Proving Prediction Prudence

23 Pages Posted: 5 Jun 2020 Last revised: 24 Jun 2020

See all articles by Dirk Tasche

Dirk Tasche

Swiss Financial Market Supervisory Authority (FINMA)

Date Written: May 7, 2020

Abstract

We study how to perform tests on samples of pairs of observations and predictions in order to assess whether or not the predictions are prudent. Prudence requires that that the mean of the difference of the observation-prediction pairs can be shown to be significantly negative. For safe conclusions, we suggest testing both unweighted (or equally weighted) and weighted means and explicitly taking into account the randomness of individual pairs. The test methods presented are mainly specified as bootstrap and normal approximation algorithms. The tests are general but can be applied in particular in the area of credit risk, both for regulatory and accounting purposes.

Keywords: Paired difference test, weighted mean, credit risk, PD, LGD, EAD, CCF

JEL Classification: G21, C12

Suggested Citation

Tasche, Dirk, Proving Prediction Prudence (May 7, 2020). Available at SSRN: https://ssrn.com/abstract=3595625 or http://dx.doi.org/10.2139/ssrn.3595625

Dirk Tasche (Contact Author)

Swiss Financial Market Supervisory Authority (FINMA) ( email )

Einsteinstrasse 2
Bern, 3003
Switzerland

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