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DC poleHodnotaJazyk
dc.contributor.authorGlova, Jozef
dc.date.accessioned2016-01-20T06:53:18Z
dc.date.available2016-01-20T06:53:18Z
dc.date.issued2013
dc.identifier.citationE+M. Ekonomie a Management = Economics and Management. 2013, č. 2, s. 138-150.cs
dc.identifier.issn1212-3609 (Print)
dc.identifier.issn2336-5604 (Online)
dc.identifier.urihttp://www.ekonomie-management.cz/download/1404723506_783a/2013_2+Determinacia+systematickeho+rizika+kmenovej+akcie+v+modeli+casovo-premenliveho+fundamentalneho+beta.pdf
dc.identifier.urihttp://hdl.handle.net/11025/17503
dc.format13 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isosksk
dc.publisherTechnická univerzita v Libercics
dc.relation.ispartofseriesE+M. Ekonomie a Management = Economics and Managementcs
dc.rights© Technická univerzita v Libercics
dc.rightsCC BY-NC 4.0cs
dc.subjectsystematické rizikocs
dc.subjectmodel oceňování kapitálových aktivcs
dc.subjectčasově proměnná betacs
dc.subjectpojistné akciiové rizikocs
dc.titleDeterminácia systematického rizika kmeňovej akcie v modeli časovo-premenlivého fundamentálneho betask
dc.title.alternativeEquity systematic risk determination using time-varying beta market modelen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThe current paper explores CAPM as a static model expressing relationships between excess return on the market portfolio often proxied by capital market indices, where beta is a measure of the volatility or systematic risk. We discuss background to the CAPM and derive the equations of the capital market line and security market line. To become more dynamic in the model we suggest apply the equations (12) and (13) expressing the time varying measure of the systematic risk of equity – fundamental beta. To demonstrate the applicability of the general model we apply financial econometrics involving three key steps – model selection, estimation and testing. We suggest a variety of factors (quite 24 variables) that potentially influence equity risk of Dell. In an efficient financial market we expect only stock market reaction to the unanticipated component of the fundamental variables. Thus we focus on the unanticipated or unexpected components, which we find as the residuals from ARIMA models fitted to the fundamental data. These ARIMA models were identified from the autocorrelation and partial autocorrelation functions of the data. The outcome of our modelling shows that only the multiplying the residuals from ARIMA model fitted to 6-month treasury bills yield data by the excess return on the market portfolio data and the excess return on the market portfolio data are linked to variations in Dell’s equity risk. The results of estimating the most comprehensive specification of the economic variable market model of equation (17) are reported in Tab. 1. Tests are indicating an absence of autocorrelation and heteroskedasticity in the model. The applied model can be used to determination of equity costs within a discounted cash flow approach to assess of the business value of equity or intrinsic value of stock.en
dc.subject.translatedsystematic risken
dc.subject.translatedcapital asset pricing modelen
dc.subject.translatedtime-varying betaen
dc.subject.translatedequity risk premiumen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Číslo 2 (2013)
Číslo 3 (2013)

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  1. DSpace at University of West Bohemia
  2. Publikace ZČU / UWB Publications
  3. Časopisy ZČU / UWB Journals
  4. Ekonomie a management
  5. 2013
  6. Číslo 3 (2013)