Real Estate Price Dynamics and the Value of Flexibility...1 International Meeting of the American...
Transcript of Real Estate Price Dynamics and the Value of Flexibility...1 International Meeting of the American...
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International Meeting of the American Real Estate & Urban Economics Association
Amsterdam, July 5, 2017
Real Estate Price Dynamics and the Value of Flexibility
David Geltner, PhDMassachusetts Institute of Technology
MIT Center for Real Estate
Reference:D.Geltner & R.de Neufville,
“Flexibility & Real Estate Valuation under Uncertainty:A Practical Guide for Developers”
Wiley Blackwell, Forthcoming 2018.
Email me [email protected] if you want an academic paper summary of the book & this lecture.
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Topics:
1) Real Estate Price Dynamics
2) The Value of Investment Resale Timing Flexibility
3) A Typology of Real Estate Development Options
4) (time permitting…) Valuing Timing & Product Options in Development
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Empirical Investment Property Asset Price Indices,Numerous Markets in the USA…
Indices based on market transaction prices of repeat-sales of same properties (Source: Real Capital Analytics, Inc.)
50
150
250
350
450
550
650
2000-12 2001-12 2002-12 2003-12 2004-12 2005-12 2006-12 2007-12 2008-12 2009-12 2010-12 2011-12 2012-12 2013-12 2014-12 2015-12 2016-12
2000
= 1
00
Real Capital Analytics CPPI
National All Types
New York Boroughs Apartment
Manhattan All TypesNYC Apartment
LA CBD West Apartment
Manhattan Apartment
1. RE Price Dynamics
Knowledge of R.E. Price Dynamics Based on:• Historical empirical evidence (Transactions
Prices, Appraisals; Indexes, Residuals)• Economic theory (Capital Mkt theory,
Micro-economic theory)• Common sense
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Typical Stock Market Price Dynamics:Random Walks (simulated)…
Pricing Factors for Five Future 24-year Scenarios, based on the Random Walk
1. RE Price Dynamics
0.0
0.5
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Five Independent Random Future Price Histories (Trials): Stock Market Price Dynamics
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
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Typical Real Estate Price Dynamics:More Complicated (simulated)…
1. RE Price Dynamics
0.0
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Five Independent Random Future Price Histories (Trials): Real Estate Price Dynamics
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
Pricing Factors for Five Future 24-year Scenarios, based on Real Estate Parameters (Random Walk with Autocorrelation, Cyclicality, & Mean Reversion)
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1. RE Price Dynamics
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Five Independent Random Future Price Histories (Trials): Stock Market Price Dynamics
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
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Five Independent Random Future Price Histories (Trials): Real Estate Price Dynamics
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
Same scales…
Both sets are generated from a stochastic process that has 20% annual volatility.
Eight Sources or Components of R.E. Price Dynamics
These 8 ==> Nature & Magnitude of “Uncertainty”
0. Starting from a known observable price…1. Long-term Trend Rate2. Volatility3. Cyclicality4. Mean-reversion5. Inertia (Autoregression)6. Price dispersion (noise)7. Idiosyncratic drift8. Black swans
1. RE Price Dynamics
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Real estate price indexes, & the transaction data they are made from, enable us to identify and quantify eight components of real estate price dynamics or randomness in the way property asset prices evolve over time. Here you can see six of them: (1) The long-term trend rate…
1. RE Price Dynamics
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Real estate price indexes, & the transaction data they are made from, enable us to identify and quantify eight components of real estate price dynamics or randomness in the way property asset prices evolve over time. Here you can see six of them:(1) The long-term trend rate; (2) Short-term volatility (that accumulates)…
1. RE Price Dynamics
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Real estate price indexes, & the transaction data they are made from, enable us to identify and quantify eight components of real estate price dynamics or randomness in the way property asset prices evolve over time. Here you can see six of them: (1) The long-term trend rate; (2) Short-term volatility; (3) Cyclicality; & (4) Mean Reversion…
Mid-Cycle to Mid-Cycle 2001-1615 yrs
1. RE Price Dynamics
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0
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Dec
-69
Dec
-71
Dec
-73
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Dec
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-11
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-15
*(Sources: Moody's/REAL, Moody's/RCA, TBI, Author's estimates.)
