November 2019
Beginner
394 pages
10h 31m
English
When building a statistical model, we use cross-validation to avoid overfitting. Cross-validation imposes a division of data into two or three different sets. One set will be used to create your model, while the other sets will be used to validate the model's accuracy. Because the model has not been created with the other datasets, we will have a better idea of its performance.
When testing a trading strategy with historical data, it is important to use a portion of data for testing. In a statistical model, we call training data the initial data to create the model. For a trading strategy, we will say that we are in the in-sample data. The testing data will be called out-of-sample data. As for cross-validation, ...