On the short-term predictability of stock returns: A quantile boosting approach
Riza Demirer (),
Christian Pierdzioch and
Finance Research Letters, 2017, vol. 22, issue C, 35-41
We study the predictability of stock returns using an iterative model-building approach known as quantile boosting. Examining alternative return quantiles that represent normal, bull and bear markets via recursive quantile regressions, we trace the predictive value of extensively studied predictors including the recently suggested short interest and sentiment variables. We find that short-term returns are predictable to some extent for extreme lower quantiles of the conditional distribution of returns. Interestingly, however, short-interest and sentiment variables do not add significant predictive power, challenging the recent findings on the predictive ability of short sellers for future cash flows and associated market returns.
Keywords: Stock returns; Predictability; Quantile boosting (search for similar items in EconPapers)
JEL-codes: C22 C53 Q02 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:22:y:2017:i:c:p:35-41
Access Statistics for this article
Finance Research Letters is currently edited by R. GenÃ§ay
More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().