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The Impact of Lease Structures on the Optimal Holding Period for a Commercial Real Estate Portfolio

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Abstract

The purpose of this paper is to exhibit the impacts of lease duration and lease break options on the optimal holding period for a real estate asset or portfolio Methodology / approach We use a Monte Carlo simulation framework to simulate a real estate assets cash-flows in which lease structures (rents indexation patterns overall lease duration and break options) are explicitly taken into account. We assume that a tenant exercises his/her option to break a lease if the rent paid as higher than the market rental value of similar properties. We also model vacancy duration stochastically using Poisson's law. Finally capital values and market rental values are simulated using specific stochastic processes. and are also assumed to be correlated. We derive the optimal holding period for the asset as the value that maximises its discounted value. which is the sum of the discounted free cash flows and the discounted terminal Findings We demonstrate that. consistent with existing capital markets literature and real estate business practice. break-options in leases can dramatically alter optimal holding periods for real estate assets and portfolios by extension. We show that. everything else being equal. shorter lease durations. higher market rental value volatility. increasing negative rental reversion. higher vacancy duration. more break options. all tend to decrease the optimal holding period of a real estate asset. The converse is also true. Practical implications Practitioners are insights as well as a practical methodology for determining the ex-ame optimal holding period for an asset or a portfolio based on a number of market and asset specific parameters including the lease structure. Originality / value The originality of the paper derives from taking an explicit modelling approach to lease duration and lease breaks as additional sources of asset specific risk alongside market risk. This is critical in real estate portfolio management because such specific risk is usually difficult to diversify.

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  • Amédée-Manesme, Charles-Olivier & Baroni, Michel & Barthélémy, Fabrice & Mokrane, Mahdi, 2014. "The Impact of Lease Structures on the Optimal Holding Period for a Commercial Real Estate Portfolio," ESSEC Working Papers WP1413, ESSEC Research Center, ESSEC Business School.
    • Handle: RePEc:ebg:essewp:dr-14013
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    1. Michel Baroni & Fabrice Barthélémy & Mahdi Mokrane, 2007. "Optimal holding period for a real estate portfolio," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 25(6), pages 603-625, October.
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    8. Charles‐Olivier Amédée‐Manesme & Fabrice Barthélémy & Michel Baroni & Etienne Dupuy, 2013. "Combining Monte Carlo simulations and options to manage the risk of real estate portfolios," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 31(4), pages 360-389, July.
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    Cited by:

    1. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy, 2018. "Ex-ante real estate Value at Risk calculation method," Annals of Operations Research, Springer, vol. 262(2), pages 257-285, March.
    2. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
    3. Amédée-Manesme, Charles-Olivier & Barthélémy, Fabrice & Prigent, Jean-Luc, 2016. "Real estate investment: Market volatility and optimal holding period under risk aversion," Economic Modelling, Elsevier, vol. 58(C), pages 543-555.

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    More about this item

    Keywords

    Real estate; Portfolio management; Simulation; Optimal holding period;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • R39 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other

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