今天继续和大家分享一个策略,本策略基于机器学习方法实现。
一、策略概述
本策略主旨思想是利用SVR建立的模型对股票每日开盘价进行回归拟合,即把前一日的 (openPrice, highestPrice, lowestPrice, closePrice, turnoverVol, turnoverValue) 作为当日 'openPrice' 的自变量，当日 'openPrice' 作为因变量。SVR的实现使用第三方库scikit-learn。

二、SVR
SVR参考文献见下方


SVM-Regression
The method of Support Vector Classification can be extended to solve regression problems. This method is called Support Vector Regression.
The model produced by support vector classification (as described above) depends only on a subset of the training data, because the cost function for building the model does not care about training points that lie beyond the margin. Analogously, the model produced by Support Vector Regression depends only on a subset of the training data, because the cost function for building the model ignores any training data close to the model prediction.

三、回测结果:


四、风险：
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更多策略及代码移步：https://www.joinquant.com/post/271