In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily and weekly … data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a new … result is that we find spurious GARCH in over 50% of the cases. Using Monte Carlo simulations, in which we evaluate our …

- Maximum Likelihood Estimator for a general nonlinear conditional mean model with first-order GARCH errors. …

ARMA(1,1)-GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility. Moreover, 1998 is a turning …

Carlo methods. The effects of several model characteristics (unit roots, GARCH, stochastic volatility, heavy tailed …

methods. The effects of several model characteristics (unit roots, GARCH, stochastic volatility, heavy tailed disturbance …

The GARCH model and the Stochastic Volatility [SV] model are competing but non-nested models to describe unobserved … volatility in asset returns. We propose a GARCH model with an additional error term, which can capture SV model properties, and … which can be used to test GARCH against SV. We discuss model representation, parameter estimation and a simple test for …

parsimony and robustness. APS is applied within a Bayesian analysis of a GARCH-mixture model which is used for the evaluation of …

the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for Korean tourist arrivals to Taiwan and the Korean Won / New Taiwan …

conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for world, US and Japanese tourist …