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...

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This exciting volume presents cutting-edge developments in high frequency financial econometrics, spanning a diverse range of topics: market microstructure, tick-by-tick data, bond and foreign exchange markets and large dimensional volatility modelling. The chapters on market microstructure deal...

We introduce TailCoR, a new measure for tail correlation that is a function of linear and non–linear correlations, the latter characterized by the tail index. TailCoR can be exploited in a number of financial applications, such as portfolio selection where the investor faces risks of a linear...

We establish the asymptotic normality of marginal sample quantiles for S-mixing vector stationary processes. S-mixing is a recently introduced and widely applicable notion of dependence. Results of some Monte Carlo simulations are given ; Establecemos la normalidad asintótica de cuantiles...

The asymptotic efficiency of indirect estimation methods, such as the efficient method of moments and indirect inference, depends on the choice of the auxiliary model. To date, this choice has been somewhat ad hoc and based on an educated guess. In this article we introduce a class of...

Realized volatilities, when observed over time, share the following stylised facts: comovements, clustering, long-memory, dynamic volatility, skewness and heavy-tails. We propose a dynamic factor model that captures these stylised facts and that can be applied to vast panels of volatilities as...