This paper proposes a calibration algorithm that fits multi-factor Gaussian models to the implied volatilities of caps using the respective minimal consistent family to infer the forward rate curve. The algorithm is applied to three forward rate volatility structures and their combination to form two-factor models. The efficiency of the consistent calibration is evaluated through comparisons with non-consistent methods. The selection of the number of factors and of the volatility functions is supported by a Principal Component Analysis. Models are evaluated in terms of in-sample and out-of-sample data fitting as well as stability of parameter estimates. The results are analyzed mainly focusing on the capability of fitting the market implied volatility curve and, in particular, of reproducing its characteristic humped shape.
Consistent Calibration of HJM Models to Implied Volatilities
ANGELINI, Flavio;
2005
Abstract
This paper proposes a calibration algorithm that fits multi-factor Gaussian models to the implied volatilities of caps using the respective minimal consistent family to infer the forward rate curve. The algorithm is applied to three forward rate volatility structures and their combination to form two-factor models. The efficiency of the consistent calibration is evaluated through comparisons with non-consistent methods. The selection of the number of factors and of the volatility functions is supported by a Principal Component Analysis. Models are evaluated in terms of in-sample and out-of-sample data fitting as well as stability of parameter estimates. The results are analyzed mainly focusing on the capability of fitting the market implied volatility curve and, in particular, of reproducing its characteristic humped shape.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
