When observed over a large panel, measures of risk (such as realized volatilities) usually exhibit a secular trend around which individual risks cluster. In this article we propose a vector Multiplicative Error Model achieving a decomposition of each risk measure into a common systematic and an...

We analyze several measures of volatility (realized variance, bipower variation and squared daily returns) as estimators of integrated variance of a continuous time stochastic process for an asset price. We use a Multiplicative Error Model to describe the evolution of each measure as the product...

Financial market price formation and exchange activity can be investigated by means of ultra-high frequency data. In this paper we investigate an extension of the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998) by adopting a mixture of distribution approach with time...

This paper is concerned with the issues of modeling and projecting the dynamics of volatility when a group of potentially useful predetermined variables is available. We predict realized volatility and value at risk (VaR) with a nested set of multiplicative error models for realized volatility....

In financial time series analysis we encounter several instances of non negative valued processes (volumes, trades, durations, realized volatility, daily range, and so on) which exhibit clustering and can be modeled as the product of a vector of conditionally autoregressive scale factors and a...

Many ways exist to measure and model financial asset volatility. In principle, as the frequency of the data increases, the quality of forecasts should improve. Yet, there is no consensus about a acirc;not;Strueacirc;not;? or quot;bestquot; measure of volatility. In this paper we propose to jointly...

The Multiplicative Error Model introduced by Engle (2002) for positive valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multivariate extension of such a model, by taking into...

Transmission mechanisms in financial markets reflect the degree of integration of capital markets and of real economies. As a matter of fact, volatility has components which may behave differently across quiet and turbulent periods, but appear to behave in similar ways from market to market. In...

Transmission mechanisms in financial markets reflect the degree of integrationof capital markets, as well as the relative importance of real economies. Market volatility has components which may behave differently across quiet and turbulent periods, but appear to behave in similar ways from...

The financial econometrics literature on Ultra High-Frequency Data (UHFD)has been growing steadily in recent years. However, it is not always straightforward to construct time series of interest from the raw data and the consequences of data handling procedures on the subsequent statistical...