Index of Long-term History of U.S. Institutional Commercial Real Estate Same-property Transaction Prices: 2000 = 100 (nominal $)
This longer term historical price index shows the cycles in commercial (investment) property more completely…
Pk-Pk 1971-8716 yrs
Pk-Pk 1987-200720 yrs
Trgh-Trgh 1975-9217 yrs
Trgh-Trgh 1992-200917 yrs
1. RE Price Dynamics
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Real estate price indexes, & the transaction data they are made from, enable us to identify and quantify eight components of real estate price dynamics or randomness in the way property asset prices evolve over time. Here you can see six of them : (1) The long-term trend rate; (2) Short-term volatility; (3) Cyclicality; & (4) Mean Reversion;& (5) Inertia (momentum, Autoregression: AR(1))…
1. RE Price Dynamics
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Summarizing up to here:1) Mkt Trend ≈ 1-2%/yr < Infla (real depr in structures) Secular trends, Real Growth, Deprec, Infla.2) Mkt Volatility ≈ 10-15%/yr. Mkt Informational Efficiency, News Arrival.3) Mkt Cycle ≈ 10-20 yrs, amplitude 50% of mean. Sup/Dem (space), Capital Flows (asset mkt).4) Mean Reversion ≈ 0.2-0.4 . Bldg structure is produced good (supply elasticity), Fdtl real values.5) Mkt AR(1) ≈ 0.2-0.4 (annual freq). Lack of perfect info efficiency, Sluggish price discovery.
Mid-Cycle to Mid-Cycle 2001-1615 yrs
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We can quantify: 48% ≈ exp(sqrt(2*.15^2 + 6*.12^2))-1(Mkt (index) volatility is 15%/yr. The values 2*.152 & .122 are intercept & coefficient from regression of repeat-sales model residuals-
squared onto time-between-sales. Deal noise twice: once each at buy & sell.)
Preceding are features of the market as whole (aggregate prices). A sixth type of uncertainty, primarily in individual assets or metro markets: Idiosyncratic drift of individual assets or market cumulatively away from overall average…
1. RE Price Dynamics
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Mor
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Actual Sale Price Minus TBI Predicted Value (% of Sale Price)
Histogram of TBI Sales Price Prediction Error
Std Dev = +/- 15%Avg Absolute Diff = 11.1%
A seventh type of uncertainty in individual assets: Price Dispersion of actual prices around predicted price…
TBI model is very good predictor of asset prices… Starts out with professional appraisal of each property, then improves on that with regression model of actual transaction prices to eliminate appraisal lag…
1. RE Price Dynamics
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Actual Pct Change Dispersion Around Index
Histogram of CPPI Individual Properties Round-Trip (avg 6 yrs hold) Price Cumulative % Change Dispersion Around Market (Index)
Std Dev = +/- 48%Avg Absolute Diff = 33%
This histogram reflects a combination of the sixth and seventh sources of uncertainty: Pricing Noise & Idiosyncratic Drift.
Quantification: 48% ≈ exp(sqrt(2*.15^2 + 6*.12^2))-1(Mkt (index) volatility is 15%/yr. The values 2*.152 & .122 are intercept & coefficient from regression of repeat-sales model residuals-
squared onto time-between-sales. Deal noise twice: once each at buy & sell.)
