versione breve 
The development of financial econometrics as a field of research has
been shaped by the availability of highfrequency data on any traded asset price over the past one and a half decades. Due to this development in data availability, a considerable amount of progress has been made in the estimation of realized variance as a measure of financial volatility as well as in the area of providing accurate forecasts of volatility based on these measures. To a much lesser extent, the literature has been asking which economic forces are at play in the dynamics of realized variance, how realized (co)variances interact across different markets and asset classes, how the parameters of the proposed models evolve over time, and what implications realized variance has for asset and derivatives pricing. The project "Analysis and models of cross asset dependency structures in highfrequency data" contributes to the literature on realized variance by filling these gaps. For practical purposes, we structure the project into two subprojects. In subproject one, we explore adaptive modeling techniques for realized variance measures at the univariate and the multivariate level. Emphasis is on parameter flexibility specified within a timevarying Bayesian statespace model representation. This allows us to capture alternating lag and weight structures and also macroeconomic risk factors that drive the evolution of the economy. The second project focuses on the question whether realized variance measures obtained from derivatives and underlying markets can be reconciled under the assumptions of standard option pricing models. Moreover, what assumptions are needed in these models and how do intraday jumps in the underlying process propagate to the derivatives market. Lastly, we seek to combine the insights gained from the two subprojects by developing sophisticated riskmanagement tools and flexible option pricing models based on information embodied in highfrequency data and the flexible models fitted to it. 
parole chiave 
Realized covariance, realized volatility, timevarying parameter models, forecasting, Bayesian variable selection, option pricing 
partner 

tipo  progetto di ricerca applicata 
status  corrente 
inizio progetto  2012 
fine progetto  2015 
informations additionelles 

argomenti 
Financial Econometrics; Realized volatility; Option pricing 
metodi 
Financial Econometrics 
profile area  SEPS  Quantitative Economic Methods 
contatto  Matthias Fengler 