CAViaR-based Forecast for Oil Price Risk
As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Eng...
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| التنسيق: | text |
| اللغة: | English |
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Institutional Knowledge at Singapore Management University
2009
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/lkcsb_research/4780 |
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| المؤسسة: | Singapore Management University |
| اللغة: | English |
| الملخص: | As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Engle and Manganelli [Engle, R.F., Manganelli, S., 2004. CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business and Economic Statistics 22, 367–381] to forecasting oil price risk. In doing so, we provide two original contributions by introducing a new exponentially weighted moving average CAViaR model and developing a mixed data regression model for multi-period VaR prediction. |
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