Skip to main content
SpringerLink
Log in

Computational Intelligence Techniques for Behavioral Research on the Analysis of Investment Decisions in the Commercial Realty Market

  • Chapter
  • First Online:
Computational Intelligence for Modern Business Systems

Abstract

The real estate market shows huge behavioural dispositions recorded in the customary financial markets. The principal goal of this examination is to recognize the Behavioral Factors that impact the assessment of investment of investors in the realty market. The primary target of this examination is to characterize the feelings-based hypotheses utilized to clarify the financial exchange issues and terms. In this paper, it is realized that feelings can’t generally spur investors, and it isn’t vital that the property market effectively be adequate at the feeble structure. There is a need for a profound examination of the hypothesis of behavioural account. This investigation is helpful to comprehend the investments by utilizing the behavioural model. Using digital and statical analysis using ML techniques get a chance to improve Behavioral Research on The Analysis of Investment Decisions in The Commercial Realty Market and further analyse the stock. Investors consistently need to put resources into those tasks with more prominent benefits and the capital’s base odds of risk or loss.

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 EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
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. Andonov A, Eichholtz P, Kok N (2012) Value added from money managers in private markets? An examination of pension fund investments in real estate. Working Paper, Maastricht University. Mejudice, pp 1–45

    Google Scholar 

  2. Chaffai M, Medhioub I (2014) Behavioural finance: an empirical study of the Tunisian stock market. Int J Econ Financ Issues 4(3):527–538

    Google Scholar 

  3. Graham JR, Harvey CR (2009) Investor competence, trading frequency, and home bias. INFORMS 55(7):1094–1106

    Google Scholar 

  4. Corrado CJ, Jordan BD (2020) Fundamentals of investments: valuation and management. http://elibrary.gci.edu.np/bitstream/123456789/685/1/BM-783%20The%20Essential%20Guide%20to%20Business%20Etiquette%20by%20Lillian%20H.%20Chaney%2C%20Jeanette%20S.%20Martin.pdf. Accessed 25 May 2021

  5. Kahneman D, Tversky A (2013) Prospect theory: an analysis of decision under risk. In: Handbook of the fundamentals of financial decision making: Part I, pp 99–127

    Google Scholar 

  6. Kahuthu DG (2011) Effects of herd behaviour on trading volume and prices of securities at NSE. Unpublished M.B.A. Research Project. The University of Nairobi

    Google Scholar 

  7. Kisii County (2014) Kisii County Annual Report, 2014. Ministry of Housing. Sessional Paper No. 3 of 2004 on National Housing Policy for Kenya

    Google Scholar 

  8. Kothari CR (2004) Research methods, quantitative and qualitative approaches

    Google Scholar 

  9. Mydhili V, Sundaridadhabai A (2017) Glimpse on realities of realty sector in India: a special focus on A.P. J Adv Res Dyn Control Syst, 9:18

    Google Scholar 

  10. Nairobi Muthama AK (2012) Effect of Investor psychology on real estate market prices in Nairobi. An Unpublished M.B.A. report. University of Nairobi

    Google Scholar 

  11. Nyamute W, Lishenga J, Oloko M (2015) The relationship between investor behaviour and portfolio performance at the Nairobi securities exchange. Int J Multidisciplinary Res Dev 2(5):248–551

    Google Scholar 

  12. Onsomu ZN (2014) The impact of behavioral biases on investor decisions in Kenya: male vs female. Int J Res Humanities Arts Literat 2(6):87–92

    Google Scholar 

  13. Dichev, Ilia, Piotroski (2021) The long-run stock returns following bond ratings changes. J Finance 56:173–203

    Google Scholar 

  14. Edmans et al. (2007) Sports sentiment and stock returns. J Finance 62:1967–1998

    Google Scholar 

  15. Mydhili V, Sundaridadhabai (2019) Rationality in decision making of residential property buyers: a Myth or Fact. Int J Innov Technol Exploring Eng 8(5)

    Google Scholar 

  16. French S (1986) Decision theory: an introduction to the mathematics of rationality. Ellis Horwood, Chichester

    MATH  Google Scholar 

  17. Glaser M, No¨th M, Weber M (2004) Behavioral finance. In Koehler DJ, Harvey N (Eds), Blackwell handbook of judgment and decision making, Blackwell, Oxford, pp 527–46

