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Taking the pulse of the real economy

datacite.subject.fosCiências Sociais::Economia e Gestãopt_PT
dc.contributor.advisorDemirci, Irem
dc.contributor.authorToshev, Valentin
dc.date.accessioned2019-05-23T14:36:46Z
dc.date.available2019-05-23T14:36:46Z
dc.date.issued2019-01-25
dc.description.abstractIn this research, I show that aggregate information from financial statement analysis helps in predicting real economic development. Further, I show that using the top 100 U.S. public companies, ranked by market capitalisation, represents a convenient method to proxy for the entire portfolio of traded companies. I then show that aggregate accounting information of the same 100 biggest companies has predictive information for next quarter real Gross Domestic Product (GDP) growth, after controlling for the traditional stock market returns, and explains a portion of professional macro forecasters’ revisions and errors. Konchitchki and Patatoukas (2014a) provide an intuitive framework for these findings. Yet, I contribute by finding that aggregate accounting drivers from the Alternative Breakdown provide greater predictive power when compared to DuPont and that introducing financial and nonfinancial data split reduces heterogeneity. Another contribution of mine is introducing out-of-sample analysis. Although, I find that current methods used by professional macro forecasters exhibit slightly lower root-mean-square error (RMSE), I only use annual stock market returns and aggregate accounting profitability drivers in my modelpt_PT
dc.identifier.tid202226905pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/70539
dc.language.isoengpt_PT
dc.subjectFinancial statement analysispt_PT
dc.subjectAccountingpt_PT
dc.subjectStock valuationpt_PT
dc.subjectMacro forecastingpt_PT
dc.subjectMacroeconomicspt_PT
dc.subjectAggregate accounting profitability drivers.pt_PT
dc.titleTaking the pulse of the real economypt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameA Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economicspt_PT

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