Estimating oil price value at risk using belief functions
© Springer International Publishing Switzerland 2015. We consider extreme value theory to study extreme price movements in crude oil market. Autoregressive-Moving-Average models are developed to describe daily log return of crude oil price. Peak-over-thresholdmodels are then used to model the log re...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
Springer Verlag
2015
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| Subjects: | |
| Online Access: | http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84919372650&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39147 |
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| Institution: | Chiang Mai University |
| Summary: | © Springer International Publishing Switzerland 2015. We consider extreme value theory to study extreme price movements in crude oil market. Autoregressive-Moving-Average models are developed to describe daily log return of crude oil price. Peak-over-thresholdmodels are then used to model the log return forecasting errors (residuals). The maximum residuals are expressed in terms of value-at-risk or return level corresponding to accepted levels of risk so that appropriate risk measures can be taken. A likelihood-based belief function is constructed to quantify estimation uncertainty. As a result, we can assess the plausibility of various assertions about the value-at-risk of the idiosyncratic shocks in the world crude oil market. |
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