Tag Archives: binary logistic regression
In this article we compare the out-of-sample performance of a trading strategy and a machine learning model that use the exact same features.
DLPAL PRO’s advanced capabilities are used to implement a long/short ETF strategy. We present the flow and examples of historical attribute, test/train and scoring files. A Binary Logistic Regression classifier is used to obtain the final results.
In this article we show how to prepare historical files with continues features and a discrete target for an ensemble of securities using DLPAL PRO. Then, we apply machine learning on a random sample of half of the data and … Continue reading