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Is out-of-sample testing of forecasting models a myth?
When working with forecasting models, a well-known observation is that in-sample performance is usually better, often much better, than out-of-sample performance. That is, a model generally produces better forecasts over the data that it was constructed on than over new data. … Continue reading
Posted in machine learning, stock market
Tagged cross validation, out-of-sample, overfitting
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Econometric Edge 