Cash Flow estimation of a Real Estate investment using Monte Carlo
Transcript of Cash Flow estimation of a Real Estate investment using Monte Carlo
Cash Flow estimation of a Real Cash Flow estimation of a Real Estate investment using Monte Estate investment using Monte
Carlo SimulationCarlo Simulation
Student : Student : RalucaRaluca IACOB IACOB Coordinator: Conf. Dr. Laura OBREJA BRASOVEANUCoordinator: Conf. Dr. Laura OBREJA BRASOVEANU
Summary Summary
Introduction Introduction
1.1. Portfolio ValuationPortfolio Valuation2.2. Methods to evaluate cash flowsMethods to evaluate cash flows3.3. Valuation example Valuation example –– Monte Carlo approachMonte Carlo approach4.4. Sensitivity and limitationsSensitivity and limitations5.5. Use of the simulation based approachUse of the simulation based approach
ConclusionConclusion
IntroductionIntroduction
use of simulated cash flows to value assets in use of simulated cash flows to value assets in real estate investment real estate investment
use of Monte Carlo Simulation methods for the use of Monte Carlo Simulation methods for the measurement of complex cash generating measurement of complex cash generating assets such as real estate assets return assets such as real estate assets return distribution distribution
1. Portfolio Valuation1. Portfolio Valuation
Cash Inflows (rents expectation)Cash Inflows (rents expectation)Cash Outflows (expenses expectation)Cash Outflows (expenses expectation)
Free Cash FlowsFree Cash Flows
Discount Rate ChoiceDiscount Rate Choice
ttttt DepWkExpntFCF ))(Re1(
Methods to evaluate Free Cash FlowsMethods to evaluate Free Cash Flows
The classical Discounted Cash Flow The classical Discounted Cash Flow (DCF) approach(DCF) approach
The simulation based approach (using The simulation based approach (using Monte Carlo Simulations)Monte Carlo Simulations)
Monte Carlo SimulationsMonte Carlo Simulations
The methodology is based on the modeling of The methodology is based on the modeling of rents, expenditures, and price dynamics. rents, expenditures, and price dynamics. geometric Brownian motiongeometric Brownian motion
tPPt
t dWdtPdP
0,0597400,0299980,05929050000,0590900,0299930,058640500
0,0576600,0304620,0571901
Number of replications MCm MC MC
We obtain the following estimations:
Valuation exampleValuation example
(0.983694)
(0.889103)(0.781186)(0.690956(0.60796)Standard error
8.7532778.167567.6254267.141226.662412MCSimulation
8.7317788.161297.6261587.124246.653525DCF
FCF5FCF4FCF3FCF2FCF1
Portfolio value at T=0 and T=5 yearsPortfolio value at T=0 and T=5 years
94.31124.28
111.27141.21
Value at time 0 (discounted)Terminal valuePortfolio value
141.23186.01
166.55211.35
Value at 5 years (at time T)Terminal valuePortfolio value
MC SimulationDCFValue / Method
Sensitivity of the DCF approach Sensitivity of the DCF approach vsvs Monte Monte Carlo SimulationsCarlo Simulations
Finally, we notice that the volatility of the Finally, we notice that the volatility of the portfolio dynamics (price and rent) does not portfolio dynamics (price and rent) does not affect the mean of the portfolio value. Only affect the mean of the portfolio value. Only the mean estimator precision is concerned. the mean estimator precision is concerned. Higher the volatility is, smaller the precision.Higher the volatility is, smaller the precision.
Limitations of DCF ValuationLimitations of DCF Valuation
DCF weakness comes overall from the fact DCF weakness comes overall from the fact that DCF valuation does not capture the that DCF valuation does not capture the distributions features of cash flows, and distributions features of cash flows, and cannot serve to value contingent contracts cannot serve to value contingent contracts on the real estate asset. on the real estate asset.
Implications for ValueImplications for Value--atat--Risk (Risk (VaRVaR) in ) in Real Estate FinanceReal Estate Finance
the risk of loss can be considered as the risk of loss can be considered as null for the portfolio in our examplenull for the portfolio in our example
Conclusions Conclusions
Based on a portfolio example, we have Based on a portfolio example, we have shown that simulated cash flowsshown that simulated cash flowsprovide more robust valuations than provide more robust valuations than traditional DCF valuations,traditional DCF valuations,permit the user to estimate the portfoliopermit the user to estimate the portfolio’’s s price distribution for any time horizon,price distribution for any time horizon,facilitate Valuesfacilitate Values--atat--Risk (Risk (VaRVaR) ) computations. computations.