1. RE Price Dynamics
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Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
aka “fat tail” events:e.g., Financial crisis of Oct 2008-Mar2009…
The eighth type of uncertainty: “Black Swans,” Unpredictable major jumps affecting all assets…
1. RE Price Dynamics
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Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
Reviewing the Types of Uncertainty seen in the History of REIT share prices…
(1) Long-term avgdrift rate
(8) “fat tail” events:e.g., Financial crisis of Oct 2008-Mar 2009…
1. RE Price Dynamics
0.0
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Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
(2) MktVolatility
Reviewing the Types of Uncertainty seen in the History of REIT share prices…
(8) “fat tail” events:e.g., Financial crisis of Oct 2008-Mar 2009…
(1) Long-term avgdrift rate
1. RE Price Dynamics
0.0
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Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
(3) Long-run cycle &(4) Mean-Reversion
(2) MktVolatility
Reviewing the Types of Uncertainty seen in the History of REIT share prices…
(8) “fat tail” events:e.g., Financial crisis of Oct 2008-Mar 2009…
(1) Long-term avgdrift rate
1. RE Price Dynamics
0.0
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Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
(7)IdioDrift
+ (5) Inertia & (6) Dispersion not depicted here as does not exist in stock mkt (but does in priv mkt)
Reviewing the Types of Uncertainty seen in the History of REIT share prices…
(8) “fat tail” events:e.g., Financial crisis of Oct 2008-Mar 2009…
(3) Long-run cycle
(2) MktVolatility
(1) Long-term avgdrift rate
1. RE Price Dynamics
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Topics:
1) Real Estate Price Dynamics
2) The Value of Investment Resale Timing Flexibility
3) A Typology of Real Estate Development Options
4) (time permitting…) Valuing Timing & Product Options in Development
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Expected Cash Flows: Totals: Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 10 Year 11
Projected Operations (Realistic Assumptions):Potential Gross Income (PGI) 100.00 102.00 104.04 106.12 108.24 110.41 112.62 114.87 117.17 119.51 121.90Vacancy Allowance 5.00 5.10 5.20 5.31 5.41 5.52 5.63 5.74 5.86 5.98 6.09Effective Gross Income 95.00 96.90 98.84 100.81 102.83 104.89 106.99 109.13 111.31 113.53 115.80Operating Expenses 35.00 35.70 36.41 37.14 37.89 38.64 39.42 40.20 41.01 41.83 42.66Net Operating Income (NOI) 60.00 61.20 62.42 63.67 64.95 66.24 67.57 68.92 70.30 71.71 73.14Capital Improvement Expenditures 10.00 10.20 10.40 10.61 10.82 11.04 11.26 11.49 11.72 11.95 12.19Net Cash Flow from Operations (PBTCF) 50.00 51.00 52.02 53.06 54.12 55.20 56.31 57.43 58.58 59.75 60.95PBTCF from Reversion 1218.99PBTCF Total (Including Reversion) 50.00 51.00 52.02 53.06 54.12 55.20 56.31 57.43 58.58 1278.75Time 0 PV @ OCC 1000.00Projected IRR @ Mkt Val Price 7.00% -1000.00 50.00 51.00 52.02 53.06 54.12 55.20 56.31 57.43 58.58 1278.75
The Starting Point:The classical 10-year DCF Valuation Pro-forma…
(Only make it realistic – no )Here, a simple rental property:
Key ideas:• Start from ubiquitous existing practice;• Practitioners have good knowledge about ex ante likely future
cash flows (once you give “haircut” to make realistic);• This “Base Case” or “original pro-forma” is realistic and
unbiased, hence, good estimates of means (prob expectations) of future CFs.
• Classic is “single-stream” (just one future…)
Pro-forma PV = $1000 (=MktVal); Going-in IRR = 7.00% (=OCC)
2. Value of Resale Flex
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Represent possible future ex post deviations from ex ante projection (single-stream) by use of
“Pricing Factors”…Ratio by which we multiply the original pro-forma cash flow expectation to arrive at a future cash flow outcome in a given scenario
Future Scenario Cash Flow Outcome = (Classical Pro-Forma Cash Flow) X (Pricing Factor)
Example:Base Case Pro-forma Year “t” CF = $100.Optimistic Scenario Year “t” CF = $110.
Represent by Price Factor = 1.10:Optimistic Yr.t CR = BaseCase*PF = $100*1.10 = $110.
2. Value of Resale Flex
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Model realistic real estate pricing factors this way, Represent possible future “scenarios” (outcomes)…
0.0
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Five Independent Random Future Price Histories (Trials): Real Estate Price Dynamics
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
Pricing Factors for Five Future 24-year Scenarios, based on Real Estate Parameters (Random Walk with Autocorrelation, Cyclicality, & Mean Reversion)
2. Value of Resale Flex
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• Each future scenario we randomly generate (using probability based Pricing Factors) is an equally possible “future history” (a “trial” in MC terms).
• In the real world, as the future happens (becoming the present fleetingly and then the past permanently), there is only one actual history.
• Prior to the future happening, as far as we know in the present, there are many possible futures that could happen.
• They are governed by our estimated probability distributions and pricing dynamics assumptions. This is the nature of uncertainty.
Monte Carlo Simulation to represent uncertainty in future ex post DCF Property Valuation (ex ante)…
2. Value of Resale Flex
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Monte Carlo Simulation to represent uncertainty in future ex post DCF Property Valuation (ex ante)…• Each future scenario we randomly generate (using
probability based Pricing Factors) is an equally possible “future history” (a “trial” in MC terms).
