Stochastic volatility and time-varying country risk in emerging markets
Anders Johansson ()
The European Journal of Finance, 2009, vol. 15, issue 3, 337-363
This study suggests an alternative method to estimate time-varying country risk. We first apply a new multivariate stochastic volatility (SV) model to a set of emerging stock markets. To estimate the SV model, we use a Bayesian Markov chain Monte Carlo simulation procedure. By applying the deviance information criterion, we show that the new model performs well relative to alternative multivariate SV models. We then compute the conditional betas for the different markets and compare the results with an often-used procedure based on multivariate GARCH models. We show that the new multivariate SV model more accurately captures the time-varying nature of country risk. The conditional betas show signs of large variations, indicating the importance of taking time-varying country risk into consideration when managing emerging market portfolios.
Keywords: conditional beta; multivariate stochastic volatility; Markov chain Monte Carlo; emerging markets (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:eurjfi:v:15:y:2009:i:3:p:337-363
Ordering information: This journal article can be ordered from
Access Statistics for this article
The European Journal of Finance is currently edited by Chris Adcock
More articles in The European Journal of Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().