Mahdi Mokrane

Optimal holding period for a real estate portfolio

This paper considers the use of simulated cash flows to determine the optimal holding period of a real estate portfolio to maximize its present value. The traditional DCF approach with an estimation of the resale value through a growth rate of the future cash flow does not let appear this optimum. However, if the terminal value is calculated from the trend of a diffusion process of the price, an optimum may appear under certain conditions. Finally we consider the sensitivity of the present value to the different parameters involved in the cash flow estimations.

Using rents and price dynamics in real estate portfolio valuation

Purpose – The aim of this paper is to use rent and price dynamics in the future cash flows in order to improve real estate portfolio valuation.Design/methodology/approach – Monte Carlo simulation methods are employed for the measurement of complex cash generating assets such as real estate assets return distribution. Important simulation inputs, such as the physical real estate price volatility estimator, are provided by results on real estate indices for Paris, derived in an article by Baroni et al..Findings – Based on a residential real estate portfolio example, simulated cash flows: provide more robust valuations than traditional DCF valuations; permit the user to estimate the portfolios price distribution for any time horizon; and permit easy values‐at‐risk (VaR) computations.Originality/value – The terminal value estimation is a core issue in real estate valuation. To estimate it, the proposed method is not based on an anticipated growth rate of cash flows but on the estimation of the trend and the ...

A repeat sales index robust to small datasets

As suggested by D. Geltner, commercial properties indices have to be built using repeat sales instead of hedonic indices. The repeat sales method is a means of constructing real estate price indices based on a repeated observation of property transactions. These indices may be used as benchmarks for real estate portfolio managers. But the investors in general are also interested in introducing real estate performance in their portfolio to enhance the efficient frontier. Thus, expected return and volatility are the two key parameters. To create and to improve contracts on real estate indices, trend and volatility of these indices must be robust regarding to the periodicity of the index and the volume of transactions. This paper aims to test the robustness of the trend and volatility estimations for two indices: the classical Weighted Repeat Sales (Case & Shiller 1987) and a PCA factorial index (Baroni, Barthelemy and Mokrane 2007). The estimations are computed from a dataset of Paris commercial properties. The main findings are the trend and volatility estimates are biased for the WRS index and not for the PCA factorial index when the periodicity increases. Consequently, the level of the index at the end of the computing period is significantly different for various periodicities in the case of the WRS index. Globally, the PCA factorial seems to be more robust to the number of transactions. Firstly, we present the two methodologies and then the dataset. Finally we test the impact of the number of transactions per period on the trend and volatility estimates for each index and we give an interpretation of the results.

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

Purpose 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 Poissons 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.