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Evaluating real estate development project with Monte Carlo based binomial options pricing model

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  • I-Cheng Yeh
  • Che-Hui Lien

Abstract

This paper proposes three evaluation models for evaluating the value of strategic waiting of real estate development project. In Model 1, the ratio of land cost to total real estate sales in period (t) and period (t + 1) is uncorrelated (random). In Model 2, the ratio is unchanged (constant). Model 3 integrates Models 1 and 2 with the ‘land value persistence factor’. The larger the factor, the more the land cost tends to consider only the previous land price. This study uses the Binomial Option Pricing Model and Monte Carlo Simulation hybrid method to solve these three models. In addition, this research also proposes a method for estimating the net present value of project expansion on the time axis. The results show that five main factors influencing the expected value of the option value are the real estate price rate of change, present value of total real estate sales, duration, land value persistence factor, and present value of land. Regardless of the land value persistence factor, the longer the time, the expected value of the option value tends to increase. However, when the land value persistence factor is larger, the expected value of the option value increases more.

Suggested Citation

  • I-Cheng Yeh & Che-Hui Lien, 2020. "Evaluating real estate development project with Monte Carlo based binomial options pricing model," Applied Economics Letters, Taylor & Francis Journals, vol. 27(4), pages 307-324, February.
  • Handle: RePEc:taf:apeclt:v:27:y:2020:i:4:p:307-324
    DOI: 10.1080/13504851.2019.1616049
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    Cited by:

    1. Chen, Yang & Zhang, Xiaoling & Chau, K.W. & Yang, Linchuan, 2022. "How the institutional change in urban redevelopment affects the duration of land redevelopment approval in China?," Land Use Policy, Elsevier, vol. 119(C).
    2. Andrejs Čirjevskis, 2021. "Value Maximizing Decisions in the Real Estate Market: Real Options Valuation Approach," JRFM, MDPI, vol. 14(6), pages 1-19, June.

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