Skip to main content

Risk Prediction in Real Estate Investment to Protect Against Asset Bubbles

  • Conference paper
  • First Online:
Applications and Techniques in Information Security (ATIS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1554))

  • 280 Accesses

Abstract

The real estate market is increasing at a rapid pace, which has also led to increase in risk of investment in real estate. In this paper analysis of real estate markets and prediction of the risk involved in the investment has been done. The approach proposed here clusters the property based on market value per square feet located in different school districts. This also help buyers to make scientifically based decisions on investing in property. The result demonstrate that tat the proposed prediction model estimates approximate value for their property. The prediction give a lower as well as upper limit on the market value of the property. This prediction can safeguard against asset bubbles that are created by various parties involved in real estate network. We can conclude that when buyers and investors are aware of the market price of the asset in future they can safeguard themselves from asset bubbles. Thus, this work is also used to protect against asset bubbles.

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 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
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

References

  1. Acciani, C., Fucilli, V., Sardaro, R.: Data mining in real estate appraisal: a model tree and multivariate adaptive regression spline approach. Aestimum, pp. 27–45 (2011)

    Google Scholar 

  2. Alfiyatin, A.N., Febrita, R.E., Taufiq, H., Mahmudy, W.F.: Modeling house price prediction using regression analysis and particle swarm optimization. Int. J. Adv. Comput. Sci. Appl. 8, 323–326 (2017)

    Google Scholar 

  3. Atkinson, P.: Asset price bubble identification and response (2012)

    Google Scholar 

  4. Bhagat, N., Mohokar, A., Mane, S.: House price forecasting using data mining. Int. J. Comput. Appl. 152(2), 23–26 (2016)

    Google Scholar 

  5. Jaen, R.D.: Data mining: an empirical application in real estate valuation. In: FLAIRS Conference, pp. 314–317 (2002)

    Google Scholar 

  6. Kubicová, I., Komarek, L.: The classification and identification of asset price bubbles (2011)

    Google Scholar 

  7. Li, W., Zhao, Y., Meng, W., Xu, S.: Study on the risk prediction of real estate investment whole process based on support vector machine. In: 2009 Second International Workshop on Knowledge Discovery and Data Mining, pp. 167–170. IEEE (2009)

    Google Scholar 

  8. Lim, W.T., Wang, L., Wang, Y., Chang, Q.: Housing price prediction using neural networks. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp. 518–522. IEEE (2016)

    Google Scholar 

  9. Lu, S., Li, Z., Qin, Z., Yang, X., Goh, R.S.M.: A hybrid regression technique for house prices prediction. In: 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp. 319–323. IEEE (2017)

    Google Scholar 

  10. Madhuri, C.R., Anuradha, G., Pujitha, M.V.: House price prediction using regression techniques: a comparative study. In: 2019 International Conference on Smart Structures and Systems (ICSSS), pp. 1–5. IEEE (2019)

    Google Scholar 

  11. Wang, T., Li, Y.Q., Zhao, S.F.: Application of SVM based on rough set in real estate prices prediction. In: 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing, pp. 1–4. IEEE (2008)

    Google Scholar 

  12. Wedyawati, W., Lu, M.: Mining real estate listings using oracle data warehousing and predictive regression. In: Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration 2004. IRI 2004, pp. 296–301. IEEE (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sumith N. .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Muniyal, B., N., S., Nayak, S., Prabhu, N. (2022). Risk Prediction in Real Estate Investment to Protect Against Asset Bubbles. In: Pokhrel, S.R., Yu, M., Li, G. (eds) Applications and Techniques in Information Security. ATIS 2021. Communications in Computer and Information Science, vol 1554. Springer, Singapore. https://doi.org/10.1007/978-981-19-1166-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1166-8_4

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1165-1

  • Online ISBN: 978-981-19-1166-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics