Exchange Rate Risk Measurement of Kenyan Commercial Banks by Integrating Value-At-Risk and Extreme Value Theory

Exchange rate risk is a critical concern for financial institutions particularly in emerging markets like Kenya where currency volatility poses significant challenges to economic stability. Kenyan commercial banks operate in an environment heavily influenced by fluctuations in the Kenyan Shilling (KSH) against the US Dollar (USD) facing considerable risks that disrupt financial planning, profitability and overall market stability. The increasing volatility in exchange rates driven by global economic uncertainties and domestic macroeconomic pressures has amplified the need for robust and reliable frameworks to as sess and manage this risk. Traditional Value-at-Risk (VaR) methods such as Historical Simulation and Monte Carlo Simulation are widely employed to measure potential losses from adverse exchange rate movements yet these models often fail to adequately capture extreme market conditions leaving institutions exposed to rare but severe events. This gap underscores the importance of integrating advanced statistical techniques to improve the precision and reliability of risk assessment frameworks. The primary objective of this study was to measure the exchange rate risk of Kenyan commercial banks by integrating Value-at-Risk (VaR) methods with Extreme Value Theory (EVT). Specifically, the study measured exchange rate risk using VaR methods namely Monte Carlo Simulation and Historical Simulation and integrated EVT particularly the Generalized Pareto Distribution (GPD) into the VaR framework to capture the likelihood and magnitude of extreme currency fluctuations. The final objective was to verify the validity of the integrated VaR EVT model through rigorous backtesting. To achieve these objectives, the study employed a quantitative research methodology focusing on the KSH/USD exchange rate from 2019 to 2023. Secondary data from Kenyan commercial banks and financial reports provided the basis for analysis. VaR methods were used to quantify potential losses under normal market conditions while EVT was incorporated to model extreme events that fell outside traditional VaR assumptions. The reliability and accuracy of the combined VaR-EVT framework were assessed using backtesting procedures ensuring robust risk estimates. This research offers a comprehensive and structured approach to assessing exchange rate risk addressing critical limitations in existing methodologies. By integrating EVT into the VaR framework, the study enhances the ability of financial institutions to anticipate and manage the impact of extreme exchange rate events. The findings provide valuable insights for risk managers, financial analysts and policymakers in Kenya equipping them with advanced tools to mitigate exchange rate risk and strengthen the financial stability of the commercial banking sector. This research contributes to academic literature by advancing methodologies for financial risk management, particularly in the context of emerging markets where extreme currency fluctuations are increasingly prevalent.