A prequential test for exchangeable theories
Alvaro Sandroni, Eran Shmaya
TL;DR
This paper introduces a prequential testing method for probabilistic forecasts that accurately identifies correct exchangeable data-generating processes without being susceptible to manipulation by false forecasts.
Contribution
It presents a novel prequential test that is both non-rejecting for true exchangeable processes and resistant to manipulation by false forecasters.
Findings
Test correctly accepts exchangeable processes
Resistant to forecaster manipulation
Applicable to probabilistic forecast evaluation
Abstract
We construct a prequential test of probabilistic forecasts that does not reject correct forecasts when the data-generating processes is exchangeable and is not manipulable by a false forecaster.
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