© 2014 oncourse learning. all rights reserved. chapter 26 real estate investment management and...

© 2014 OnCourse Learning. All Rights Reserved. 1

Chapter 26

Real Estate Investment Management and Derivatives


CHAPTER OUTLINE26.1 Macro-Level Investment Performance Attribution

26.1.1 The Importance of Property-Level Investment Management

26.1.2 Macro Property-Level Performance Attribution and the Four Fundamental Responsibilities

26.1.3 Portfolio-Level Performance Attribution

26.1.4 Use of a Benchmark in Performance Attribution

26.1.5 The Case for Using Manager Allocation Weights in the Benchmark

26.2 Investment Performance Evaluation and Benchmarking26.2.1 The Basic Idea

26.2.2 Benchmarks and Investment Styles in the Private Real Estate Asset Class

26.3 Real Estate Derivatives26.3.1 How Index Swaps Can Be Used and Priced

26.3.2 The Broader Potential Role of Index Derivatives

26.3.3 Solving the Index Problem

26.4 Chapter Summary


LEARNING OBJECTIVES

After reading this chapter, you should understand:What is meant by investment performance attribution at

both the macro property level and the portfolio level.How to quantify segment allocation versus asset

selection effects in a portfolio’s differential performance relative to an appropriate benchmark.

What are the major institutional real estate investment management “styles” and how these may be accounted for in quantitative investment performance evaluation.

The new concept of real estate equity index derivatives and how such products might be used in real estate investment management.


26.1.1: Importance of Property-Level Investment Management

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Moody's/RCA CPPI & Price Paths of 10 Last-sold Property Investments as of June 2012*

*Pegged to starting value on index at time of prior sale (buy), then tracked at constant rate per month to ultimate sale price deviation at disposition in June 2012.

Individual property investment performance varies widely around the market average performance. How well you do can depend on your individual property-level (“idiosyncratic”) performance.


Macro-Level Investment Policy Analysis:• Strategic Investment Decision Making:

- Long-run objectives & plan:- Chapter 21 (Portf Theory) Basic methodology.- Chapter 22 (Equilibr Models) Rational expectations to apply MPT.

• Tactical Investment Policy:- Short/medium term actions (opportunistic):- Chapter 22 (Equilibr Models) Find mis-priced assets.

• Policy Implementation:- Investment management:- Chapter 26 (Perf. Attrib., Benchmarking).- Chapter 22 (Equilibr Models) Risk-adjustment for perf. Attrib.- Most relevent for private direct investment - Also relevant for REIT mgt to consider, as REITs can be viewed as mgrs

of direct priv R.E. investments on behalf of stockholders.


DEFINITION: The formal (quantitative) comparison of a given investment agent’s (or portfolio’s) investment performance with that of a suitably defined index or peer group, over a specified time period.

EXAMPLE:• A large-cap stock manager is “benchmarked against the

S&P500”• Manager averages a 10% return over a 3-yr mgt contract

period• S&P500 averages 12% over the same period• Manager has some “explaining” to do.

What is“Benchmarking” ?


DEFINITION: The decomposition of the total investment performance into additive components so as to “attribute” the total performance to sources that may reflect various investment management functions.

EXAMPLE:• Manager 10% vs NCREIF 12%, but…• If mgr had allocated among different property types in same

proportion as NCREIF Index, then mgr would have earned 13%: Mgr relative good at individual asset “selection”; Source of poor relative performance must be

“allocation” across property type market segments.

What is“Performance Attribution” ?


Some historical Perspective• MPT (1950s & 60s)

• CAPM (1960s & 70s)Invstmt Mgt Perf.Eval: “Risk-adjusted returns”:

“Jensen’s Alpha,” “Sharpe Ratio,” “Treynor Ratio.”

• Disillusionment with CAPM (1980s & 90s): Going beyond “beta” to explain expected returns: Size, B/M Ratio,

• “Style” oriented invstmt strategy (1980s & 90s):Style-based benchmarking as an invstmt mgt tool,

consistent with style-based portfolio strategy.

