In recent years there has been an increased interest in the extent to which managers can improve their property portfolio position through international diversification. Much of this interest has centred on the use of various statistical/econometric tests of time-varying correlations and...

Purpose ? To develop an integrated approach to forecasting spot foreign exchange rates by incorporating some principles underlying long-term dependence.Design/methodology/approach ? The paper utilises the random-walk framework to develop a stochastic forecast model wherein the sign (positive or...

An important assumption underlying traditional theories of financial time-series behaviour is that consecutive changes in the price of an asset (ie. asset returns) are independent of each other. For analysts seeking to predict the future value of an asset, this implies that the best step-ahead...

This paper proposes generalisations of the Realized GARCH model by Hansen et al. (2012), in three different directions. First, heteroskedasticity in the noise term in the measurement equation is allowed, since this is generally assumed to be time-varying as a function of an estimator of the...

This paper proposes generalisations of the Realized GARCH model by Hansen et al. (2012), in three different directions. First, heteroskedasticity in the noise term in the measurement equation is allowed, since this is generally assumed to be time-varying as a function of an estimator of the...

This paper proposes generalisations of the Realized GARCH model by Hansen et al. (2012), in three different directions. First, heteroskedasticity in the noise term in the measurement equation is allowed, since this is generally assumed to be time-varying as a function of an estimator of the...

This paper proposes novel approaches to the modeling of attenuation bias effects in volatility forecasting. Our strategy relies on suitable generalizations of the Realized GARCH model by Hansen et al. (2012) where the impact of lagged realized measures on the current conditional variance is...