dc.contributor.author | Golda-Larissa, Akolo | |
dc.date.accessioned | 2013-09-27T08:09:55Z | |
dc.date.available | 2013-09-27T08:09:55Z | |
dc.date.issued | 2009-08 | |
dc.identifier.citation | Akolo-Larissa,G.,October,2009.Analysis of financial risk using extreme value theory. | en |
dc.identifier.uri | http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/57053 | |
dc.description.abstract | Financial Risk management is about understanding large movements in the
financial market. This study examines the modeling of extreme financial
data using the methods of Extreme Value Theory. The two models are fitted
to the NSE 20 Share Index and it emerges that the Peaks Over Threshold
model gives a better fit to the data as opposed to the Block Maxima Model.
The maximum likelihood method has been used to estimate the parameters
of the extreme value models. The Extreme Value Theory based quantiles are
used to estimate the Value-at-Risk,Expected shortfall and the Return level
for the the data.
Key words: Extreme Value Theory, Generalized Extreme Value, Block
Maxima Model, Generalized Pareto Distribution,Peaks Over Threshold Model,
Value-at Risk,Expected shortfall. | en |
dc.language.iso | en | en |
dc.publisher | University of Nairobi | en |
dc.title | Analysis of financial risk using extreme value theory | en |
dc.type | Thesis | en |
local.publisher | College of Biological and Physical Sciences | en |