A method capable of estimating richly parametrized versions of the dynamic conditional correlation (DCC) model that go beyond the standard scalar case is presented. The algorithm is based on the maximization of a Gaussian quasi-likelihood using a Bregman-proximal trust-region method that handles...

The recent widespread availability of intraday tick-by-tick databases for stocks, options and currencies has had an important impact on research in applied financial econometrics and market microstructure. Econometric Modelling of Stock Market Intraday Activity focuses on the econometric...

We build on two contributions that have found conditions for large dimensional networks or systems to generate long memory in their individual components, and provide a multivariate methodology for modeling and forecasting series displaying long range dependence. We model long memory properties...

In this chapter written for a forthcoming Handbook of Financial Time Series to be published by Springer-Verlag, we review the econometric literature on dynamic duration and intensity processes applied to high frequency financial data, which was boosted by the work of Engle and Russell (1997) on...

The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and...

We design and implement optimal foreign exchange portfolio allocations. An optimal allocation maximizes the expected return subject to a Value-at-Risk (VaR) constraint. Based on intradaily data, the optimization procedure is carried out at regular time intervals. For the estimation of the...