Author(s)

Katu Daniel Edem^1*, Marcel Ndengo²

¹African Institute for Mathematical Sciences (AIMS), Kigali, Rwanda.
²Department of Natural Sciences, College of Arts and Sciences, William V.S. Tubman University, Harper, Liberia.

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.

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

Edem, K. and Ndengo, M. (2021) Modeling Bank of Kigali Stock Risks in Rwanda Stock Exchange Using Extreme Value Distribution. Journal of Financial Risk Management, 10, 225-240. doi: 10.4236/jfrm.2021.103013.