• Property “Crash” of early 1990s:Benchmarking expands from equities to R.E. (1990s).


Lecture Outline

26.1. Performance Attribution

26.2. Basics of Benchmarking

26.2 (cont.). Issues in Benchmarking Private Real Estate


26.1. Macro-level Investment Performance Attribution

• Definition & Overview• 26.1.3. Portfolio-Level Performance

Attribution• 26.1.2 Property-Level Performance

Attribution


DEFINITION: The decomposition (or “breaking down,” or “parsing”) of the total investment return of a subject property or portfolio of properties (or an investment manager).

PURPOSE:To assist with the diagnosis and understanding of what caused the given investment performance.

USAGE:By investment managers (agents) and their clients (principals).REIT managers also could use.

Performance Attribution Overview


Portfolio levelPertains to dynamic portfolios or investment manager (or

fund) level. Property level

Pertains to individual properties or static portfolios of multiple properties.


Two levels at which performance attribution is performed:


Major attributes (return components):

At the PORTFOLIO LEVEL:AllocationSelection

Interaction

At the PROPERTY LEVEL:Initial Cash Yield

Cash Flow ChangeYield Change



Portf Tot.Return – Bnchmk Tot.Return

Allocation Selection Interaction

Portfolio Level:

Prop.IRR – Bnchmk Cohort IRR

Init.Yield CF Growth Yield Chge

Property Level:


• At both levels, diagnostic purpose is facilitated by comparison between subject portfolio or mgr with an appropriate benchmark.

• Relative (or differential) performance betw subj vs benchmrk is quantified, in total & w/in components.


Alloc Strategy Across Segments

Asset Picking & Oper.Mgt

Alloc & Selection Synergy

Allocation Selection Interaction

For example, at the portfolio level


Basic idea is that components of the performance differential between the subject & the benchmark reflect performance of various distinct functions of investment management.

Note: In private R.E., the asset “Selection” function also includes asset Operational Management.


Init.Yield CF Change Yield Chge

Acquisition

Selection

Operational

Mgt

Mgt & Disp

Selection


For example, at the property level

Basic idea is that components of the performance differential between the subject & the benchmark reflect performance of various distinct functions of investment management.


A basic problem with all performance attribution analyses:

It is generally impossible to define unique, unambiguous break-downs or components of the total return that correspond to clear causal determinants or investment management functions.

Nevertheless,

Some useful insights can be obtained from performance attribution, provided results are used

carefully.



• Performance attribution lacks significance for any one short holding period (e.g., quarter or year).

• When aggregating across periods:• At the portfolio level (i.e., for allocation and selection

attribution), it is generally best to use the arithmetic TWRR of the attribution components (for component additivity).

• At the property level (i.e., for initial yield, cash flow change, and yield change attribution), it is probably more appropriate to use the IRR, because capital flow timing is controlled by the property (investment) manager at the property level.


Multi-period Attribution


Simple Numerical Example:• Bob & Sue are competing property investment managers

specializing in office and industrial property.• Over the same time period they made the following segment

allocations and achieved the following returns

Exhibit 27-2: Bob & Sue's returns realized for clients:

Weights: Bob: Sue:

Industr 90% 10%

Office 10% 90%

Returns: Bob: Sue:

Total Portfolio 9.20% 9.70%

Industrial Properties 9.00% 7.00%

Office Properties 11.00% 10.00%

• Sue beat Bob by 50 basis points, 9.70% to 9.20%, in total portfolio performance, which is what counts.

• But how can we attribute this total performance differential between the two major functions an investment manager performs @ portf level: segment allocation, and asset selection?

26.1.3 Portfolio-Level Performance Attribution


Suppose (to simplify the illustration) that Bob’s performance is identical to whatever benchmark index would be an appropriate reference for Sue’s performance. Then we can attribute Sue’s differential performance, with respect to her benchmark, to allocation (AS–AB) and selection (SS–SB) as follows:

SS – SB = wBI(rSI – rBI) + wBO(rSO – rBO)

= 0.9(7% – 9%) + 0.1(10% – 11%)

= – 1.8% – 0.1% = – 1.9%

26.1.4. Use of a Benchmark in Performance Attribution

The most logical way to perform this type of comparative attribution analysis is to define a common benchmark that is an appropriate reference point for both Bob’s and Sue’s performance.

