McNeil, Alexander John orcid.org/0000-0002-6137-2890 and Gordy, Michael (2020) Spectral backtests of forecast distributions with application to risk management. Journal of Banking and Finance. 105817. ISSN 1872-6372
Abstract
We study a class of backtests for forecast distributions in which the test statistic depends on a spectral transformation that weights exceedance events by a function of the modeled probability level. The weighting scheme is specified by a kernel measure which makes explicit the user’s priorities for model performance. The class of spectral backtests includes tests of unconditional coverage and tests of conditional coverage. We show how the class embeds a wide variety of backtests in the existing literature, and further propose novel variants which are easily implemented, well-sized and have good power. In an empirical application, we backtest forecast distributions for the overnight P&L of ten bank trading portfolios. For some portfolios, test results depend materially on the choice of kernel.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © Elsevier, 2020. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. |
Keywords: | Backtesting; Volatility; Risk management |
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > The York Management School |
Depositing User: | Pure (York) |
Date Deposited: | 06 Apr 2020 15:30 |
Last Modified: | 21 Jan 2025 17:46 |
Published Version: | https://doi.org/10.1016/j.jbankfin.2020.105817 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.jbankfin.2020.105817 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159163 |
Download
Filename: spectraltest20200330_combined.pdf
Description: spectraltest20200330_combined
Licence: CC-BY-NC-ND 2.5