Finance and Economics Discussion Series (FEDS)
August 2024
Spectral backtests unbounded and folded
Michael B. Gordy and Alexander J. McNeil
Abstract:
In the spectral backtesting framework of Gordy and McNeil (2020) a probability measure on the unit interval is used to weight the quantiles of greatest interest in the validation of forecast models using probability-integral transform (PIT) data. We extend this framework to allow general Lebesgue-Stieltjes kernel measures with unbounded distribution functions, which brings powerful new tests based on truncated location-scale families into the spectral class. Moreover, by considering uniform distribution preserving transformations of PIT values the test framework is generalized to allow tests that are focused on both tails of the forecast distribution.
Keywords: Backtesting; Volatility; Risk management
DOI: https://doi.org/10.17016/FEDS.2024.060
PDF: Full Paper
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