||Modelling uncertain operational cash flows of real estate investments using simulations of stochastic processes
||Andreas Pfnür and Stefan Armonat
||In this paper we apply a numerical simulation of stochastic processes to the problem of real estate investment valuation. In contrast to usually on the income side focussed models in the literature here a focus is put on the uncertain dynamics in real estate operating costs as a key return factor. Those uncertain operating cost will be integrated into an enhanced dy-namic simulation. To model the dynamics in the uncertainty of the cost schedule we use a selection of different types of stochastic processes. Therefore we subdivide the operating costs by costs drivers and determine an appropriate stochastic process for each of the de-rived cost clusters. The application of our model to real world investment situations shows that linear and de-terministic modelling underestimates the risk generating effect of uncertain operating ex-penses, which often can lead to inefficient investment decisions. In a further application of our model we demonstrate the relevant impact of uncertain operating costs to the optimal capital structure of real estate investments. To optimize the capital structure in our applica-tion we use heuristic optimization with genetic algorithms.
|Year of publication:
Andreas Pfnür and Stefan Armonat (2012).
Modelling uncertain operational cash flows of real estate investments using simulations of stochastic processes. 19th Annual European Real Estate Society Conference in Edinburgh, Scotland,