This dissertation consists of three stand-alone research papers, all of which treat the topic of estimation and dynamic modelling of multivariate volatility by employing the information contained in high-frequency data, which became available in the last 10 - 15 years. The main focus of all...

Quantification techniques are popular methods in empirical research for aggregating the qualitative predictions at the microlevel into a single figure. In this paper, we analyze the forecasting performance of various methods that are based on the qualitative predictions of financial experts for...

In this paper we propose a model for the conditional multivariate density of integer count variables defined on the set Zn. Applying the concept of copula functions, we allow for a general form of dependence between the marginal processes, which is able to pick up the complex nonlinear dynamics...

In recent years high-frequency finance has become one of the most active research fields in finance and economics. The wide-spread availability of high-frequency datasets has particularly spurred research within this field and has, in turn, given birth to the rapidly expanding bridge between...

We explore the information content of counterparty identities and how their disclosure can be exploited by other investors in a post-trade transparent market. Using data from the Helsinki Stock Exchange, we form dynamic mean-variance strategies with daily rebalancing which condition on the net...