AS – AB = rBI(wSI – wBI) + rBO(wSO – wBO)

= 9%(0.1 – 0.9) + 11%(0.9 – 0.1)

= – 7.2% + 8.8% = +1.6%


Sue's returns vs her benchmark:

Weights: Benchmark Sue:

Industr 90% 10%

Office 10% 90%

Returns: Benchmark: Sue:




Clearly, Sue outperformed her benchmark (9.70% vs 9.20%, a +50 bp differential) because of her superior allocation (90% to the office segment that did better than industrial property), not because of her selection (which actually hurt her performance, as her properties did worse than the benchmarks within each segment).

The pure effect of her differential performance in the selection and allocation functions is quantified as follows.

Portfolio-Level Performance Attribution


The pure effect of Sue’s allocation choices, relative to her benchmark, is quantified as the sum across all segments, of the difference between Sue’s allocation and the benchmark’s allocation multiplied by the benchmark’s return in each segment.

AS – AB = rBI(wSI – wBI) + rBO(wSO – wBO)


The pure effect of Sue’s asset selection, relative to her benchmark, is quantified as the sum across all segments of the difference between Sue’s within-segment return and the benchmark’s within-segment return, weighted by the benchmark’s allocation to each segment.

SS – SB = wBI(rSI – rBI) + wBO(rSO – rBO)


Thus, the pure effect of Sue’s selection performance relative to her benchmark was:

SS–SB = wBI(rSI – rBI) + wBO(rSO – rBO)

= 0.9(7% – 9%) + 0.1(10% – 11%)

= –1.8% – 0.1% = –1.9%

She lost 1.9% relative to her benchmark because her industrial properties did 2% worse than the benchmark’s industrial properties and her office properties did 1% worse than the benchmark’s office properties, and her benchmark allocation was 90% to industrial.

Note that in order to avoid mixing the effect of Sue’s allocation in with the effect of her selection, we quantify her selection effect using the benchmark’s allocation.



Similarly, the pure effect of Sue’s allocation performance relative to her benchmark was:

AS–AB = rBI(wSI – wBI) + rBO(wSO – wBO)

= 9%(0.1 – 0.9) + 11%(0.9 – 0.1)

= – 7.2% + 8.8% = +1.6%

She gained 1.6% relative to her benchmark because she put 80% more weight than her benchmark into office properties, and office properties performed 2% better than industrial properties within the benchmark.

Note that in order to avoid mixing the effect of Sue’s selection performance in with the effect of her allocation, we quantify her allocation effect using the benchmark’s selection performance.



The sum of these two pure effects of Sue’s selection and allocation performance does not equal her total return performance differential with respect to her benchmark.

The remaining performance differential is due to the combined effect of Sue’s selection and allocation performances interacting together. (There is no meaningful way to disentangle this interaction effect and allocate it to either one of the two pure effects.)

Sue vs her benchmark:

Attribute:

Allocation 1.60%

Selection -1.90%

Interaction 0.80%

Total differential 0.50%



Sue's returns vs her benchmark:

Weights: Benchmark Sue:

Industr 90% 10%

Office 10% 90%

Returns: Benchmark: Sue:




Sue vs her benchmark:

Attribute:

Allocation 1.60%

Selection -1.90%

Interaction 0.80%

Total differential 0.50%

The interaction effect is sometimes called the “cross-product.”

Some analysts suggest that it reflects the investment manager’s “specialization” ability, her degree of success in over-weighting segments in which the manager has relatively better (or less bad) selection skills even though her overall selection ability may be weak and such segments may not be strategically superior from an overall allocation perspective.

e.g., Sue over-weighted office, where her selection was “less bad” than in industrial, so she achieved a positive interaction (specialization) effect.



