Examining the impact of exchange rate uncertainty on the Tehran Stock Exchange Index: hybrid approach using wavelet transform and quantile regression model

This study examines the impact of exchange rate uncertainty on the Tehran Stock Exchange (TSE) index, addressing the critical role of currency volatility in Iran’s sanction-constrained economy. Motivated by the need to understand non-linear market dynamics, it aims to analyze scale-specific and quantile-based effects of USD/IRR fluctuations from 2010 to 2024. Employing a hybrid quantile wavelet model, integrating discrete wavelet transform (DWT) with maximum overlap multi-resolution analysis (MOMRA) and quantile regression, the study reveals a positive and significant impact of exchange rate uncertainty across all time scales, with stronger effects in lower quantiles. These findings offer practical strategies for investors to optimize portfolios by targeting export-oriented firms and for policymakers to design stabilization measures, contributing a novel multi-scale framework to financial analysis in emerging markets. This study aims to analyze the multi-scale and quantile-specific effects of exchange rate uncertainty on the TSE index, contributing novel insights into Iran's financial dynamics by integrating wavelet transforms with quantile regression, surpassing traditional models in capturing non-linear relationships and offering practical strategies for investors and policymakers amid currency volatility.