Regime switching in stock market returns

Huntley Schaller and Simon van Norden ()

Applied Financial Economics, 1997, vol. 7, issue 2, 177-191

Abstract: An extension of Hamilton's Markov switching techniques (Hamilton, J. B., 1989, A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica, 57, 357-84) is used to describe and analyse stock market returns. Using new tests, very strong evidence is found for switching behaviour. A major innovation is to use a multivariate specification that allows examination of whether the price/dividend ratio has marginal predictive power for stock market returns after accounting for state-dependent switching. We find strong evidence of predictability. The response of returns to the past price/dividend ratio is strongly asymmetric - about four times larger in the low-return state than in the high-return state. A second innovationis to allow the probability of transitions from one regime to another to depend on economic variables; again there is an asymmetric response to the past price/dividend ratio.

Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (144)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/096031097333745 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Regime Switching in Stock Market Returns (1995)
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:7:y:1997:i:2:p:177-191

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

DOI: 10.1080/096031097333745

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 ().