Vorhersage von Mustern auf mehreren Ebenen bei unstrukturierten Finanzdaten
Vorhersage von Mustern auf mehreren Ebenen bei unstrukturierten Finanzdaten

Vorhersage von Mustern auf mehreren Ebenen bei unstrukturierten Finanzdaten


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About the Book

Die Vorhersage der Zukunft ist ein Aspekt bei der Entwicklung profitabler Daytrading-Strategien. Bei der technischen Analyse werden Preise, Volumina und andere Marktinformationen analysiert, während bei der Fundamentalanalyse die Fakten des Unternehmens, des Marktes, der Währung oder des Rohstoffs untersucht werden. Die meisten großen Maklerunternehmen, Handelsgruppen oder Finanzinstitute verfügen in der Regel sowohl über ein Team für technische Analyse als auch für Fundamentalanalyse. Die technische Analyse wird in der Forschungsarbeit berücksichtigt. In dieser Forschungsarbeit wird ein auf HMDM basierendes System zur Vorhersage von Börsentrends und EHHMM zur Vorhersage zukünftiger Trends der CBOE und nigerianischer 7up-Abfüllunternehmen vorgestellt. Die Merkmale werden aus den historischen CBOE-Schlusskursdaten extrahiert. Die extrahierten Merkmale werden verwendet, um die Vorhersage zu erstellen. HHMMs sind nützlich bei Anwendungen, die sich mit Sequenzen von Symbolen befassen. Die Studie zeigt, dass das EHMDM-basierte System genauer ist als das HMDM-basierte System. Es wurde festgestellt, dass das EHMDM in Kombination mit dem EST-Vorhersagesystem eine bessere Genauigkeit aufweist. Das HMDM-System in Kombination mit dem MAT-Vorhersagesystem mit versteckten Zuständen ergab eine geringere Genauigkeit.


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Product Details
  • ISBN-13: 9786204852041
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Verlag Unser Wissen
  • Height: 229 mm
  • No of Pages: 144
  • Spine Width: 9 mm
  • Width: 152 mm
  • ISBN-10: 6204852043
  • Publisher Date: 15 Jun 2022
  • Binding: Paperback
  • Language: German
  • Returnable: N
  • Weight: 272 gr


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Vorhersage von Mustern auf mehreren Ebenen bei unstrukturierten Finanzdaten
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Vorhersage von Mustern auf mehreren Ebenen bei unstrukturierten Finanzdaten
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