Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/85480
Authors: 
Caserta, Silvia
Danielsson, Jon
de Vries, Casper G.
Year of Publication: 
1998
Series/Report no.: 
Tinbergen Institute Discussion Paper 98-107/2
Abstract: 
Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and compares favourably with the conventionalfinance normal distribution based approach. It is shown that theefficiency of the estimator of the extreme returns may benefit fromhigh frequency data. Empirical tail shapes are calculated for theGerman Mark-US Dollar foreign exchange rate, and we use the semi-parametric tail estimates in combination with the empiricaldistribution function to evaluate the returns on exotic options.
Subjects: 
Extreme value theory
tail estimation
high frequency data
exotic options
Document Type: 
Working Paper

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