• Generate many such scenarios (we use 10,000 for teaching purposes in Excel; you could do more).
• Integrate across all (e.g., 10,000) outcomes.• Relative frequency of simulated ex post outcomes
(fraction of 2000) is “sample probability” density.• It’s an estimate of actual underlying outcome
probability distribution, hence, estimate of:• Ex Ante Probability of Outcomes (quantification of
uncertainty: turning “unknown unknowns” into “known unknowns”, replacing “uncertainty” with “risk”).
2. Value of Resale Flex
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0%
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$0 $200 $400 $600 $800 $1,000 $1,200 $1,400 $1,600 $1,800 $2,000
Sam
ple
Prob
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Time 0 PV @ OCC
PV Frequency Distribution Function(across 2,000 simulated project outcomes
Inflexible PV Distn Inflexible Mean PV Pro-forma PV
Effect of Uncertainty, Without Flexibility:Risk in property’s Time 0 PV
(ex post, discounted to Time 0 @ OCC)
Monte Carlo E[PV(CFs)] = PV(E[CFs]) Pro-forma“PV is a Linear Function of CFs”
E[PV] = $1000 = Pro-forma PV
2. Value of Resale Flex
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Risk in property’s Time 0 IRR (ex post, @ $1000 price at Time 0)
0%
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-4% -2% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18%
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Realized IRR
IRR Frequency Distribution Function(across 2,000 simulated project outcomes)
Inflexible IRR Distn Inflexible Mean IRR Pro-forma ex ante IRR
E[IRR] < 7% = Pro-forma IRR
2. Value of Resale Flex
Ex Post IRR is symmetric probability distribution (not skewed), butIRR is Concave Function of PV E[IRR(CFs)] < IRR(E[CFs])
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-5%
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0 500 1,000 1,500 2,000 2,500
IRR
Inflexible Ex Post PV Outcome
IRR by Ex Post PV @ $1000 Price, Inflexible Case
2. Value of Resale Flex
Ex Post IRR is symmetric probability distribution (not skewed), butIRR is Concave Function of PV E[IRR(CFs)] < IRR(E[CFs])
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PV has skewed distribution but unbiased in Proforma.IRR has symmetric distribution but biased in Proforma.
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$0 $200 $400 $600 $800 $1,000 $1,200 $1,400 $1,600 $1,800 $2,000
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Time 0 PV @ OCC
PV Frequency Distribution Function(across 2,000 simulated project outcomes
Inflexible PV Distn Inflexible Mean PV Pro-forma PV
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Realized IRR
IRR Frequency Distribution Function(across 2,000 simulated project outcomes)
Inflexible IRR Distn Inflexible Mean IRR Pro-forma ex ante IRR
Uncertainty Without Flexibility…2. Value of Resale Flex
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Modeling flexibility in resale timing:Can sell before 10 yrs, or after…
“Stop-Gain” Flexible Resale Decision Rule:Sell as soon as market prices are >= 20% above Base
Case (pro-forma) projection for any given year.
This type of rule is sometimes proposed for stock market investments, but it is controversial and does not systematically work well in simulations, because stocks follow Random Walk.But real estate has Momentum & Cycles & Mean-Reversion…
Example:Base Case Pro-forma Year “t” CF = $100.
In a given random future scenario Year “t” CV = $121.Then Sell! (not before or after).
2. Value of Resale Flex
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• Don’t be “too greedy”.
• Mean-reversion: If it goes up, it’s got to come down.
• Cyclicality: If it goes up, it’s got to come down…
What is the idea behind the Stop-Gain Rule?2. Value of Resale Flex
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Flexible ReSale Timing with Stop-Gain @ 20% over Base Case:Typical Cumulative Sample Probability Function, Target: PV
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PV Cumulative Distribution Function: Stop-Gain Rule @ Input Price Factor
(across 2,000 simulated project outcomes)
Flexible PV Distn Flexible Mean PV Inflexible PV DistnInflexible Mean PV Pro-forma PV
E[PV] ≈ $1250 = 25% grtr than
MktVal (pro-forma DCF) or Inflex
2. Value of Resale Flex
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0%
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Realized IRR
IRR Cumulative Distribution Function: Stop-Gain Rule @ Input Price Factor
(across 2,000 simulated project outcomes)
Flexible IRR Distn Flexible Mean IRR Inflexible IRR DistnInflexible Mean IRR Pro-forma ex ante IRR
Flex E[IRR] ≈ 14% > 6.6% ≈ Inflex E[IRR]Versus 7% pro-forma OCC
Flexible ReSale Timing with Stop-Gain @ 20% over Base Case:Typical Cumulative Sample Probability Function, Target: IRR
2. Value of Resale Flex
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Time 0 PV @ OCC
PV Frequency Distribution Function(across 2,000 simulated project outcomes.) Note: Compare shapes & locations, not integral areas.
