Fourier series method for measurement of multivariate volatilities View Full Text


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Article Info

DATE

2002-01

AUTHORS

Paul Malliavin, Maria Elvira Mancino

ABSTRACT

We present a methodology based on Fourier series analysis to compute time series volatility when the data are observations of a semimartingale. The procedure is not based on the Wiener theorem for the quadratic variation, but on the computation of the Fourier coefficients of the process and therefore it relies on the integration of the time series rather than on its differentiation. The method is fully model free and nonparametric. These features make the method well suited for financial market applications, and in particular for the analysis of high frequency time series and for the computation of cross volatilities. More... »

PAGES

49-61

Journal

TITLE

Finance and Stochastics

ISSUE

1

VOLUME

6

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s780-002-8400-6

DOI

http://dx.doi.org/10.1007/s780-002-8400-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009105692


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