Stochastic volatility and time-varying country risk in emerging markets
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.
Volume (Year): 15 (2009)
Issue (Month): 3 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/REJF20 |
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/REJF20|
When requesting a correction, please mention this item's handle: RePEc:taf:eurjfi:v:15:y:2009:i:3:p:337-363. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.