Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30956
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Michaelides, Michael | - |
dc.contributor.author | Niraj, Poudyal | - |
dc.date.accessioned | 2023-12-21T12:36:39Z | - |
dc.date.available | 2023-12-21T12:36:39Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Financial Review, 2023 | en_US |
dc.identifier.issn | 07328516 | - |
dc.identifier.issn | 15406288 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/30956 | - |
dc.description.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> | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Financial Review | en_US |
dc.rights | © The Authors | en_US |
dc.subject | Basel III | en_US |
dc.subject | financial risk forecasting | en_US |
dc.subject | market risk | en_US |
dc.subject | time-heterogeneous Student's t AR model | en_US |
dc.subject | Value-at-Risk | en_US |
dc.title | Good risk measures, bad statistical assumptions, ugly risk forecasts | en_US |
dc.type | Article | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.collaboration | Kathmandu University | en_US |
dc.subject.category | Economics and Business | en_US |
dc.journals | Open Access | en_US |
dc.country | Cyprus | en_US |
dc.country | Nepal | en_US |
dc.subject.field | Social Sciences | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1111/fire.12368 | en_US |
dc.identifier.scopus | 2-s2.0-85174594693 | - |
dc.identifier.url | http://dx.doi.org/10.1111/fire.12368 | - |
cut.common.academicyear | 2022-2023 | en_US |
dc.identifier.external | 149016428 | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
crisitem.journal.journalissn | 1540-6288 | - |
crisitem.journal.publisher | Wiley | - |
crisitem.author.dept | Department of Finance, Accounting and Management Science | - |
crisitem.author.faculty | Faculty of Management and Economics | - |
crisitem.author.orcid | 0009-0009-6727-5563 | - |
crisitem.author.parentorg | Faculty of Management and Economics | - |
Appears in Collections: | Άρθρα/Articles |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Good risk measures bad statistical assumptions ugly risk forecasts.pdf | 521.93 kB | Adobe PDF | View/Open |
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