Skip to main content

Individualisation of a Fuzzy System for Asset Allocation

  • Chapter
  • First Online:
Entscheidungsunterstützung in Theorie und Praxis
  • 1571 Accesses

Zusammenfassung

In this article it is displayed how a model for asset allocation which reproduces the judgement-making process of an expert (via concepts based on fuzzy logic) can be individualised and extended in order to adapt it to the judgement-making process of other experts. Here, even after wide-ranging changes and additions, the advantages of the fuzzy approach remain, which consist of its flexibility, its realistic reproduction of expert knowledge and the comprehensibility of its results. In order to clarify the procedure, typical adaptation and extension requests for an asset allocation model are presented. The steps towards their implementation are shown on an application which was developed under the expert supervision of a leading international capital investment company. The composition of the examples shown is based on experiences from several presentations in which the model was presented to various financial service providers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 74.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literaturverzeichnis

  • Anon. (2016). Euribor-EBF. URL: http://www.euribor-ebf.eu (Accessed 14/08/2016).

  • Böckhoff, M.; Stracke, G. (2004). Der Finanzplaner: Handbuch der privaten Finanzplanung und individuellen Finanzberatung. 2nd Ed., Recht und Wirtschaft, Heidelberg.

    Google Scholar 

  • Flach, J.; Rommelfanger, H. (2002). Fuzzy-Logik basiertes Bonitätsrating. In: Oehler, A. (Ed). Kreditrisikomanagement: Kernbereiche, Aufsicht und Entwicklungstendenzen. 2nd Ed., Schäffer-Poeschel, Stuttgart, 1 – 33.

    Google Scholar 

  • Jänsch, M. (2004). Fuzzy-Logik basiertes Rating-System. Diploma thesis, Institute of Mathematical Economics, Economics Department, Goethe University, Frankfurt am Main.

    Google Scholar 

  • Lehmann-Maldonado, S. (2006). Heikle Themen auf den Tisch bringen. Wealth Management, 4, 11 – 13.

    Google Scholar 

  • Müller, J. (1999). Handbuch Geldanlage. Campus, Frankfurt am Main.

    Google Scholar 

  • North, R. (2016). Fuzzy-Logic based Asset Allocation. Working paper Institute of Mathematical Economics, Economics Department, Goethe University, Frankfurt am Main.

    Google Scholar 

  • Reittinger, W. (2006). Financial Planning im Wealth Management. In: Brost, H.; Faust, M. (Eds). Private Banking und Wealth Management, Bankakademie, Frankfurt am Main, 367 – 389.

    Google Scholar 

  • Rommelfanger, H. (1993). Fuzzy Logik basierte Verarbeitung von Expertenregeln. OR-Spektrum, 15 (1), 31 – 42.

    Google Scholar 

  • Rommelfanger, H. (1994). Fuzzy Decision Support-Systeme: Entscheiden bei Unschärfe. 2nd Ed., Springer, Berlin.

    Google Scholar 

  • Rommelfanger, H.; Eickemeier, S. (2002). Entscheidungstheorie: Klassische Konzepte und Fuzzy-Erweiterungen. Springer, Berlin.

    Google Scholar 

  • Rommelfanger, H. (2008). Mathematisch-statistische Verfahren und Fuzzy-Expertensysteme. In: Everling, O. (Ed.). Certified Rating Analyst, Oldenbourg, München, 159 – 185.

    Google Scholar 

  • Schmidt, G. (2006). Persönliche Finanzplanung: Modelle und Methoden des Financial Planning. Springer, Berlin.

    Google Scholar 

  • Scholz, C. (2006). Wertpapierformen und Derivate. In: Brechmann, A.; Glutting, T.; Harter, E.G. et al. (Eds.). Wertpapiere in Theorie und Praxis, 6th Ed., Deutscher Sparkassenverlag, Stuttgart, 286 – 529.

    Google Scholar 

  • Spremann, K. (1999). Vermögensverwaltung. Oldenbourg, München.

    Google Scholar 

  • Wyder, A. (2006). Methodik der privaten Vermögensplanung. In: Krauß, P. J. (Ed.). Financial Planning in der Praxis: Private Finanzplanung erfolgreich umsetzen, Gabler, Wiesbaden, 219 – 243.

    Google Scholar 

  • Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, 8, 338 – 353.

    Google Scholar 

  • Zand Niapour, S. (2007). Fuzzy-Expertensystem für das Analysefeld Absatzmarkt und Marktstellung. Diploma thesis, Institute of Mathematical Economics, Economics Department, Goethe University, Frankfurt am Main.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Reiner North Dipl.-Kfm. .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Fachmedien Wiesbaden GmbH

About this chapter

Cite this chapter

North, R. (2017). Individualisation of a Fuzzy System for Asset Allocation. In: Spengler, T., Fichtner, W., Geiger, M., Rommelfanger, H., Metzger, O. (eds) Entscheidungsunterstützung in Theorie und Praxis. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-17580-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-17580-1_7

  • Published:

  • Publisher Name: Springer Gabler, Wiesbaden

  • Print ISBN: 978-3-658-17579-5

  • Online ISBN: 978-3-658-17580-1

  • eBook Packages: Business and Economics (German Language)

Publish with us

Policies and ethics