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A Pricing Framework for Real Estate Derivatives

Author

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  • Frank J. Fabozzi
  • Robert J. Shiller
  • Radu S. Tunaru

Abstract

New methods are developed here for pricing the main real estate derivatives — futures and forward contracts, total return swaps, and options. Accounting for the incompleteness of this market, a suitable modelling framework is outlined that can produce exact formulae, assuming that the market price of risk is known. This framework can accommodate econometric properties of real estate indices such as predictability due to autocorrelations. The term structure of the market price of risk is calibrated from futures market prices on the Investment Property Databank index. The evolution of the market price of risk associated with all five futures curves during 2009 is discussed.

Suggested Citation

  • Frank J. Fabozzi & Robert J. Shiller & Radu S. Tunaru, 2012. "A Pricing Framework for Real Estate Derivatives," European Financial Management, European Financial Management Association, vol. 18(5), pages 762-789, November.
    • Handle: RePEc:bla:eufman:v:18:y:2012:i:5:p:762-789
    DOI: 10.1111/j.1468-036X.2011.00635.x
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    References listed on IDEAS

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    3. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, August.
    4. Xubiao He & Pu Gong, 2020. "A Radial Basis Function-Generated Finite Difference Method to Evaluate Real Estate Index Options," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 999-1019, March.
    5. Steven Kou & Xianhua Peng & Haowen Zhong, 2018. "Asset Pricing with Spatial Interaction," Management Science, INFORMS, vol. 64(5), pages 2083-2101, May.
    6. Rafal M. Wojakowski & M. Shahid Ebrahim & Aziz Jaafar & Murizah Osman Salleh, 2019. "Can Loan Valuation Adjustment (LVA) approach immunize collateralized debt from defaults?," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 28(2), pages 141-158, May.
    7. Frontczak, Robert & Rostek, Stefan, 2015. "Modeling loss given default with stochastic collateral," Economic Modelling, Elsevier, vol. 44(C), pages 162-170.
    8. Dong Zou & Pu Gong, 2017. "A Lattice Framework with Smooth Convergence for Pricing Real Estate Derivatives with Stochastic Interest Rate," The Journal of Real Estate Finance and Economics, Springer, vol. 55(2), pages 242-263, August.
    9. Stanescu, Silvia & Tunaru, Radu & Candradewi, Made Reina, 2014. "Forward–futures price differences in the UK commercial property market: Arbitrage and marking-to-model explanations," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 177-188.
    10. Gong, Pu & Zou, Dong & Wang, Jiayue, 2018. "Pricing and simulation for real estate index options: Radial basis point interpolation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 177-188.
    11. Timothy Kyng & David Pitt & Sachi Purcal & Jinhui Zhang, 2021. "Financial `metrics for comparing Australian retirement villages," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5581-5611, December.
    12. Olivia S. Mitchell, 2018. "Enhancing risk management for an aging world," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 43(2), pages 115-136, September.
    13. Gong, Pu & Dai, Jun, 2017. "Pricing real estate index options under stochastic interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 309-323.
    14. Lionel Sopgoui, 2024. "Modeling the impact of Climate transition on real estate prices," Papers 2408.02339, arXiv.org.
    15. Frank J. Fabozzi & Robert J. Shiller & Radu S. Tunaru, 2020. "A 30-Year Perspective on Property Derivatives: What Can Be Done to Tame Property Price Risk?," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 121-145, Fall.
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