Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models
Miguel Ataurima Arellano () and
Gabriel Rodríguez ()
The North American Journal of Economics and Finance, 2020, vol. 52, issue C
Using weekly data for stock and Forex market returns, a set of MS-GARCH models is estimated for a group of high-income (HI) countries and emerging market economies (EMEs) using algorithms proposed by Augustyniak (2014) and Ardia et al. (2018, 2019a,b), allowing for a variety of conditional variance and distribution specifications. The main results are: (i) the models selected using Ardia et al. (2018) have a better fit than those estimated by Augustyniak (2014), contain skewed distributions, and often require that the main coefficients be different in each regime; (ii) in Latam Forex markets, estimates of the heavy-tail parameter are smaller than in HI Forex and all stock markets; (iii) the persistence of the high-volatility regime is considerable and more evident in stock markets (especially in Latam EMEs); (iv) in (HI and Latam) stock markets, a single-regime GJR model (leverage effects) with skewed distributions is selected; but when using MS models, virtually no MS-GJR models are selected. However, this does not happen in Forex markets, where leverage effects are not found either in single-regime or MS-GARCH models.
Keywords: MS-GARCH models; GARCH models; Returns; Volatility; Latin American countries; High-income countries; Stock; Forex (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940820300607
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