Effects of estimation techniques on generalised extreme value distribution (GEVD) parameters and their spatio-temporal variations

2021 ◽  
Author(s):  
Iqbal Hossain ◽  
Monzur A. Imteaz ◽  
Anirban Khastagir
Keyword(s):  
Extreme Value Distribution ◽  
Temporal Variations ◽  
Extreme Value ◽  
Value Distribution ◽  
Estimation Techniques ◽  
Generalised Extreme Value Distribution ◽  
Spatio Temporal

scholarly journals Analysing Extreme Risk in the South African Financial Index (J580) using the Generalised Extreme Value Distribution

2020 ◽  
Vol 8 (4) ◽  
pp. 915-933
Author(s):  
Delson Chikobvu ◽  
Owen Jakata
Keyword(s):  
South African ◽  
Extreme Value Distribution ◽  
Value Theory ◽  
Extreme Value ◽  
Value Distribution ◽  
The South ◽  
Extreme Risk ◽  
Generalised Extreme Value Distribution ◽  
Financial Index ◽  
Block Maxima

The aim of this study is to model the probabilistic behaviour of unusually large financial losses (extreme-risk)and gains of the South African Financial Index (J580). Risk is defined as uncertainty in return in this paper. This study makes use of Extreme Value Theory (EVT) for the period years: 1995-2018 to build models that are used to estimate extreme losses and gains. The quarterly block maxima/minima of monthly returns are tted to the Generalised Extreme Value Distribution (GEVD). Return levels (maximum loss/gain) based on the parameters from the GEVD are estimated. A comparative analysis with the Generalised Pareto Distribution (GPD) is carried out. The study reveals that EVT provides an efficient method of forecasting potentially high risks in advance. The conclusion is that analysing extreme risk in the South African Financial Index helps investors understand its riskness better and manage to reduce the risk exposure in this portfolio.

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