Skip to main content
SpringerLink
Log in

TAIEX Forecasting Based on Fuzzy Time Series and Technical Indices Analysis of the Stock Market

  • Conference paper
Recent Trends in Applied Artificial Intelligence (IEA/AIE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7906))

  • 4029 Accesses

Abstract

This paper presents a new method for forecasting the TAIEX based on fuzzy time series and technical indices analysis of the stock market. Because the proposed method uses both fuzzy time series and technical indices analysis of the stock market to analyze the historical training data in details for forecasting the TAIEX, it can get higher forecasting accuracy rate than the existing methods. The contribution of this paper is that we present a new fuzzy time series forecasting method based on the MACD index, combined with the stochastic line indices (KD indices) to forecast the TAIEX. It gets a higher average forecasting accuracy rate than the existing method for forecasting the TAIEX.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Appel, G., Hitschler, W.F.: Stock Market Trading Systems. Traders Press (1990)

    Google Scholar 

  2. Chen, S.M.: Forecasting Enrollments Based on Fuzzy Time Series. Fuzzy Sets and Systems 81(3), 311–319 (1996)

    Article  Google Scholar 

  3. Huarng, K., Yu, T.H.K.: The Application of Neural Networks to Forecast Fuzzy Time Series. Physica A 363(2), 481–491 (2006)

    Article  Google Scholar 

  4. Huarng, K.H., Yu, T.H.K., Hsu, Y.W.: A Multivariate Heuristic Model for Fuzzy Time-Series Forecasting. IEEE Transaction on Systems, Man, Cybernetics Part-B: Cybernetics 37(4), 836–846 (2007)

    Article  Google Scholar 

  5. Kirkpatrick, C.D., Dahlquist, J.R.: Technical Analysis: The Complete Resource for Financial Market Technicians, 2nd edn. FT Press (2010)

    Google Scholar 

  6. Song, Q., Chissom, B.S.: Fuzzy Time Series and Its Model. Fuzzy Sets and Systems 54(3), 269–277 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  7. Song, Q., Chissom, B.S.: Forecasting Enrollments with Fuzzy Time Series—Part I. Fuzzy Sets and Systems 54(1), 1–9 (1993)

    Article  MathSciNet  Google Scholar 

  8. Song, Q., Chissom, B.S.: Forecasting Enrollments with Fuzzy Time Series—Part II. Fuzzy Sets and Systems 62(1), 1–8 (1994)

    Article  Google Scholar 

  9. Yu, H.K.: Weighted Fuzzy Time-Series Models for TAIEX Forecasting. Physica A 349(3–4), 609–624 (2005)

    Article  Google Scholar 

  10. Yu, T.H.K., Huarng, K.H.: A Bivariate Fuzzy Time Series Model to Forecast the TAIEX. Expert Systems with Applications 34(4), 2945–2952 (2008)

    Article  Google Scholar 

  11. Yu, T.H.K., Huarng, K.H.: Corrigendum to “A Bivariate Fuzzy Time Series Model to Forecast the TAIEX”. Expert Systems with Applications 37(7), 5529 (2010)

    Article  Google Scholar 

  12. Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  13. TAIEX Web Site, http://www.twse.com.tw/en/products/indices/tsec/taiex.php

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

    Shyi-Ming Chen & Cheng-Yi Wang

Authors
  1. Shyi-Ming Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cheng-Yi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University, 78666, San Marcos, TX, USA

    Moonis Ali

  2. Agent Systems Research Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081, Amsterdam, HV, The Netherlands

    Tibor Bosse

  3. Interactive Intelligence Group, Department of Intelligent Systems, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    Koen V. Hindriks  & Catholijn M. Jonker  & 

  4. Computational Intelligence Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Mark Hoogendoorn

  5. Agent Systems Research Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Jan Treur

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, SM., Wang, CY. (2013). TAIEX Forecasting Based on Fuzzy Time Series and Technical Indices Analysis of the Stock Market. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_48

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38577-3_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38576-6

  • Online ISBN: 978-3-642-38577-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation