Sudden shifts in variance in the Spanish market: persistence and spillover effects

Jose Luis Miralles Marcelo, José Miralles Quirós and Maria del Mar Miralles Quiros

Applied Financial Economics, 2007, vol. 18, issue 2, 115-124

Abstract: In this paper we use the Iterated Cumulative Sums of Squares (ICSS) algorithm to detect sudden changes in variance in the Spanish stock Market. However, we employ an alternative methodology based on an EGARCH model to better capture the asymmetric behavior of the stock markets. We also use these sudden shifts to analyze the information spillovers between large and small cap portfolios. The results of this study show a significant decrease in the volatility persistence of both portfolios when sudden changes are taken into account. Spillover effects are also reduced but, in contrast with most of the previous evidence, we find a feedback relationship between the large and small portfolios. In this paper we shed some light on the understanding of the stock market by suggesting a common behavior of the portfolios. This results may be valid for a great number of markets and useful for the building of accurate asset pricing models or forecasting volatilities.

Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100601057862 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apfiec:v:18:y:2007:i:2:p:115-124

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20

DOI: 10.1080/09603100601057862

Access Statistics for this article

Applied Financial Economics is currently edited by Anita Phillips

More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().