The Predictive Power of Financial Stress on the Financial Markets Dynamics: Hidden Markov Model

Hayet Soltani () and Mouna Boujelbène Abbes ()
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Hayet Soltani: University of Sfax
Mouna Boujelbène Abbes: University of Sfax

Journal of Economics and Finance, 2023, vol. 47, issue 1, No 5, 94-115

Abstract: Abstract This study investigates the predictive power of the financial stress on the dynamic of the Middle East and North Africa (MENA) financial market returns from 2007 to 2021. Based on a Quantile Regression, we show that financial stress has highest predictive abilities at the lower quantiles when the market is bearish. Then, we propose a Hidden Markov Model (HMM) based on the transition matrix to understand the relationship between financial stress index and the MENA stock market dynamics. We find that the effect of financial stress on stock market return reveals the persistence of regimes: Bullish state exists and persists, and has the longest conditional expected duration for the majority of MENA markets, except Bahrain, Qatar and Jordan. However, the transition probability from the bullish to the calm regime is too low for the financial market of Bahrain, United Arab Emirates and Egypt. Besides, the estimated mean returns for each regime divulge that the bearish and calm states are more attractive destination for both portfolio managers and investors.

Keywords: Financial Stress Index; Hidden Markov Model; Transition Probability Matrix; MENA region; COVID_19 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12197-022-09600-z

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