Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/35175
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMcMillan, Daviden_UK
dc.date.accessioned2023-06-06T00:00:09Z-
dc.date.available2023-06-06T00:00:09Z-
dc.identifier.urihttp://hdl.handle.net/1893/35175-
dc.description.abstractFinancial markets are expected to predict macroeconomic conditions as movement in the former depends upon expectations of future performance for the latter. However, existing evidence is mixed. We argue that this arises because the stock return and term structure series typically used in studies, fail to sufficiently capture investor risk preferences. For US data, we use the variance risk premium (VRP) and default yield (DFY) to better capture such a risk measure and demonstrate that these variables exhibit greater evidence of predictive power for key macroeconomic series. In addition to VRP and DFY, we include further variables that may also capture market risk. Given similar dynamics between different risk measures and the potential for multicollinearity in estimation, we consider variable combinations. Using results obtained through predictive regressions, out-of-sample forecasting and a probit model designed to capture periods of expansion and contraction, we show that these combination variables can predict future movements in macroeconomic conditions as well as results using individual variables. Of key interest, combinations that include the VRP and DFY are preferred across all macro-series.en_UK
dc.language.isoenen_UK
dc.publisherWileyen_UK
dc.relationMcMillan D (2023) Do Financial Markets Predict Macroeconomic Performance? Evidence from Risk-Based Measures. <i>Manchester School</i>.en_UK
dc.rightsThis item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.subjectVariance Risk Premiumen_UK
dc.subjectDefault Yielden_UK
dc.subjectPredictionen_UK
dc.subjectEconomic Growthen_UK
dc.titleDo Financial Markets Predict Macroeconomic Performance? Evidence from Risk-Based Measuresen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2027-05-29en_UK
dc.rights.embargoreason[stock_vrp_output.pdf] Publisher requires embargo of 24 months after publication.en_UK
dc.citation.jtitleManchester Schoolen_UK
dc.citation.issn1467-9957en_UK
dc.citation.issn1463-6786en_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.author.emaildavid.mcmillan@stir.ac.uken_UK
dc.description.notesOutput Status: Forthcoming/Available Onlineen_UK
dc.contributor.affiliationAccounting & Financeen_UK
dc.identifier.wtid1909002en_UK
dc.contributor.orcid0000-0002-5891-4193en_UK
dc.date.accepted2023-05-29en_UK
dcterms.dateAccepted2023-05-29en_UK
dc.date.filedepositdate2023-06-02en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorMcMillan, David|0000-0002-5891-4193en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2027-05-29en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||2027-05-28en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/all-rights-reserved|2027-05-29|en_UK
local.rioxx.filenamestock_vrp_output.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1467-9957en_UK
Appears in Collections:Accounting and Finance Journal Articles

Files in This Item:
File Description SizeFormat 
stock_vrp_output.pdfFulltext - Accepted Version636.62 kBAdobe PDFUnder Embargo until 2027-05-29    Request a copy


This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.