We present a detailed methodological study of the application of the modified profile likelihood method for the calibration of nonlinear financial models characterised by a large number of parameters. We apply the general approach to the Log-Periodic Power Law Singularity (LPPLS) model of...

A family of threshold nonlinear generalised autoregressive conditionally heteroscedastic models is considered, that allows smooth transitions between regimes, capturing size asymmetry via an exponential smooth transition function. A Bayesian approach is taken and an efficient adaptive sampling...

This paper studies the statistical properties of a two-step conditional quantile estimator in nonlinear time series models with unspecified error distribution. The asymptotic distribution of the quasi-maximum likelihood estimators and the filtered empirical percentiles is derived. Three...

The reaction coefficients in the forecast-based monetary policy reaction function are only weakly identified when the smoothing coefficient for the nominal interest rate is close to unity. This situation also causes the nominal interest rate to be highly persistent. Inference based on the...

This paper presents simulation results on the robustness of normal parametric inference in non-linear mixed models. A linearization approach to inference is compared with two two-stage methods (standard two-stage, STS, and global two-stage, GTS). When the assumptions of normality of the...