Analysis of financial risk using extreme value theory

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.