Detecting Exchange Rate Bubbles Using Hamilton Filter
This paper develops an adaptive Hamilton-filter framework for detecting speculative bubbles in exchange rate markets. With the reformulation of the traditional bubble-crash model through a binary transformation, the proposed approach expresses bubble dynamics within a nonlinear regime-switching structure and derives recursive estimates of bubble continuation probabilities. Unlike conventional explosive root tests, the method provides real-time, time-varying conditional probabilities of speculative regimes.
The empirical application focuses on the USD - Iranian Rial exchange rate over the period 2000–2020, examining six episodes of heightened volatility. Bubble detection results are compared with ADF, SADF, and GSADF tests, showing that the proposed filter effectively identifies multiple rational bubble episodes consistent with macroeconomic and policy developments. Additional analysis of tradable and non-tradable goods prices suggests that external-sector imbalances significantly contribute to exchange rate explosiveness. Overall, the findings demonstrate that the adaptive Hamilton-filter approach offers a robust and economically interpretable tool for real-time bubble monitoring and exchange rate risk assessment.
© The Author(s) 2026. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.
Article’s history: Received 11th of February, 2026; Revised 24th of March, 2026; Accepted for publication 7th of April, 2026; Available online: 17th of April, 2026; Published as research article in Volume II, Issue 1(3), 2026.
Habibi, R. (2026). Detecting Exchange Rate Bubbles Using Hamilton Filter. Applied Journal of Economics, Law and Governance, Volume II, Issue 1(3), 91-104. https://doi.org/10.57017/ajelg.v2.i1(3).05
CRediT Authorship Contribution Statement: Habibi, R. is only author of paper and is corresponding author and he is responsible for ensuring that the descriptions are accurate.
Conflict of Interest Statement: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments: Author thanks Journal Editor for their valuable helps.
Data Availability Statement: Simulated openly available data: The simulated data that support the findings of this study are openly available and generated in random number generators of R software.
Ethical Approval Statement: The research utilises publicly accessible secondary financial and macroeconomic data and does not involve human subjects, individual-level confidential information, or experimental interventions. Consequently, in accordance with standard academic research guidelines, formal ethical approval was not required.
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