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Seymour, A. J., & Polakow, D. A. (2003). A Coupling of Extreme-Value Theory and Volatility Updating with Value-at-Risk Estimation in Emerging Markets: A South African Test. Multinational Finance Journal, 7, 3-23.

has been cited by the following article:

• TITLE: Modeling Bank of Kigali Stock Risks in Rwanda Stock Exchange Using Extreme Value Distribution

  AUTHORS: Katu Daniel Edem, Marcel Ndengo

  KEYWORDS: Extreme Value Theory, Generalised Extreme Value Distribution, Block Maxima, Generalised Pareto Distribution, Peak over Threshold, Value at Risk, Expected Shortfall

  JOURNAL NAME: Journal of Financial Risk Management, Vol.10 No.3, August 3, 2021

  ABSTRACT: Extreme Value Theory has come forth as one of the most significant probability theories in applied sciences. Modeling extreme events has always been of interest in many disciplines such as hydrology, insurance, and finance. This study seeks to model the Bank of Kigali’s (BK) stock risks in Rwanda stock exchange using Extreme Value Distribution. Two major approaches are used. To model Bank of Kigali stock risks, the Generalised Extreme Value Distribution (GEVD), precisely the Block Maxima is implemented. To examine its associated exceedances, the Generalised Pareto Distribution (GPD) is also implemented. Risk measures considered are the Value at Risk (VaR) and the Expected Shortfalls (ES). Findings reveal that the Frechet distribution fits reasonably well the distribution of the BK stock returns and GPD the exceedances. Also, the risk measures such as Value at Risk and Expected shortfall were computed with high level (99.5%) quantiles to serve as a guide to investors to make a decision as to whether to invest in Bank of Kigali’s stock or not. The findings show that GPD fits the tail of the data well.