Neuronale Netze in der Wertpapieranalyse
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Projektarbeit aus dem Jahr 2013 im Fachbereich BWL - Investition und Finanzierung, Note: 1,3, Hochschule für Wirtschaft und Umwelt Nürtingen-Geislingen; Standort Nürtingen, Sprache: Deutsch, Abstract: Lernen ist ein langsamer, lebenslang andauernder Prozess der den Menschen auf seine heutige evolutorische Stufe gehoben hat. Die Grundlagen hierfür liegen in unserem komplexen und hochentwickelten Gehirn dessen Struktur uns das Lernen erst ermöglicht. Inspiriert durch das biologische Vorbild, das Informationen aufnimmt, speichert und Schlüsse für die Zukunft und unser zukünftiges Verhalten zieht, beschäftigen sich seit einigen Jahren Wissenschaftler damit, die neuronale Struktur in unserem Gehirn künstlich nachzubilden und damit basierend auf Zeitreihen der Vergangenheit Aussagen über den zukünftigen Verlauf der Zeitreihe zu treffen. Ein besonderer Aspekt ist hier die bereits erwähnte Fähigkeit des Menschen zu lernen, die Computer im Gegensatz zum Menschen in der Regel nicht besitzen. Mit künstlichen neuronalen Netzen (KNN) kann dem Computer diese Fähigkeit verliehen werden, wodurch sich völlig neue Einsatzmöglichkeiten ergeben. Beispielsweise lassen sich sehr leistungsstarke aber auch rechenintensive Netze zur kurzfristigen Prognose von Wertpapierindices oder Aktienkursen erstellen, auf welchen in dieser Arbeit auch der Schwerpunkt liegt. Zunächst wird auf das bereits erwähnte biologische Vorbild, das Gehirn, eingegangen, und der historische Ursprung künstlicher neuronaler Netze dargestellt. Daran anschlie end werden der Aufbau eines künstlichen neuronalen Netzes sowie die Funktionsweise erläutert. Abschlie end wird auf die vielfältigen Einsatzmöglichkeiten im Rahmen der Wertpapieranalyse eingegangen, und ein Fazit gezogen.
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