Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30956
Title: Good risk measures, bad statistical assumptions, ugly risk forecasts
Authors: Michaelides, Michael 
Niraj, Poudyal 
Major Field of Science: Social Sciences
Field Category: Economics and Business
Keywords: Basel III;financial risk forecasting;market risk;time-heterogeneous Student's t AR model;Value-at-Risk
Issue Date: 2023
Source: Financial Review, 2023
Journal: Financial Review 
Abstract: <jats:title>Abstract</jats:title><jats:p>This paper proposes the time‐heterogeneous Student's <jats:italic>t</jats:italic> autoregressive model as an alternative to the various volatility forecast models documented in the literature. The empirical results indicate that: (i) the proposed model has better forecasting performance than other commonly used models, and (ii) the problem of reliable risk measurement arises primarily from the model risk associated with risk forecast models rather than the particular risk measure for computing risk. Based on the results, the paper makes recommendations to regulators and practitioners.</jats:p>
URI: https://hdl.handle.net/20.500.14279/30956
ISSN: 07328516
15406288
DOI: 10.1111/fire.12368
Rights: © The Authors
Type: Article
Affiliation : Cyprus University of Technology 
Kathmandu University 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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