Time Variation in Cash Flows and Discount Rates*
Tolga Cenesizoglu and
Denada Ibrushi
Journal of Financial Econometrics, 2023, vol. 21, issue 5, 1557-1589
Abstract:
We analyze the decomposition of the conditional, rather than the unconditional, variance of market returns based on an extension of the standard Campbell–Shiller approach. The relative importance of cash flow and discount rate news in determining the conditional variance of market returns exhibits significant variation over time and relates to economic conditions. The components of the conditional market variance outperform several benchmark variables, including the conditional market variance itself, in forecasting future market returns and realized variance across different horizons. The forecasts based on the conditional market variance components also provide sizable economic benefits compared with benchmark forecasts in an out-of-sample portfolio exercise where a myopic investor allocates her wealth between the market portfolio and a risk-free asset across different holding periods.
Keywords: conditional market variance; multivariate conditional variance models; forecasting; return decomposition (search for similar items in EconPapers)
JEL-codes: C58 G11 G17 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1093/jjfinec/nbac016 (application/pdf)
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:oup:jfinec:v:21:y:2023:i:5:p:1557-1589.
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani
More articles in Journal of Financial Econometrics from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().