Midpoint method and accuracy of variability forecasting
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Abstract
This study develops an alternative variability forecasting method, the midpoint method. This method, along with the interval computing and OLS lower and upper bound methods in the literature, is applied to predict variability in the stock market and mortgage rates. Results suggest that both the midpoint and interval computing methods can generate significantly higher accuracy in variability forecasts than the OLS lower and upper bound method. Nonetheless, the midpoint method requires less asymmetric distribution of input data than the interval computing.
Keywords
Variability forecasting Midpoint method Interval computing Symmetric dataJEL Classification
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