Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/269949 
Year of Publication: 
2020
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 8 [Issue:] 1 [Article No.:] 1802806 [Year:] 2020 [Pages:] 1-49
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
We employ the Markov Regime-Switching GARCH (MRS- GARCH) family models under the normal, Student's t-, and GED distributions to measure the uncertainty of the industry index returns (IIR) of Tehran Stock Exchange over the period of 2013-2019. The models distinguish between two different regimes in both conditional mean and conditional variance. The results show that the MRS-EGARCH-in-mean (MRS-EGARCH-M) models under GED and Student's t-distributions have the best performance to model the IIR volatility. We find evidence of regime-switching behaviour in Iran's stock market. After removing the forecastable component (expected variation) from the best fitted models, we measure the time series of the IIR uncertainty (unforecastable component) and estimate the impact of exchange rate fluctuations on them using an autoregressive distributed lag (ARDL) model. We find that foreign exchange rate fluctuations have a significant and distinct impact on the IIR uncertainty across various regimes. The results show that the exchange rate generally has a negative and positive impact on the IIR uncertainty for export and import-oriented industries, respectively, under both regimes.
Subjects: 
Markov regime-switching
stock market
uncertainty
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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