    Google Scholar 

  18. Gallimore P (2004) Behavioural real estate research, Retrieved January 17, 2004, from http://construction.ntu.ac.uk/graduate_school/Research/Property

  19. Johnsson M, Lindblom H, Platan P (2002) Behavioral finance and change of investor behavior during and after the speculative at the end of the 1990s. School Econ Manag (2002)

    Google Scholar 

  20. Kim KA, Nofsinger JR (2008) Behavioral finance in Asia. Pacific-Basin Finance J 16:1–7

    Google Scholar 

  21. Guiso L et al (2008) Trusting the stock market. J Finance’ 63(6):2557–2600

    Article  Google Scholar 

  22. Lakonishok J, Shleifer A, Vishny R (1994) Contrarian investment, extrapolation, and risk. J Finance 49:1541–1578

    Article  Google Scholar 

  23. Millington AF (1988) An introduction to property valuation, 3rd edn. Estates Gazette, London

    Google Scholar 

  24. Montier J (2009) Behavioural investing: a practitioner’s guide to applying behavioural finance. Wiley

    Google Scholar 

  25. Żywiołek J, Rosak-Szyrocka J, Jereb B (2021) Barriers to knowledge sharing in the field of information security. Manag Syst Prod Eng 29:114–119

    Google Scholar 

  26. Żywiołek J, Rosak-Szyrocka J, Mrowiec M (2021)K nowledge management in households about energy saving as part of the awareness of sustainable development. Energies 14(24):8207

    Google Scholar 

  27. Żywiołek J, Schiavone F (2021) Perception of the quality of smart city solutions as a sense of residents’ safety. Energies 14:5511

    Article  Google Scholar 

  28. Almahirah MS, Jahan VNM, Sharma S, Kumar S (2021) Role of market microstructure in maintaining economic development. Empirical Econ Lett 20(2)

    Google Scholar 

  29. Nayak NR, Kumar S, Gupta D, Suri A, Naved M, Soni M (2022) Network mining techniques to analyze the risk of the occupational accident via bayesian network. Int J Syst Assur Eng Manag

    Google Scholar 

  30. Kumar S (2021) Relevance of Buddhist philosophy in modern management theory. Psychol Educ 58(3):2104–2111

    Google Scholar 

  31. Kumar S, Baag PK, SKV (2021) Impact of E.S.G. Integration on equity performance between developed and developing economy: evidence from S and P 500 and NIFTY 50. Empirical Econ Lett 20(4)

    Google Scholar 

  32. Kumar S, Baag PK, SKV (2021) Financial engineering and quantitative risk analytics. SYBGEN Learning 1(1):1–360

    Google Scholar 

  33. Kakti A, Kumar S, John NK, Ratna VV, Afzal S, Gupta AD (2021) Impact of patients approach towards healthcare costs on their perception towards health: an empirical study. Tobacco Regulatory Sci 7(6–1):7380–7390

    Google Scholar 

  34. Roland G, Kumaraperumal S, Kumar S, Gupta AD, Afzal S, Suryakumar M (2021) P.C.A. (Principal Component Analysis) approach towards identifying the factors determining the medication behavior of indian patients: an empirical study. Tobacco Regulatory Sci 7(6-1):7391–7401

    Google Scholar 

  35. .Kumar S, Baag PK (2021) Ethics erosion in capital market: Lehman Brothers’ case study of Repo 105. In: AIMS-18, March 4, India, AIMS Texas U.S.A., A1872-Final.pdf (aims-international.org)

    Google Scholar 

  36. Kumar S, Baag PK (2021) Erosion of Ethics in credit derivatives: a case study. In: AIMS-18, March 4, India, AIMS India & Texas U.S.A., A1873-Final.pdf (aims-international.org)

    Google Scholar 

  37. Parnaik VK, Chaturvedi P (2015) Fluorescence recovery after photobleaching studies reveal complexity of nuclear architecture. Int J Chem 4(4):297–302

    Google Scholar 

  38. Singh B, Jalil NA, Sharma DK, SR, Kumar K, Jebakumar Immanuel D (2021) Computational systems overview and random process with theoretical analysis. 2021 7th international conference on advanced computing and communication systems, pp 1999–2005

    Google Scholar 

  39. Setiawan R, Leonardo Cavaliere LP, Koti K, Ogunmola GA, Jalil NA, Kalyan Chakravarthi M, Suman Rajest S, Regin R, Singh S (2021) The artificial intelligence and inventory effect on banking industrial performance. Turkish Online J Qual Inquiry 12(6):8100–8125

    Google Scholar 

  40. Roespinoedji D, Juniati S, Hasan H, Jalil NA, Shamsudin MF (2019) Experimenting the long-haul association between components of consuming renewable energy: ARDL method with special reference to Malaysia. Int J Energy Econ Policy 9:453–460

    Article  Google Scholar 

  41. Sharma DK, Jalil NA, Nassa VK, Vadyala SR, Senthamil LS, TN (2021) Deep learning applications to classify cross-topic natural language texts based on their argumentative form. 2021 2nd international conference on smart electronics and communication, pp 1580–1586

    Google Scholar 

  42. Sharma DK, Jalil NA, Regin R, Rajest SS, Tummala RK, TN (2021) Predicting network congestion with machine learning. 2021 2nd international conference on smart electronics and communication, pp 1574–1579

    Google Scholar 

  43. Zhao B, Chaturvedi P, Zimmerman DL, Belmont AS (2020) Efficient and reproducible multigene expression after single-step transfection using improved bac transgenesis and engineering toolkit. A.C.S. Synth Biol 9(5):1100–1116

    Google Scholar 

  44. Kubiczek J, Hadasik B (2021) Challenges in reporting the COVID-19 spread and its presentation to the society. J Data Inf Qual 13(4):1–7

    Article  Google Scholar 

  45. Bieleń M, Kubiczek J (2020) Response of the labor market to the needs and expectations of Generation Z. e-mentor 86(4):87–94

    Google Scholar 

  46. Sehgal P, Chaturvedi P (2022) Survival strategies in cold-adapted microorganisms, 1st ed. Singapore: Springer Singapore

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management Studies, Vignan’s Nirula Institute of Technology and Science for Women, Guntur, Andhra Pradesh, India

    S. Siva Venkata Ramana & T. Mydhili

  2. R.V.R. & J.C. College of Engineering, Chowdavaram, India

    Ponduri Siddardha

  3. Department of S&H, VFSTR Deemed to Be University, Valdamudi, Andhra Pradesh, India

    Gomatam Mohana Charyulu

  4. Department of C.S.E., Malla Reddy University, Hyderabad (MRUH), Hyderabad, Telangana, India

    K. Saikumar

  5. Researcher, Green Fields, Vaddeswaram, Guntur, 522302, Andhra Pradesh, India

    K. Saikumar

Authors
  1. S. Siva Venkata Ramana
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. Mydhili
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ponduri Siddardha
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gomatam Mohana Charyulu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. K. Saikumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Siva Venkata Ramana .

Editor information

Editors and Affiliations

  1. LBEF Campus, Kathmandu, Nepal

    Sandeep Kautish

  2. Department of Mechanical Engineering, MCKV Institute of Engineering, Howrah, West Bengal, India

    Prasenjit Chatterjee

  3. Faculty of Organizational Sciences, Department of Operations Research and Statistics, University of Belgrade, Belgrade, Serbia

    Dragan Pamucar

  4. Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, India

    N. Pradeep

  5. Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Pune, India

    Deepmala Singh

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ramana, S.S.V., Mydhili, T., Siddardha, P., Charyulu, G.M., Saikumar, K. (2024). Computational Intelligence Techniques for Behavioral Research on the Analysis of Investment Decisions in the Commercial Realty Market. In: Kautish, S., Chatterjee, P., Pamucar, D., Pradeep, N., Singh, D. (eds) Computational Intelligence for Modern Business Systems . Disruptive Technologies and Digital Transformations for Society 5.0. Springer, Singapore. https://doi.org/10.1007/978-981-99-5354-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-5354-7_3

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5353-0

  • Online ISBN: 978-981-99-5354-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation