Skip to main content
SpringerLink
Log in

Fuzzy Logic Decision Support for Long-Term Investing in the Financial Markets

  • Conference paper
Nostradamus: Modern Methods of Prediction, Modeling and Analysis of Nonlinear Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 192))

  • 1370 Accesses

Abstract

This paper discusses the use of fuzzy logic and modeling as a decision support for long-term investment decisions in the financial markets. A simple model is proposed to calculate recommendations for investors. This research required thorough analysis of historical data that lead to the discovery of interesting dependencies between the Dow Jones index, currency pairs, oil price and the VIX volatility index. The fuzzy model uses several input variables that are used to simplify the complex conditions in the financial markets. The purpose of the model is to evaluate the current market situation, compare the current situation to similar situations in the past and to provide investment recommendations for long-term future investing.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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.

References

  1. Abel, H.: Digital Day Trading, Dearborn, USA, 269p. (1999) ISBN 0-7931-3113-8

    Google Scholar 

  2. Aliev, A., Aliev, R.: Soft Computing and Its Applications, 444 p. World Scientific Pub. Ltd., UK (2002) ISBN 981-02-4700-1

    Google Scholar 

  3. Altrock, C.: Fuzzy Logic & Neurofuzzy – Applications in Business & Finance, 375 p. Prentice Hall, USA (1996) ISBN 0-13-591512-0

    Google Scholar 

  4. Armstrong, S.J.: Principles of Forecasting, 849s p. Kluwer Academic Publishers, USA (2001) ISBN 0-7923-7930-6

    Google Scholar 

  5. Baird, B., Burney, C.: Electronic Day Trading to Win, 220 p. John Wiley & Sons Inc., USA (1999) ISBN 0-471-35072-9

    Google Scholar 

  6. Bernice, C.: The Edge of Chaos - Financial Booms, Bubbles, Crashes and Chaos, 379 p. John Wiley & Sons Ltd., UK (1997) ISBN 0-471-96907-9

    Google Scholar 

  7. Dostál, P., Sojka, Z.: Financial Risk Management. In: Zlín 2005, Skripta, 60 p. (2005) ISBN 80-7318-343-9

    Google Scholar 

  8. DostÁL, P.: Prediction of Competitive Environment in Business. In: 28th International Symposium on Forecasting, Nice, France, p. 171, 6p., ISSN 1997-4116, ISSN 1997-4124

    Google Scholar 

  9. DostÁL, P., Rais, K.: Stock Market Decision Machine. In: 29th International Symposium on Forecasting, Hong-Kong, China, p. 171, 5 p. (2009) ISSN 1997-4116

    Google Scholar 

  10. Dostál, P., Budík, J.: System for Intelligent Investment Portfolio Making. In: 30th International Symposium on Forecasting, San Diego, USA, 6 p. (2010) ISSN 1997-4116

    Google Scholar 

  11. Dostál, P.: Advanced Decision Making in Business and Public Services, 168 p. CERM, Brno (2011) ISBN 978-80-7204-747-5

    Google Scholar 

  12. Dostál, P., Brož, Z.: Fuzzy Logic Investment Support on the Financial Market. In: 31th International Symposium on Forecasting, Praha, CZ, 6 p. (2011) ISSN 1997-4116

    Google Scholar 

  13. Ehlers, F.J.: Cybernetic Analysis for Stock and Futures, 256 p. John Wiley & Sons Inc, USA (2004) ISBN 0-471-46307-8

    Google Scholar 

  14. Franses, P.H.: Time Series Models for Business and Economic Forecasting, Cambridge, 213 p. University Press, UK (2001) ISBN 0-521-58641-0

    Google Scholar 

  15. Frost, A.J., Pretcher, R.: Elliott Wave Principle, 245 p. New Classic Library, USA (2000) ISBN 0-932750-43-5

    Google Scholar 

  16. Gleick, J.: Chaos, 330 p. Ando Publishing (1996) ISBN 80-86047-04-0

    Google Scholar 

  17. Gozzhelf, P.: Techno Fundamental Trading, 267 p. Probus Publishing Company, USA (1995) ISBN 1-55738-541-6

    Google Scholar 

  18. Hand, D., Mannila, H.: Principles of Data Mining, 546 p. The MIT Press, USA (2001) ISBN 0-262-08290-X

    Google Scholar 

  19. Herbst, F.: Analyzing and Forecasting Futures Prices, 238 p. John Wiley & Sons Inc., USA (1992) ISBN 0-471-53312-2

    Google Scholar 

  20. Howard, A.: Digital Day Trading, Dearborn, USA, 269 p. (1999) ISBN 0-7931-3113-8

    Google Scholar 

  21. Chen, S., Wang, P., Wen, T.: Computational Intelligence in Economic and Finance. Springer (2004) ISBN 978-3-540-72820-7

    Google Scholar 

  22. Chen, S., Wang, P., Wen, T.: Computational Intelligence in Economic and Finance, vol. II. Springer (2007) ISBN 978-3-540-72820-7

    Google Scholar 

  23. Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic, Theory and Applications, 279 p. Prentice Hall, New Jersy (1995) ISBN 0-13-101171-5

    Google Scholar 

  24. Peters, E.E.: Fractal Market Analysis – Applying Chaos Theory to Investment & Economic, 315 p. John Wiley & Sons Inc, USA (1994) ISBN 0-471-58524-6

    Google Scholar 

  25. Peters, E.E.: Chaos and Order in the Capital Markets: A New View of Cycles, Prices, Wiley Finance Edition, USA, 274 p. (1996) ISBN 0-471-13838-6

    Google Scholar 

  26. Trippi, R.R.: Chaos & Nonlinear Dynamic in the Financial Markets, 505p. Irwin Professional Publishing, USA (1995) ISBN 1-55738-857-1

    Google Scholar 

  27. Ribeiro, R., Yager, R.: Soft Computing in Financial Engineering, 590 p. A Springer Verlag Company (1999) ISBN 3-7908-1173-4

    Google Scholar 

  28. THE MATHWORKS. MATLAB – User’s Guide, The MathWorks, Inc. (2010)

    Google Scholar 

  29. Weigend, A.: Time Series Prediction: Forecasting the Future and Understanding the Past, 643 p. Addison-Wesley, Massachusetts (1993) ISBN 0-201-62602-0

    Google Scholar 

  30. Williams, L.V.: Information Efficiency in Financial and Betting Markets, 353 p. Cambridge University Press (2005) ISBN 0–521-81603-3

    Google Scholar 

  31. Wisniewski, M.: Quantitative Methods for Decision Makers, 4th edn., 592 p. Pearson Education Limited, England (2006) ISBN 0 27368 789 1

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Business and Management, Institute of Informatics, Brno University of Technology, Kolejní 2906/4, 612 00, Brno, Czech Republic

    Zdeňek Brož & Petr Dostál

Authors
  1. Zdeňek Brož
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Petr Dostál
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering and Co, Department of Computer Science, VŠB-Technical University of Ostrava, 17. listopadu 15, Ostrava-Poruba, 70833, Czech Republic

    Ivan Zelinka

  2. Institute of Physical and, Theoretical Chemistry, University of Tuebingen, Auf der Morgenstelle 8, Tuebingen, 72076, Germany

    Otto E. Rössler

  3. , Faculty of Electrical Engineering, Department of Computer Science, 17. listopadu 15, Ostrava-Poruba, 708 33, Czech Republic

    Václav Snášel

  4. (MIR Labs), Scientific Network for Innovation and, Machine Intelligence Research Labs, MIR Labs Campus, Auburn, 98071, Washington, USA

    Ajith Abraham

  5. , Dept. de Informática y Automática, University of Salamanca, Plaza de la Merced, s/n, Salamanca, 37008, Spain

    Emilio S. Corchado

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Brož, Z., Dostál, P. (2013). Fuzzy Logic Decision Support for Long-Term Investing in the Financial Markets. In: Zelinka, I., Rössler, O., Snášel, V., Abraham, A., Corchado, E. (eds) Nostradamus: Modern Methods of Prediction, Modeling and Analysis of Nonlinear Systems. Advances in Intelligent Systems and Computing, vol 192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33227-2_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-33227-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33226-5

  • Online ISBN: 978-3-642-33227-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation