Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model

Ray Chou

Journal of Money, Credit and Banking, 2005, vol. 37, issue 3, 561-82

Abstract: We propose a dynamic model for the high/low range of asset prices within fixed time intervals: the Conditional Autoregressive Range Model (henceforth CARR). The evolution of the conditional range is specified in a fashion similar to the conditional variance models as in GARCH and is very similar to the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998). Extreme value theories imply that the range is an efficient estimator of the local volatility, e.g., Parkinson (1980). Hence, CARR can be viewed as a model of volatility. Out-of-sample volatility forecasts using the S&P500 index data show that the CARR model does provide sharper volatility estimates compared with a standard GARCH model.

Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (184)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mcb:jmoncb:v:37:y:2005:i:3:p:561-82

Access Statistics for this article

Journal of Money, Credit and Banking is currently edited by Robert deYoung, Paul Evans, Pok-Sang Lam and Kenneth D. West

More articles in Journal of Money, Credit and Banking from Blackwell Publishing
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().