CAViaR and the Australian Stock Markets: An Appetiser
AbstractValue-at-Risk (VaR) has become the universally accepted metric adopted internationally under the Basel Accords for banking industry internal control and for regulatory reporting. This has focused attention on methods of measuring, estimating and forecasting lower tail risk. One promising technique is Quantile Regression which holds the promise of efficiently calculating (VAR). To this end, Engle and Manganelli in (2004) developed their CAViaR model (Conditional Autoregressive Value at Risk). In this paper 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 and out of sample tests. We also contrast the results with those obtained from a GARCH(1,1) model, the RiskMetricsTM model and an APARCH model
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Bibliographic InfoPaper provided by Edith Cowan University, School of Accounting Finance & Economics in its series Working papers with number 2010-03.
Length: 14 pages
Date of creation: Sep 2010
Date of revision:
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Postal: 270 Joondalup Drive, Joondalup, Western Australia, 6027
Web page: http://www.ecu.edu.au/schools/accounting-finance-economics
More information through EDIRC
VaR; Quantile regressions; Autoregressive; CAViaR;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-03-19 (All new papers)
- NEP-FMK-2011-03-19 (Financial Markets)
- NEP-RMG-2011-03-19 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- David E Allen & Michael McAleer & Marcel Scharth, 2008. "Realized Volatility Uncertainty," Working papers 2008-07, Edith Cowan University, School of Accounting Finance & Economics.
- James W. Taylor, 2008. "Using Exponentially Weighted Quantile Regression to Estimate Value at Risk and Expected Shortfall," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(3), pages 382-406, Summer.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- 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.
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