This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to ?t them using a BEKK-type parameterization of the...

This paper introduces a new class of multivariate volatility models that utilizes high-frequency data. We discuss the models dynamics and highlight their di¤erences from multivariate GARCH models. We also discuss their covariance targeting specification and provide closed-form formulas for...

I discuss models which allow the local level model, which rationalised exponentially weighted moving averages, to have a time-varying signal/noise ratio. I call this a martingale component model. This makes the rate of discounting of data local. I show how to handle such models effectively using...

Background: There has been extensive discussion of the workings of the English system of higher education income contingent student loans. Major focuses have been on what former students are likely to pay and when, distributional characteristics and how much the Government guarantees made to...

In this paper we obtain a closed form expression for the convergence rate of the Gibbs sampler applied to an AR(1) plus noise model in terms of the parameters of the model. We also provide evidence that a ``centered'' parameterisation of a state space model is preferable for the performance of...

We consider kernel-based estimators of integrated variances in the presence of independent market microstructure effects. We derive the bias and variance properties for all regular kernel-based estimators and derive a lower bound for their asymptotic variance. Further we show that the...

In this paper we provide an asymptotic distribution theory for some non-parametric tests of the hypothesis that asset prices have continuous sample paths. We study the behaviour of the tests using simulated data and see that certain versions of the tests have good finite sample behaviour. We...

In this paper we review some recent work on limit results on realised power variation, that is sums of powers of absolute increments of various semimartingales. A special case of this analysis is realised variance and its probability limit, quadratic variation. Such quantities often appear in...

Stochastic volatility models present a natural way of working with time-varying volatility. However the difficulty involved in estimating these types of models has prevented their wide-spread use in empirical applications. In this paper we exploit Gibbs sampling to provide a likelihood framework...