',
'2010-1-1', '2019-12-31',
10000, 0.0, 'logistic')
In [125]: scibt.run_strategy('2015-1-1', '2019-12-31',
'2015-1-1', '2019-12-31', lags=15)
Out[125]: ...
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