University of St.Gallen
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Analysis and models of cross asset dependency structures in high-frequency data

Kurzfassung The development of financial econometrics as a field of research has been
shaped by the availability of high-frequency 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 high-frequency 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 time-varying Bayesian
state-space 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 intra-day 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 risk-management tools and flexible option pricing models based on information embodied in high-frequency data and the flexible
models fitted to it.
   
Schlagwörter (Tags) Realized covariance, realized volatility, time-varying parameter models, forecasting, Bayesian variable selection, option pricing
   
Partner
Typ angewandtes Forschungsprojekt
Status laufend
Projektstart 2012
Projektende 2015
Weitere Informationen
Themen Financial Econometrics; Realized volatility; Option pricing
Methoden Financial Econometrics
Profilbereich SEPS - Quantitative volkswirtschaftliche Methoden
Kontakt Matthias Fengler