Flexible PV Distn Flexible Mean PV Inflexible PV Distn Inflexible Mean PV Pro-forma PV
E[PV] ≈ $1250 = 25% grtr than MktVal (pro-forma DCF)
Flexible ReSale Timing with Stop-Gain @ 20% over Base Case:Typical Sample Probability Density (Frequency) Function, Target: PV
2. Value of Resale Flex
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Flex E[IRR] ≈ 14% > 6.6% ≈ Inflex E[IRR]Versus 7% pro-forma OCC
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Realized IRR
IRR Frequency Distribution Functions on Same Scale(across 2,000 simulated project outcomes)
Flexible IRR Distn Flexible Mean IRR Inflexible IRR Distn Inflexible Mean IRR Pro-forma ex ante IRR
Flexible ReSale Timing with Stop-Gain @ 20% over Base Case:Typical Sample Probability Density (Frequency) Function, Target: IRR
2. Value of Resale Flex
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PV Simulation ResultsFlex Inflex
Mean $1,265 $1,00095%ile $1,656 $1,424
Median $1,255 $9605%ile $884 $702
Std Deviation $228 $228mean/Std Deviation 5.55 4.40
Mean Holding Period (yrs) 9.28 10.00Proportion Inflex>Flex 0.19Proportion Flex>Inflex 0.76
Std Err of Difference 6.95
IRR Simulation ResultsFlex Inflex
Mean 14.34% 6.58%95%ile 34.70% 11.50%
Median 10.75% 6.46%5%ile 5.90% 2.09%
Std Deviation 9.10% 2.92%mean/Std Deviation 1.57 2.26
RiskPrem/DnSideStdDev 2.43 1.79Proportion Flex<Inflex 0.15Proportion Flex>Inflex 0.80
Typical Simulation Output Statistics:2. Value of Resale Flex
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Flexible Resale does not always beat Inflexible 10-yr(But it usually does…)
-$1,500
-$1,000
-$500
$0
$500
$1,000
$1,500
0 500 1000 1500 2000 2500
Diff
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lexi
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-Inf
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Inflexible PV Outcome
Flexible Minus Inflexible PV Outcomes Difference As Function of Inflexible PV
Scatterplot: Each dot is one of 10,000 outcome scenarios
2. Value of Resale Flex
Downward shape of the cloud ==> Flexibility helps most in downside outcomes.
40Scatterplot: Each dot is one of 2000 outcome scenarios
-20%
-10%
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Inflexible IRR Outcome
Flexible Minus Inflexible IRR Outcomes Difference As Function of Inflexible IRR
2. Value of Resale Flex
Flexible Resale does not always beat Inflexible 10-yr(But it usually does…)
Downward shape of the cloud ==> Flexibility helps most in downside outcomes.
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2. Value of Resale FlexStabilized Asset Flexible Resale Timing Effect:
Sensitivity Analysis of Various Price Dynamics and Decision Rule Assumptions on the Mean Valuation & IRR Outcomes
0.90
1.00
1.10
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1.30
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1.50
Lowest Lower Base Higher Highest
Analysis Input Parameter Values
Resale Timing: Ex Post Mean Present Value Ratio Flexible / Inflexible
1: Vol & Noise
2: Auto & Revert
3: Cyc Ampli
4: All Four
5: Cyc Period
6: Cyc Phase
7: Trigger
9: StkMktVol
10: StkMktTrig
-5%
0%
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15%
20%
Lowest Lower Base Higher Highest
Analysis Input Parameter Values
Resale Timing: Ex Post Mean IRR Difference: Flexible - Inflexible
1: Vol & Noise
2: Auto & Revert
3: Cyc Ampli
4: All Four
5: Cyc Period
6: Cyc Phase
7: Trigger
9: StkMktVol
10: StkMktTrig
Valuation finding appears pretty unbiased and robust.
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• Can you for sure commit to, implement Stop-Gain @ 20%?
• Will you have sufficient information?
• What if you care more about the IRR Std Dev?
• Simulation valuation is relevant for “Private Value”(or “Investment Value” ) of particular Decision Maker.
• Distinct from “Market Value” (MV).
Why is Mkt Val $1000, not $1250?...What is the $1250 PV if not Mkt Val?...
2. Value of Resale Flex
43
Expected Cash Flows: Totals: Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 10 Year 11
Projected Operations (Realistic Assumptions):Potential Gross Income (PGI) 100.00 102.00 104.04 106.12 108.24 110.41 112.62 114.87 117.17 119.51 121.90Vacancy Allowance 5.00 5.10 5.20 5.31 5.41 5.52 5.63 5.74 5.86 5.98 6.09Effective Gross Income 95.00 96.90 98.84 100.81 102.83 104.89 106.99 109.13 111.31 113.53 115.80Operating Expenses 35.00 35.70 36.41 37.14 37.89 38.64 39.42 40.20 41.01 41.83 42.66Net Operating Income (NOI) 60.00 61.20 62.42 63.67 64.95 66.24 67.57 68.92 70.30 71.71 73.14Capital Improvement Expenditures 10.00 10.20 10.40 10.61 10.82 11.04 11.26 11.49 11.72 11.95 12.19Net Cash Flow from Operations (PBTCF) 50.00 51.00 52.02 53.06 54.12 55.20 56.31 57.43 58.58 59.75 60.95PBTCF from Reversion 1218.99PBTCF Total (Including Reversion) 50.00 51.00 52.02 53.06 54.12 55.20 56.31 57.43 58.58 1278.75Time 0 PV @ OCC 1000.00Projected IRR @ Mkt Val Price 7.00% -1000.00 50.00 51.00 52.02 53.06 54.12 55.20 56.31 57.43 58.58 1278.75
The Starting Point:The classical 10-year DCF Valuation Pro-forma…
(Only make it realistic – no )
Here, a simple rental property:
For management purposes (not just Mkt Val estimation), does this “single-stream” DCF look pretty lame compared to explicit
consideration of both uncertainty and flexibility?...
Pro-forma PV = $1000 (=MktVal); Going-in IRR = 7.00% (=OCC)
2. Value of Resale Flex
44
Topics:
1) Real Estate Price Dynamics
2) The Value of Investment Resale Timing Flexibility
3) A Typology of Real Estate Development Options
4) (time permitting…) Valuing Timing & Product Options in Development
45
Typology of RED Flexibility Options
1. Project Delay Option: Choose when to start project (land value call option, may equally be viewed as “put”).
2. Buildout Modular Production Timing Option: Start & stop (pause) project at any time and recommence later (or abandon).
3. Phasing Option: Parallel (independent) or Sequential. Once started, phase must be completed, but start of any phase can be delayed indefinitely (or ultimately abandoned).
4. Product Mix Switching Option: Build alternate real estate “products” (style, type, tenure; e.g.: 1Br vs 2BR, Apt vs Hotel, Rental vs Condo), substitute one for another.
5. Expansion Options: Horizontal (requires land bank), or vertical (requires design & permitting features).
3. Typology of Dvlpt Options
46
Typology of RED Flexibility Options
1. Project Delay Option: Choose when to start project (land value call option, may equally be viewed as “put”).
2. Buildout Modular Production Timing Option: Start & stop (pause) project at any time and recommence later (or abandon).
3. Phasing Option: Parallel (independent) or Sequential. Once started, phase must be completed, but start of any phase can be delayed indefinitely (or ultimately abandoned).
4. Product Mix Switching Option: Build alternate real estate “products” (style, type, tenure; e.g.: 1Br vs 2BR, Apt vs Hotel, Rental vs Condo), substitute one for another.
5. Expansion Options: Horizontal (requires land bank), or vertical (requires design & permitting features).
Def
ensi
ve O
ptio
nsB
oth
Off
ensi
ve3. Typology of Dvlpt Options
47
Ch.15 Target Curves Characteristic of Puts & Calls…D
efen
sive
Opt
ions
Off
ensi
ve3. Typology of Dvlpt Options
48
Typology of RED Flexibility Options
1. Project Delay Option: Choose when to start project (land value call option, may equally be viewed as “put”).
2. Buildout Modular Production Timing Option: Start & stop (pause) project at any time and recommence later (or abandon).
