Work detail

Risk model for real estate assets: Analysis and development

Author: Mgr. Klára Koubková
Year: 2015 - summer
Leaders:
Consultants:
Work type: Finance, Financial Markets and Banking
Masters
Language: English
Pages: 79
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/134244/
Abstract: The main aim of this thesis is to design a new and more advanced methodology for valuation of real
estate portfolios and incorporate uncertainty into the valuation process. From the comprehensive real
estate literature we identified the main value drivers whose treatment is often neglected in the
traditional appraisal methodology as they are used as a single point estimates. The identified
parameters are the discount rate, inflation, prime rent, occupancy and market capital value changes.
In contrast with the traditional approach, we calibrate distributions of these parameters from historical
data and allow their variation through the Monte Carlo simulation. This enables us to model their
impact on the market value of our real estate portfolio, which comprises of A-class office buildings with
detailed property level data including their lease structure. The methodology presented here builds on
the widely used DCF approach, which is augmented by the risk parameters and through the
thousands of iterations of the Monte Carlo simulation we arrive to a distribution of all potential values
of the portfolio. Finally, the knowledge of relevant risk factors and their impact on returns of their
property portfolio then provides investors with better and more reliable foundations for their decisions
and understanding of the markets. It is also a valuable tool for them to monitor their portfolio, evaluate
its key risk and return parameters and predict possible future developments, including up to date VaR
based on the current market development.

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CRIF
McKinsey
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