File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Technological innovations and aggregate risk premiums

TitleTechnological innovations and aggregate risk premiums
Authors
KeywordsPatents
Research and development
Return predictability
Technological innovations
Technology shocks
Issue Date2009
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jfec
Citation
Journal Of Financial Economics, 2009, v. 94 n. 2, p. 264-279 How to Cite?
AbstractIn this paper, I propose that technological innovations increase expected stock returns and premiums at the aggregate level. I use aggregate patent data and research and development (R&D) data to measure technological innovations in the U.S., and find that patent shocks and R&D shocks have positive and distinct predictive power for U.S. market returns and premiums. Similar patterns are also found in international data including other G7 countries, China, and India. These findings are consistent with previous empirical studies based on firm-level data, and call for further theoretical explanations. © 2009 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/141770
ISSN
2023 Impact Factor: 10.4
2023 SCImago Journal Rankings: 13.655
SSRN
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHsu, PHen_HK
dc.date.accessioned2011-09-27T03:00:42Z-
dc.date.available2011-09-27T03:00:42Z-
dc.date.issued2009en_HK
dc.identifier.citationJournal Of Financial Economics, 2009, v. 94 n. 2, p. 264-279en_HK
dc.identifier.issn0304-405Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/141770-
dc.description.abstractIn this paper, I propose that technological innovations increase expected stock returns and premiums at the aggregate level. I use aggregate patent data and research and development (R&D) data to measure technological innovations in the U.S., and find that patent shocks and R&D shocks have positive and distinct predictive power for U.S. market returns and premiums. Similar patterns are also found in international data including other G7 countries, China, and India. These findings are consistent with previous empirical studies based on firm-level data, and call for further theoretical explanations. © 2009 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jfecen_HK
dc.relation.ispartofJournal of Financial Economicsen_HK
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in <Journal of Financial Economics>. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL 94, ISSUE 2, (2009)] DOI 10.1016/j.jfineco.2009.01.002-
dc.subjectPatentsen_HK
dc.subjectResearch and developmenten_HK
dc.subjectReturn predictabilityen_HK
dc.subjectTechnological innovationsen_HK
dc.subjectTechnology shocksen_HK
dc.titleTechnological innovations and aggregate risk premiumsen_HK
dc.typeArticleen_HK
dc.identifier.emailHsu, PH: paulhsu@hku.hken_HK
dc.identifier.authorityHsu, PH=rp01553en_HK
dc.description.naturepostprinten_US
dc.identifier.doi10.1016/j.jfineco.2009.01.002en_HK
dc.identifier.scopuseid_2-s2.0-70349138005en_HK
dc.identifier.hkuros210277-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349138005&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume94en_HK
dc.identifier.issue2en_HK
dc.identifier.spage264en_HK
dc.identifier.epage279en_HK
dc.identifier.isiWOS:000274725600005-
dc.publisher.placeNetherlandsen_HK
dc.identifier.ssrn971211-
dc.identifier.scopusauthoridHsu, PH=8974031100en_HK
dc.identifier.citeulike5375846-
dc.identifier.issnl0304-405X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats