Skip to main content

Prediction Market Index by Combining Financial Time-Series Forecasting and Sentiment Analysis Using Soft Computing

  • Conference paper
  • First Online:
Distributed Computing and Artificial Intelligence, 15th International Conference (DCAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 800))

  • 652 Accesses

Abstract

In recent years, a lot of research is focusing on predicting real-world outcomes using Social networks data (for example, Twitter Data). Sentiment Analysis of the twitter data thus has become one of the key aspects of making predictions involving human sentiments. Stock market movements are very sensitive and it affects investment of the investors because of this prediction is the main interest of the researchers. Soft computing approaches and nature-inspired computing has a lot of potential in predicting the market movement. In this paper, soft computing techniques are used to predict market trends using sentiments extracted from market data. The results indicate that by selecting suitable neural networks architecture and selecting suitable regression coefficients can improve the overall accuracy and correlation of the predictions. Stock market information people use for investment decisions. Forecasting must be accurate otherwise it will not be effective in the decision. There are techniques like trend based classification, adaptive indicators selection and market trading signals are used in forecasting.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dinesh Kumar Saini .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Saini, D.K., Zia, K., Abusham, E. (2019). Prediction Market Index by Combining Financial Time-Series Forecasting and Sentiment Analysis Using Soft Computing. In: De La Prieta, F., Omatu, S., Fernández-Caballero, A. (eds) Distributed Computing and Artificial Intelligence, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-319-94649-8_22

Download citation

Publish with us

Policies and ethics