Abstract

The Foreign Exchange Market in developing countries, Kenya being one of them is a key driving force for the development of a country economic growth. In the last decade, world financial markets have been characterized by significant instabilities and the currency exchange rate market is not an exception. As a consequence of the significant instabilities in the financial markets, this paper models the tail risk associated with the Kenya Shilling against the leading currencies, especially the one day ahead Value-at-Risk forecast in risk control, by using the two leading alternatives, the two-stage GARCH-EVT approach and the asymmetry GARCH models. In practice by applying the conditional Extreme Value Theory, the tail behaviour of the daily returns is modelled and thus the VaR while by using the asymmetry GARCH models, one models the whole distribution of the returns and thereafter estimates the Value at Risk. In addition to modelling the value at risk, we further examine the performance of the two leading alternatives with the daily log returns of leading currencies in the Kenyan Foreign Exchange market (US dollar, Sterling Pound and Euro) foreign currencies from the period January 2005 – August 2017 for trading days excluding weekends and holidays. The backtesting result indicate that the conditional Extreme Value Theory does not completely dominate the asymmetry GARCH models in estimating the VaR especially in the Sterling Pound and Euro Exchange Rates.

Highlights

  • The value of one country’s currency converted in terms of the currency of another country is defined as the exchange rate

  • A major problem has risen in the past of how to measure and quantify risks especially in financial markets

  • To evaluate the Value-at-Risk estimates produced by asymmetry GARCH forecasts and GARCH-EVT was the main objective of this paper

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Summary

Introduction

The value of one country’s currency converted in terms of the currency of another country is defined as the exchange rate. Financial markets worldwide have proved to be very turbulent. A major problem has risen in the past of how to measure and quantify risks especially in financial markets. Value-at-Risk (VaR) has been the popular measure of risks because of its simplicity among the risk measures available. Since the problem of quantifying the risk existed, the VaR as a method for measuring risk was put into practice and proposed in details by [1]. The worst loss that can occur over a given period of time in a given level of confidence is defined as Value-at-Risk according to [2]

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