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CAViaR-based forecast for oil price risk

  • Huang, Dashan
  • Yu, Baimin
  • Fabozzi, Frank J.
  • Fukushima, Masao

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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Article provided by Elsevier in its journal Energy Economics.

Volume (Year): 31 (2009)
Issue (Month): 4 (July)
Pages: 511-518

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Handle: RePEc:eee:eneeco:v:31:y:2009:i:4:p:511-518
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