Multiple hypothesis testing of market risk forecasting models

Esposito, Francesco P. and Cummins, Mark (2016) Multiple hypothesis testing of market risk forecasting models. Journal of Forecasting, 35 (5). pp. 381-399. ISSN 0277-6693 (https://doi.org/10.1002/for.2381)

[thumbnail of Esposito-Cummins-JF-2016-Multiple-hypothesis-testing-of-market-risk-forecasting-models]
Preview
 Text. Filename: Esposito_Cummins_JF_2016_Multiple_hypothesis_testing_of_market_risk_forecasting_models.pdf
Accepted Author Manuscript
License: Strathprints license 1.0
Download (1MB)| Preview

Abstract

Extending previous risk model backtesting literature, we construct multiple hypothesis testing (MHT) with the stationary bootstrap. We conduct multiple tests which control for the generalized confidence level and employ the bootstrap MHT to design multiple comparison testing. We consider absolute and relative predictive ability to test a range of competing risk models, focusing on value-at-risk and expected shortfall (ExS). In devising the test for the absolute predictive ability, we take the route of recent literature and construct balanced simultaneous confidence sets that control for the generalized family-wise error rate, which is the joint probability of rejecting true hypotheses. We implement a step-down method which increases the power of the MHT in isolating false discoveries. In testing for the ExS model predictive ability, we design a new simple test to draw inference about recursive model forecasting capability. In the second suite of statistical testing, we develop a novel device for measuring the relative predictive ability in the bootstrap MHT framework.

CORE (COnnecting REpositories)