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A Gourmet's delight: CAViaR and the Australian stock market

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  • D. E. Allen
  • A. K. Singh
  • R. Powell

Abstract

Value at Risk (VaR) is the metric adopted by the Basel Accords for banking industry internal control and regulatory reporting. This has focused attention on the measuring, estimating and forecasting of lower tail risk. Engle and Manganelli (2004) developed the conditional autoregressive value at risk (CAViaR) model using quantile regression to calculate VaR. In this article we apply their model to Australian stock market indices and a sample of stocks, and test the efficacy of four different specifications of the model in a set of in-sample and out-of-sample tests. We also contrast the results with those obtained from a Generalized Autoregressive Conditional Heteroskedastic (GARCH(1,1)) model, the RiskMetrics™ model (Morgan, 1996) and an Asymmetric Power Autoregressive Conditional Heteroskedastic (APARCH) model.

Suggested Citation

  • D. E. Allen & A. K. Singh & R. Powell, 2012. "A Gourmet's delight: CAViaR and the Australian stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1493-1498, October.
    • Handle: RePEc:taf:apeclt:v:19:y:2012:i:15:p:1493-1498
    DOI: 10.1080/13504851.2011.636017
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    References listed on IDEAS

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    1. James W. Taylor, 2008. "Using Exponentially Weighted Quantile Regression to Estimate Value at Risk and Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 382-406, Summer.
    2. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
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    4. Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(5), pages 793-813, December.
    5. Li, W K & Ling, Shiqing & McAleer, Michael, 2002. "Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
    6. W. K. Li & Shiqing Ling & Michael McAleer, 2002. "Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
    7. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    8. David E. Allen & Robert Powell, 2009. "Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(3), pages 425-444, September.
    9. James W. Taylor, 2008. "Estimating Value at Risk and Expected Shortfall Using Expectiles," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 231-252, Spring.
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    Cited by:

    1. Wu, JunFeng & Zhang, Chao & Chen, Yun, 2022. "Analysis of risk correlations among stock markets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    2. Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
    3. Peng, Wei & Hu, Shichao & Chen, Wang & Zeng, Yu-feng & Yang, Lu, 2019. "Modeling the joint dynamic value at risk of the volatility index, oil price, and exchange rate," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 137-149.

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