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Level II
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Quantitative Methods
Quantitative Methods
Hard
An analyst uses standard 5-fold cross-validation to evaluate a random forest model for predicting monthly stock returns. The primary concern with this approach for time series data is that:
A
Random fold assignment allows future data to appear in training sets, creating look-ahead bias
B
Five folds provide insufficient data for training the model
C
Random forests require at least 10-fold cross-validation for reliable estimates
D
Cross-validation is inappropriate for random forest models due to their ensemble nature
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Tags
#cross-validation
#look-ahead-bias
#time-series
#walk-forward
#random-forest
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