CAViaR and the Australian Stock Markets: An Appetiser
19 Pages Posted: 10 May 2010 Last revised: 23 Aug 2010
Date Written: March 1, 2010
Value-at-Risk (VaR) has become the universally accepted metric in the financial services industry for 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.
Keywords: VaR, Quantile Regressions, Autoregressive, CAViaR
JEL Classification: C31, G11
Suggested Citation: Suggested Citation