Skip to main content

Index Frequency-Based Contour Selection of Gray Wave Forecasting Model and Its Application in Shanghai Stock Market

  • Conference paper
  • First Online:
Book cover Smart Service Systems, Operations Management, and Analytics (INFORMS-CSS 2019)

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Included in the following conference series:

  • 1233 Accesses

Abstract

Indexes reflect the mechanism of the stock market and the Gray Wave Forecasting Model (GWFM) which has been confirmed to be one of the most effective methods for forecasting. However, the previous method did not take into account the fact that the larger the index frequency is, the more likely this index is to appear in the future. According to the changing law of indexes, an index frequency-based contour selection of GWFM is put forward in this study where the classical uniformly spaced contour line is used twice to select the contour lines. Using this model, the fluctuation trend of Shanghai stock indexes is well predicted which demonstrated that this model has certain advantage over the original GWFM at forecasting stock indexes.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and 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
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. H. Yao H, D. Li, J. Li, Stock market volatility forecast based on calculation of characteristic hysteresis. J. Comput. Appl. 35(07), 2077–2082 (2015)

    Google Scholar 

  2. J. Lee, The evolving linkage between China and U.S. stock markets. J. Pediatr. Surg. 5(4), 468–470 (2012)

    Google Scholar 

  3. L. Chijie, Hybridizing nonlinear independent component analysis and support vector regression with particle swarm optimization for stock index forecasting. Neural Comput. Appl. 23(7–8), 2417–2427 (2013)

    Google Scholar 

  4. L.J. Kao, C.C. Chiu, C.H. Lu et al., Integration of nonlinear independent component analysis and support vector regression for stock price forecasting. Neurocomput. 99(1), 534–542 (2013)

    Article  Google Scholar 

  5. T. Xiong, Y. Bao, Z. Hu et al., Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting. Knowl. Based Syst. 5587–55100 (2014)

    Google Scholar 

  6. G.S. Atsalakis, E.M. Dimitrakakis, D. Constantinos et al., Elliott wave theory and neuro-fuzzy systems, in stock market prediction: the WASP system. Expert Syst. Appl. 38(8), 9196–9206 (2011)

    Article  Google Scholar 

  7. M.Y. Chen, M.H. Fan, Y.L. Chen et al., Design of experiments on neural network’s parameters optimization for time series forecasting in stock markets. Neural Netw. World J. 23(4), 369–390 (2013)

    Article  Google Scholar 

  8. P. Singh, B. Borah, Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization. Int. J. Approx. Reason. 55(3), 812–833 (2014)

    Article  Google Scholar 

  9. L. Sifeng, L. Yi, Grey Systems: Theory and Applications (Springer Science & Business Media, Berlin, Germany, 2010)

    Google Scholar 

  10. J. Wei, L. Zhou, F. Wang et al., Work safety evaluation in mainland China using grey theory. Appl. Math. Modell. 39(2), 924–933 (2015)

    Article  Google Scholar 

  11. Q. Wan, Y. Wei, X. Yang, Research on grey wave forecasting model. Adv. Grey Syst. Res. (2010)

    Google Scholar 

  12. Y. Chen, K. He, C. Zhang, A novel grey wave forecasting method for predicting metal prices. Resour. Policy 49, 323–331 (2016)

    Article  Google Scholar 

  13. Y. Chen, B. Liu, Forecasting port cargo throughput based on grey wave forecasting model with generalized contour lines. J. Grey Syst. 29(1), 51–63 (2017)

    Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge financial support from the Science and Technology Commission of Shanghai Municipality (No.17DZ1101005).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xingyuan Li .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, X., Tang, Q., Ning, S. (2020). Index Frequency-Based Contour Selection of Gray Wave Forecasting Model and Its Application in Shanghai Stock Market. In: Yang, H., Qiu, R., Chen, W. (eds) Smart Service Systems, Operations Management, and Analytics. INFORMS-CSS 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-30967-1_26

Download citation

Publish with us

Policies and ethics