In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

Structural breaks in GARCH processes do matter for applications and model-based inference. To show this, I first propose a new approach to estimate change-point GARCH models with maximum likelihood, for which no method exists so far. Practical implementation of the proposed algorithm is...

While it is widely agreed that Purchasing Power Parity (PPP) holds as a long-run concept the specific dynamic driving the process is largely build upon a priori economic belief rather than a thorough statistical modeling procedure. The two prevailing time series models, i.e. the exponential...

In this paper, we consider and examine the performance of two-step LM unit root tests with trend-breaks. In the first step, we jointly test for the existence and location of breaks using a maximum F-test. In the second step, we utilize the identified breaks and test for a unit root. A...

We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent...

Daily returns of financial assets are frequently found to exhibit positive autocorrelation at lag 1. When specifying a linear AR(l) conditional mean, one may ask how this predictability affects option prices. We investigate the dependence of option prices on autoregressive dynamics under...

We make use in this article of a testing procedure suggested by Robinson (1994) for testing deterministic seasonality versus seasonal fractional integration. A new test statistic is developed to simultaneously test both, the order of integration of the seasonal component and the need of seasonal...

Spatial/Spatiotemporal interdependence - i.e., that the outcomes, actions, or choices of some unit-times depend on those of others - is substantively and theoretically ubiquitous and central in binary outcomes of interest across the social sciences. However, most empirical applications omit...

A new version of the local scale model of Shephard (1994) is presented. Its features are identically distributed evolution equation disturbances, the incorporation of in-the-mean effects, and the incorporation of variance regressors. A Bayesian posterior simulator and a new simulation smoother...

We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and their forecasting performance of the conditional variance in an out-of-sample setting. Exponential GARCH model of Nelson (1991) with “constant mean, t-distribution, one lag...