標題: Forecasting financial volatilities with extreme values: The Conditional Autoregressive Range (CARR) Model
作者: Chou, RY
經營管理研究所
Institute of Business and Management
關鍵字: CARR;high/low range;extreme values;GARCH;ACD
公開日期: 1-六月-2005
摘要: 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.
URI: http://dx.doi.org/10.1353/mcb.2005.0027
http://hdl.handle.net/11536/14403
ISSN: 0022-2879
DOI: 10.1353/mcb.2005.0027
期刊: JOURNAL OF MONEY CREDIT AND BANKING
Volume: 37
Issue: 3
起始頁: 561
結束頁: 582
顯示於類別:期刊論文


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  1. 000230133700010.pdf