3. Phasing Option: Parallel (independent) or Sequential. Once started, phase must be completed, but start of any phase can be delayed indefinitely (or ultimately abandoned).
4. Product Mix Switching Option: Build alternate real estate “products” (style, type, tenure; e.g.: 1Br vs 2BR, Apt vs Hotel, Rental vs Condo), substitute one for another.
5. Expansion Options: Horizontal (requires land bank), or vertical (requires design & permitting features).
InO
n3. Typology of Dvlpt Options
49
Typology of RED Flexibility Options
1. Project Delay Option: Choose when to start project (land value call option, may equally be viewed as “put”).
2. Buildout Modular Production Timing Option: Start & stop (pause) project at any time and recommence later (or abandon).
3. Phasing Option: Parallel (independent) or Sequential. Once started, phase must be completed, but start of any phase can be delayed indefinitely (or ultimately abandoned).
4. Product Mix Switching Option: Build alternate real estate “products” (style, type, tenure; e.g.: 1Br vs 2BR, Apt vs Hotel, Rental vs Condo), substitute one for another.
5. Expansion Options: Horizontal (requires land bank), or vertical (requires design & permitting features).
Tim
ing
Opt
ions
Prod
uct O
ptio
ns3. Typology of Dvlpt Options
50
In next section consider these three only…
1. Project Delay Option: Choose when to start project (land value call option, may equally be viewed as “put”).
2. Buildout Modular Production Timing Option: Start & stop (pause) project at any time and recommence later (or abandon).
3.
4. Product Mix Switching Option: Build alternate real estate “products” (style, type, tenure; e.g.: 1Br vs 2BR, Apt vs Hotel, Rental vs Condo), substitute one for another.
5.
Tim
ing
Opt
ions
Prod
uct O
ptio
ns3. Typology of Dvlpt Options
51
Topics:
1) Real Estate Price Dynamics
2) The Value of Investment Resale Timing Flexibility
3) A Typology of Real Estate Development Options
4) (time permitting…) Valuing Timing & Product Options in Development
52
Central Tendencies of Simulated Ex Post Development Project Present Value & IRR,Comparison of Three Types of Flexibility Individually & in Combination…
3. Typology of Dvlpt Options
Performance Metric:NPV Percent of
Land Value Internal Rate of ReturnMean Completion
Delay (Yrs)Start Delay Flexibility Only 21.5% 8.2% 1.9
Buildout Delay Flexibility Only 13.0% 7.8% 5.3Switch Option Only 13.6% 5.8% 0.0Start+BldOut Only 21.4% 9.0% 6.2Start+Switch Only 33.8% 12.0% 1.5
BldOut+Swicth Only 25.7% 11.1% 4.1All Three Options 33.9% 12.4% 4.8
Simulated Ex Post Mean Performance Differential, Flexible Minus Inflexible:
Main Results:Flexibility…• Adds 13-34% to project value (land bid-price)• Timing (delay) options are redundant within themselves• Timing & product (delay & type-switching) options are
additive• Modular production delay option (after project start)
may add significantly to project completion time.
53
Right-shift in left-hand tail ==> Downside protection.Average 21% project value (land bid-price) improvement, 1.9 yr completion delay.
3. Typology of Dvlpt Options
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
-400,000 -300,000 -200,000 -100,000 0 100,000 200,000 300,000 400,000 500,000 600,000
Sam
ple
Prob
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(Fr
eque
ncy)
Ex Post NPV @ Given Discount Rate (USD 000s)
NPV Frequency Distribution Function Net of $200M Land Price(across 10,000 simulated project outcomes.)
NPV - Start Delay Only NPV - No Flexibility Pro-forma PV
Mean NPV - Start Delay Only Mean NPV - No Flexibility
0%
5%
10%
15%
20%
25%
30%
35%
-80% -60% -40% -20% 0% 20% 40% 60% 80% 100%
Sam
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Prob
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(Fre
quen
cy)
Realized Future IRR @ Given Land Price
IRR Frequency Distribution Function at $200M Land Price(across 10,000 simulated project outcomes)
IRR - Start Delay Only IRR - No Flexibility Pro-forma IRR
Mean IRR - Start Delay Only Mean IRR - No Flexibility
Simulated Ex Post Distributions of Development Project Present Value & IRR,Comparison of Start Delay Flexibility Only (blue) versus Inflexible Base Plan (orange)
54
3. Typology of Dvlpt Options
Simulated Ex Post Distributions of Development Project Present Value & IRR,Comparison of Modular Buildout Delay Flexibility Only (blue) versus Inflexible Base
Plan (orange)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
-400,000 -300,000 -200,000 -100,000 0 100,000 200,000 300,000 400,000 500,000 600,000
Sam
ple
Prob
abili
tyDe
nsity
(Fr
eque
ncy)
Ex Post NPV @ Given Discount Rate (USD 000s)
NPV Frequency Distribution Function Net of $200M Land Price(across 10,000 simulated project outcomes.)
NPV - BldOut Option Only NPV - No FlexibilityPro-forma PV Mean NPV - BldOut Option OnlyMean NPV - No Flexibility
0%
5%
10%
15%
20%
25%
30%
35%
-80% -60% -40% -20% 0% 20% 40% 60% 80% 100%
Sam
ple
Prob
abili
tyDe
nsity
(Fre
quen
cy)
Realized Future IRR @ Given Land Price
IRR Frequency Distribution Function at $200M Land Price(across 10,000 simulated project outcomes)
IRR - BldOut Option Only IRR - No FlexibilityPro-forma IRR Mean IRR - BldOut Option OnlyMean IRR - No Flexibility
Right-shift in left-hand tail ==> Downside protection.Average 13% project value (land bid-price) improvement, 5.3 yr completion delay.
55
Right-shift in both tails & center ==> Downside protection + Upside opportunity.Average 14% project value (land bid-price) improvement, 0 yr completion delay.
3. Typology of Dvlpt Options
Simulated Ex Post Distributions of Development Project Present Value & IRR,Comparison of Switching Option Only (blue) versus Inflexible Base Plan (orange)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
-400,000 -300,000 -200,000 -100,000 0 100,000 200,000 300,000 400,000 500,000 600,000
Sam
ple
Prob
abili
tyDe
nsity
(Fr
eque
ncy)
Ex Post NPV @ Given Discount Rate (USD 000s)
NPV Frequency Distribution Function Net of $200M Land Price(across 10,000 simulated project outcomes.)
NPV - Switch Option Only NPV - No FlexibilityPro-forma PV Mean NPV - Switch Option OnlyMean NPV - No Flexibility
0%
5%
10%
15%
20%
25%
30%
35%
-80% -60% -40% -20% 0% 20% 40% 60% 80% 100%
Sam
ple
Prob
abili
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nsity
(Fre
quen
cy)
Realized Future IRR @ Given Land Price
IRR Frequency Distribution Function at $200M Land Price(across 10,000 simulated project outcomes)
IRR - Switch Option Only IRR - No FlexibilityPro-forma IRR Mean IRR - Switch Option OnlyMean IRR - No Flexibility
56
Right-shift in both tails but especially left ==> Both downside protection & upside opportunities, but especially downside protection.
Average 34% project value (land bid-price) improvement, 4.3 yr completion delay.
3. Typology of Dvlpt Options
Simulated Ex Post Distributions of Development Project Present Value & IRR,Comparison of All Three Options Together (blue) versus Inflexible Base Plan (orange)
0%
5%
10%
15%
20%
25%
30%
35%
-80% -60% -40% -20% 0% 20% 40% 60% 80% 100%
Sam
ple
Prob
abili
tyDe
nsity
(Fre
quen
cy)
Realized Future IRR @ Given Land Price
IRR Frequency Distribution Function at $200M Land Price(across 10,000 simulated project outcomes)
IRR - All 3 Options IRR - No Flexibility Pro-forma IRR
Mean IRR - All 3 Options Mean IRR - No Flexibility
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
-400,000 -300,000 -200,000 -100,000 0 100,000 200,000 300,000 400,000 500,000 600,000
Sam
ple
Prob
abili
tyDe
nsity
(Fr
eque
ncy)
Ex Post NPV @ Given Discount Rate (USD 000s)
NPV Frequency Distribution Function Net of $200M Land Price(across 10,000 simulated project outcomes.)
NPV - All 3 Options NPV - No Flexibility Pro-forma PV
Mean NPV - All 3 Options Mean NPV - No Flexibility