Abstract: This study has two main parts, part one consist of highlighting the statistical procedure which can be used to find out the best model among GARCH-family models for modelling the exchange market of Rwanda using the daily exchange rate data for 2038 days since 2010/01/01. Part two consist of modeling residuals extracted from a selected GARCH model using the Generalized Pareto Distribution (GPD) and the Generalized Extreme Values (GEV), then estimate the Value at Risk(VaR) and the Expected Shortfall (ES) from both GPD and GEV models. In the first part, the study employed four models from the family of Generalized Autoregressive Conditional Heteroscedasticity models (GARCH) combined with the mean model ARMA; among which this study chose to estimate ARMA(1,1)-GARCH (1,1), ARMA(1,1)-GJR-GARCH(1,1), ARMA(1,1)-EGARCH(1,1) and ARMA(1,1)-APARCH(1,1,1) and choose the best among them, with a view to approximate the dynamics exchange market volatility.
Keywords: Volatility, GARCH-family models, Extreme value theory, Value at risk, Expected shortfall.
Title: Modeling Exchange Market Volatility Risk in Rwanda Using GARCH-EVT Approach
Author: Rafiki Murenzi, Kigabo Thomas, Joseph K. Mung’atu
International Journal of Thesis Projects and Dissertations (IJTPD)
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