Provides a comprehensive and updated study of GARCH models and their applications in
finance, covering new developments in the discipline This book provides a comprehensive …

We propose a robust method for constructing conditionally valid prediction intervals based
on models for conditional distributions such as quantile and distribution regression. Our …

This book contains a up-to-date overview of nonlinear time series models and their
application to modelling economic relationships. It considers nonlinear models in stationary …

In this paper, we introduce quantile coherency to measure general dependence structures
emerging in the joint distribution in the frequency domain and argue that this type of …

Invertibility conditions for observation-driven time series models often fail to be guaranteed
in empirical applications. As a result, the asymptotic theory of maximum likelihood and quasi …

Variance targeting estimation (VTE) is a technique used to alleviate the numerical difficulties
encountered in the quasi-maximum likelihood estimation (QMLE) of GARCH models. It relies …

This paper studies the asymptotic properties of the quasi‐maximum likelihood estimator of
(generalized autoregressive conditional heteroscedasticity) GARCH (1, 1) models without …

This paper studies a class of Markov models that consist of two components. Typically, one
of the components is observable and the other is unobservable or “hidden.” Conditions …

In this paper, we present an alternative method for the spectral analysis of a univariate,
strictly stationary time series {Y_t\}_t∈Z. We define a “new” spectrum as the Fourier …

Abstract Since 2016, the Basel Committee on Banking Supervision has regulated banks to
switch from a Value-at-Risk (VaR) to an Expected Shortfall (ES) approach to measuring the …