GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks in the volatility process. Flexible alternatives are Markov-switching GARCH and change-point GARCH models. They require estimation by MCMC methods due to the path dependence problem. An unsolved...

We propose and illustrate a Markov-switching multi-fractal duration (MSMD) model for analysis of inter-trade durations in financial markets. We establish several of its key properties with emphasis on high persistence (indeed long memory). Empirical exploration suggests MSMD's superiority...

The paper compares one-period ahead forecasting performance of linear vector-autoregressive (VAR) models and single-equation Markov-switching (MS) models for two cases: when leading information is available and when it is not. The results show that single-equation MS models tend to perform...

Business cycle indicators are used to assess the economic situation of countries or regions. They are closely watched by the public, but are not easy to interpret. Does a current movement of the indicator signal a turning point or not? With the help of Markov Switching Models movements of...

The study proposes and a family of regime switching GARCH neural network models to model volatility. The proposed MS-ARMA-GARCH-NN models allow MS type regime switching in both the conditional mean and conditional variance for time series and further augmented with artificial neural networks to...

This paper investigates the dynamics of hedge fund returns and their behavior of persistence in a unified framework through the Markov Switching ARFIMA model of Härdle and Tsay (2009). Major results based on the CSFB/Tremont hedge fund indexes monthly data during the period 1994-2011, highlight...

The Hidden Markov Model (HMM) has been widely used in regime classification and turning point detection for econometric series after the decisive paper by Hamilton (1989). The present paper will show that when using HMM to detect the turning point in cyclical series, the accuracy of the...

We describe stationarity and ergodicity (SE) regions for a recently proposed class of score driven dynamic correlation models. These models have important applications in empirical work. The regions are derived from sufficiency conditions in Bougerol (1993) and take a non-standard form. We show...

This paper extends the evolution equation of Patton (2006) for the time variation of the copula parameters by specifying an autoregressive fractionally integrated term. For any copula parameter there is a suitable one-to-one transformation so that the maximum likelihood estimation method may be...

We extend the Markov-switching dynamic factor model to account for some of the specifi cities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as ragged edges and mixed frequencies. We examine the theoretical benefi ts of this extension and corroborate...