This study is applied in nature and aims to generate new knowledge regarding financial market performance analysis within the Iranian economy, utilizing a scientific framework based on economic time-series data. The primary objective is to analyze the impact of economic uncertainty and government responses on financial market performance during the coronavirus pandemic—while accounting for prevailing market regimes—using data from the Iranian economy spanning the period from Dey 1398 to Dey 1401 (January 2020 to January 2023). To achieve the research objectives, the MIDAS regression approach and a hybrid Markov-Switching MIDAS model were employed. By combining the advantages of these two advanced models, this method enables complex analyses involving data of varying frequencies. The statistical population consists of a set of macroeconomic variables influencing the Iranian financial market that are capable of explaining the dynamics associated with the COVID-19 pandemic. The statistical sample comprises time-series data for these variables across two different frequencies (daily and monthly), selected to fully cover the coronavirus pandemic period (Dey 1398 to Dey 1401). Key findings indicate that: firstly, the impact of these variables on market performance is heavily dependent on the prevailing market regime, and a uniform, linear effect cannot be assumed for the entire period. Secondly, government responses and economic support measures—while potentially sources of volatility under normal conditions—play a stabilizing and calming role at the peak of a crisis and during periods of market tension. Thirdly, the COVID-19 growth rate exhibits dual behavior: it reduces returns in calm markets but is associated with positive returns in volatile markets. Fourthly, volatility displays different characteristics across time horizons (3-day versus 5-day), with 5-day volatility proving more persistent and exhibiting greater inertia.