This paper features an analysis of major currency exchange rate movements in relation to the US dollar, as constituted in US dollar terms. Euro, British pound, Chinese yuan, and Japanese yen are modelled using a variety of non-linear models, including smooth transition regression models,...

A growing number of empirical studies provides evidence that dynamic properties of macroeconomic time series have been changing over time. Model-based procedures for the measurement of business cycles should therefore allow model parameters to adapt over time. In this paper the time dependencies...

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modelling and Management” (RMM2011). The papers cover the following topics: currency hedging...

The purpose of this paper is to examine the asymmetric relationship betweenprice and implied volatility and the associated extreme quantile dependence usinglinear and non linear quantile regression approach. Our goal in this paper is todemonstrate that the relationship between the volatility and...

In this paper we document that realized variation measures constructed from highfrequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even...

This paper features an analysis of the relationship between the S&P 500 Index and the VIX using daily data obtained from both the CBOE website and SIRCA (The Securities Industry Research Centre of the Asia Pacific). We explore the relationship between the S&P 500 daily continuously compounded...

This paper features an analysis of the cointegration relationships among agricultural commodity, ethanol and Cushing crude oil spot and futures prices. The use of grains for the creation of bio-fuels has sparked fears that these demands are inflating food prices. We analyse approximately 10...

We characterize the dynamic properties of Generalized Autoregressive Score (GAS) processes by identifying regions of the parameter space that imply stationarity and ergodicity. We show how these regions are affected by the choice of parameterization and scaling, which are key features of GAS...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...