Resource title

Measuring and modeling risk using high-frequency data

Resource image

image for OpenScout resource :: Measuring and modeling risk using high-frequency data

Resource description

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management.The recent availability of high-frequency data allows for refined methods in this field.In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns.In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures af systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorpration and the DJIA index.

Resource author

Wolfgang Karl Härdle, Nikolaus Hautsch, Uta Pigorsch

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/25285

Resource license

Adapt according to the presented license agreement and reference the original author.