A Methodological Approach to Calculating Exchange Rate Volatility: A Competition among GARCH, FIGARCH, Fourier-GARCH, and Semi-Parametric Rational Inattention Frameworks

Document Type : RESEARCH PAPER

Authors

1 Assistant Professor,The Center for Development Research and Foresight, Tehran, Iran.

2 Department of Agricultural Economics, Faculty of Economics and Agricultural Development, University of Tehran, Karaj, Iran

3 , Associate Professor, Department of Agricultural Economics, Faculty of Economics and Agricultural Development, University of Tehran, Karaj, Iran

10.22111/sedj.2026.55538.1706

Abstract

Exchange rate volatility in Iran, driven by an import-oriented economic structure, dependence on oil revenues, and sanction-induced shocks, is considered one of the primary sources of macroeconomic instability and systematic risk. Despite the extensive body of prior research, few studies have simultaneously compared approaches based on long memory (FIGARCH), control for structural breaks (Fourier-GARCH), and agents’ behavioral constraints (the semi-parametric Rational Inattention model). This study aims to identify the most accurate analytical framework for calculating exchange rate volatility in Iran over the period from March 1992 to December 2025 by comparing the performance of four models: GARCH, FIGARCH, Fourier-GARCH, and the Rational Inattention model, using monthly exchange rate return data. After confirming the stationarity of the variables, the baseline GARCH(1,2) model was selected, and competing models were estimated. Performance evaluation in the out-of-sample period using RMSE, MAE, and MSE metrics indicated that the Rational Inattention model achieved the best forecasting performance, with the lowest error rates. The FIGARCH model confirmed the presence of long memory (with a fractional integration parameter d = 0.648; however, the Nyblom stability test revealed that these parameters are unstable over time. The Fourier-GARCH model also demonstrated better performance than the simple GARCH model, validating the role of structural breaks. The main finding of this study is that the root cause of exchange rate volatility persistence in Iran is less a fixed statistical feature (inherent long memory) and more a result of rational inattention, limited information processing capacity, and asymmetric agent responses to positive and negative news. The high speed of information processing (φ = 0.235) and the negative value of the Directional Volatility Ratio (DVR) index indicate a competitive market with rapid expectation adjustments. Given the superiority of the rational inattention model in forecasting exchange rate volatility, it is recommended that monetary policymakers incorporate market expectations and the behavior of market participants—alongside macroeconomic variables—into their currency analyses and decision-making processes. Furthermore, considering the significant role of structural breaks, the design of exchange rate policies should be accompanied by transparent communication and the management of market expectations. 

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References

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