Risk adjusted asset valuation using a probabilistic approach with optimized asking rents and resale timing options

The model developed here provides an enhancement of the traditional DCF asset acquisition valuation template, in Excel. It provides a relatively transparent and user-friendly yet flexible risk-adjusted valuation of a subject individual acquisition, structured to consider the asset either as a core asset or a value-add asset. This study applies a basic stock flow model of space market dynamics to address the question of covariance among input variables. The model is designed with optional probabilistic inputs and historical data for the local space market (employment, rents, net rentable area, occupied space, new completions, vacancy and absorption) and the asset market (cap rates history) to produce a 15-year forecast for the relevant space and asset market for the subject property. An optional optimal rent module in the model uses the forecasted cap rates and consequent opportunity cost of capital to arrive at optimal asking rents for the subject property. The existing rent roll is combined with the future rents and vacancies along with asset level projections of operating costs and capital expenditures to arrive at the cash flow projections. Renewal probability and probability to lease up are major differentiating factors between the core and value add asset. The model also enables the user to optionally consider how flexibility in resale timing can improve the overall return performance from a probabilistic perspective. The output of the model includes an apprehension of the entire going-in risk return relationship, depicted relative to a relevant security market line generated by the input risk free interest rate and the opportunity cost of capital in the relevant asset market. Key words: Probabilistic, risk adjusted valuation, forecast, optimal rent, flexibility, renewal probability, probability to lease up.

Department dc:contributor.department

Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Paradkar, Sarwesh

Advisor dc:contributor.advisor

• David Geltner.

• Center for Real Estate. Program in Real Estate Development.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/84376

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/84376