Predicting the direction of US stock markets using industry returns

Pönkä, Harri

Predicting the direction of US stock markets using industry returns

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper, we examine the directional predictability of excess stock market returns by lagged excess returns from industry portfolios and a number of other commonly used variables by means of dynamic probit models. We focus on the directional component of the market returns because, for investment purposes, forecasting the direction of return correctly is presumably more relevant than the accuracy of point forecasts. Our findings suggest that only a small number of industries have predictive power for market returns. We also find that the binary response models outperform conventional predictive regressions in forecasting the direction of the market return. Finally, we test trading strategies and find that a number of industry portfolios contain information that can be used to improve investment returns.

Keywords: industry excess return; sign prediction; probit model; forecasting (search for similar items in EconPapers)
JEL-codes: C25 C53 C58 G17 (search for similar items in EconPapers)
Date: 2014-02-24
New Economics Papers: this item is included in nep-fmk and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/62942/1/MPRA_paper_62942.pdf original version (application/pdf)

Related works:
Journal Article: Predicting the direction of US stock markets using industry returns (2017)
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:62942

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 ().