Comparison and Forecasting of Value-at-Risk (VaR) Models for Financial Risk Measurement: Evidence from Iran’s Foreign Exchange Market (2019–2025)
Keywords:
Value at Risk (VaR), GARCH model, generalized error distribution (GED), Kupiec test, exchange-rate risk, Iran’s unofficial foreign exchange marketAbstract
With the increasing prevalence of tail risks in financial markets, Value at Risk (VaR) has become a widely used risk measurement tool because of its simplicity of calculation and interpretation. This study aims to compare the performance of five VaR models: the conventional VaR model, RiskMetrics, GARCH-N, GARCH-t, and GARCH-GED. For this purpose, daily price data for the US dollar in Iran’s unofficial (free) foreign exchange market were collected for the period from April 2019 to April 2025, comprising approximately 2,500 trading days. The full sample was divided into a training subsample covering the first five years and a testing subsample covering the final two years, and daily risk was estimated using a rolling-window approach. The backtesting results at the 95% and 99% confidence levels indicate that, except for the RiskMetrics model, all models pass the Kupiec test at the 95% confidence level. At the 99% confidence level, and based on the ideal failure rate, only the GARCH-GED model passes the test. Overall, the GARCH-GED model exhibits the lowest forecast failure rate among the GARCH-family models. These findings are particularly significant in light of the historic exchange-rate surges recorded in 2025, when the exchange rate exceeded 1.3 million Iranian rials per US dollar.
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Copyright (c) 2025 Masoud Tahouneh (Author); Khadijeh Khodabakhshi Parijan
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