Workshop: Advanced Modeling in Finance and Insurance
Time: Tue, September 23, 2008, 15:00-15:50
Speaker: Jeannette Woerner
Abstract
In the framework of high frequency data the estimating problem of volatility
has recently received much attention. Empirical studies have shown that
tick-by-tick data does not behave like the theory for Brownian motion based
stochastic volatility models suggest. As a way to explain these empirical
findings the concept of market microstructure has been introduced, which means
that a noise term, i.e. a sequence of random variables, mostly assumed to be
iid, is added.
However, when analyzing the fine structure and the correlation structure of
high frequency data fractional Brownian motion based models seem to explain
the empirical findings more realistically. We apply our results to Daimler
Chrysler and Infineon tick-by-tick data and show the implications of our
results to volatility estimates.
Presentation slides (pdf, 1.7 MB)
URL: www.ricam.oeaw.ac.at/specsem/sef/events/program/presentation.php
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