Volatility forecasting with range models: An evaluation of new alternatives to ...

• Author(s): Miralles Quirós, José Luis ; Daza Izquierdo, Julio
• Date: 2011
• Persistent ID: http://hdl.handle.net/10400.21/1430
• Origin: Repositório Científico do Instituto Politécnico de Lisboa
• Subject(s): CARR; GARCH; Range estimators; Forecasting performance
• Document Type: Conference Object
• Language: English

Description

The aim of this paper is to analyze the forecasting ability of the CARR model proposed by Chou (2005) using the S&P 500. We extend the data sample, allowing for the analysis of different stock market circumstances and propose the use of various range estimators in order to analyze their forecasting performance. Our results show that there are two range-based models that outperform the forecasting ability of the GARCH model. The Parkinson model is better for upward trends and volatilities which are higher and lower than the mean while the CARR model is better for downward trends and mean volatilities.