Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility

Annika Lindblad

MPRA Paper from University Library of Munich, Germany

Abstract: I use the GARCH-MIDAS framework of Engle et al. (2013) to examine the relationship between the macro economy and stock market volatility, focusing on the role played by survey-based sentiment indicators compared to macroeconomic variables. I find that once the information in sentiment indicators is controlled for, backward-looking macroeconomic data does not include useful information for predicting stock return volatility. On the other hand, forward-looking macroeconomic variables remain useful for forecasting stock market volatility after sentiment data is taken into account. The term spread is the best predictor for stock return volatility over long horizons.

Keywords: stock market volatility; volatility components; MIDAS; survey data; macro finance link (search for similar items in EconPapers)
JEL-codes: C53 G12 G17 (search for similar items in EconPapers)
Date: 2017-07-19
New Economics Papers: this item is included in nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/80266/1/MPRA_paper_80266.pdf original version (application/pdf)

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:pra:mprapa:80266

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().