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Eignung des Garch-Modells zur Prognose der Volatilität des Dow Jones Industrial Average

Eignung des Garch-Modells zur Prognose der Volatilität des Dow Jones Industrial Average

          
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About the Book

Bachelorarbeit aus dem Jahr 2021 im Fachbereich BWL - Investition und Finanzierung, Note: 1,3, Hochschule München, Sprache: Deutsch, Abstract: Bei Kapitalanlagen verfolgen Investoren i. d. R. das Ziel, hohe Renditen innerhalb kurzer Laufzeiten bei zeitgleich niedrigen Anlagerisiken, zu erzielen. Dabei ist grundsätzlich jeder Investor als Risikoavers anzusehen, der ausschließlich bereit ist, ein Risiko einzugehen, wenn die Risikobereitschaft sich in der Höhe der resultierenden Rendite positiv bemerkbar macht. Ein wichtiger Maßstab zur Messung des Risikos einer Investition ist die Betrachtung der Volatilität, welche das Streuungsmaß über einen Zeitverlauf beschreibt. So gilt eine Investition als risikoreich, wenn sie starken Kursschwankungen unterliegt und das investierte Kapital der Gefahr ausgesetzt ist, einen betragsmäßig höheren Anteil an Wert zu verlieren. Daraus ist zu schließen, dass die Volatilität einen wichtigen Risikoparameter darstellt und vor Investitionsentscheidungen auf die eigene Risikobereitschaft abgestimmt werden sollte. Vor der Investition wird jedoch üblicherweise die vergangene Volatilität des Investitionsobjektes betrachtet, obwohl die zukünftige Volatilität jene ist, welche das tatsächlich einzugehende Risiko beschreibt. Um einen Einblick über die Ausprägungen der zukünftigen Volatilitäten zu bekommen, werden sogenannte Zeitreihenmodelle verwendet, mit deren Hilfe auf Basis von vergangenen Daten eine Prognose der zukünftigen Ausprägungen durchgeführt wird. In der vorliegenden Arbeit wird der Frage nachgegangen, welche Zeitreihenmodelle es grundsätzlich gibt und welche davon sich für eine Prognose der Volatilität von Finanzmarktzeitreihen eignen. Hierfür findet eine Darlegung der elementarsten mathematischen Grundlagen statt, um im Anschluss daran die unterschiedlichen Modelle vorzustellen. Daraufhin wird mithilfe des GARCH-Modells der Dow Jones Industrial Average (DJIA) Index auf Basis eines Datensatzes von den Jahren 2000 bis Ende 2020 mode


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Product Details
  • ISBN-13: 9783346482174
  • Publisher: Bod Third Party Titles
  • Publisher Imprint: Grin Verlag
  • Height: 210 mm
  • No of Pages: 80
  • Spine Width: 5 mm
  • Width: 148 mm
  • ISBN-10: 3346482170
  • Publisher Date: 03 Aug 2021
  • Binding: Paperback
  • Language: German
  • Returnable: N
  • Weight: 113 gr


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