Some analysts use the manager’s weights to compute the “selection” effect:

SS − SB = wSI(rSI − rBI) + wSO(rSO − rBO)

= 0.1(7% − 9%) + 0.9(10% − 11%)

= −0.2% − 0.9% = −1.1%

This allocates the entire performance differential to just selection and allocation, eliminating the interaction effect:

Alloc (Sue – Bnchmrk) = +1.6%+ Select (Sue – Bnchmrk) = −1.1%

————Total +0.5%

26.1.4. Mgr Allocation Weights in the Benchmark?

But it is misleading to define the selection effect this way and think of it as a pure selection effect. It would be more meaningful to explicitly combine the interaction effect with selection and call it “Selection & Allocation.”


The meaning of portfolio-level attribution in private real estate investment (as distinct from public securities investment).

• The allocation component has a very similar meaning in private real estate as compared to public securities (corresponding to the segment weight allocation decision at the portfolio level), but…

• The selection component in private real estate encompasses both the traditional “asset picking” function of securities investment management (picking good individual assets), and also (unlike with public securities) the acquisition and operational management function associated with negotiating private asset deals and long-term holding of a real property asset that must be managed by its investor/owner. (i.e., purely “passive” investment is not possible in the private real estate investment industry.)



It is very difficult to break down the overall selection performance between the contributions provided by the “traditional selection” (asset picking) function and that provided by the acquisition and operational management functions.

Some insight may be obtained by analysis of property-level performance attribution. In particular:

• Initial yield relates to the traditional selection & acquisition functions;

• Cash flow change relates largely to the operational management function (but not purely or necessarily, e.g., it may reflect expiration of vintage leases);

• Yield change may reflect either a traditional selection (asset picking) effect or an operational management effect, or both.



26.1.2 Property-Level Performance Attribution

Property level performance attribution focuses on “property level” investment performance, i.e., the total return achieved within a given property or a static (fixed) portfolio of properties (that is, apart from the effect of investment allocation decisions, as if holding allocation among categories constant).

Property level attribution should be designed to break out the property level total return performance in a manner useful for shedding light on the four major property level investment management functions:

• Property selection (picking “good” properties as found);

• Acquisition transaction execution;

• Operational management during the holding period (e.g., marketing, leasing, expense mgt, capital expenditure mgt);

• Disposition transaction execution.


Property-Level Performance Attribution

These property-level management functions are related generally to three attributes (components) of the property-level since-acquisition IRR, essentially as indicated below.

Initial Yield

(IY)

Cash Flow Change

(CFC)

Yield Change

(YC)

Property Selection

Acquisition Transaction Execution

Operational Management

Disposition Transaction Execution

EXHIBIT 26-2 The Four Fundamental Property-Level Investment Management Responsibilities Related to the Three Property-Level Performance Attributes


Conventional property level performance attribution is based on periodic returns, or on time-weighted multi-period returns (TWRRs).

But IRR-based performance attribution is arguably more useful for property level management diagnostic purposes, because:

• At the property level, the investment manager is typically responsible for the major cash flow timing decisions that can significantly effect property level (static portfolio) returns, e.g., leasing decisions, capital expenditure decisions.

• The IRR is sensitive to the effect of cash flow timing, the TWRR is not.• The IRR is cash flow based (net of capital improvement expenditures),

therefore, more accurately reflecting the investment return effect of capital improvement decisions.



Useful IRR-Based property level performance attribution benchmarking requires the use of:

Since-acquisition IRR

• IRR is computed since acquisition of property (or portfolio):

• In order to reflect investment operational performance during entire holding period since acquisition;

• Property investment holding periods are typically multi-year (single period or periodic returns do not reflect effective investment management holding period).

• IRR is computed for appropriate benchmark cohort, defined as universe of similar investments by competing managers, measured from same inception date (equal to property acquisition date).



Simple Numerical Example:• Property (or static portfolio) bought at initial cash yield

of 9%.• Net cash flow grew at 2% per year.• Property (or properties) sold (or appraised) after 10

years at a terminal yield of 10%, based on yr.11 projected cash flow (also 2% more than yr.10).

• IRR is 10.30%.• How much of this IRR is due to 3 components: Initial

Yield (IY), Cash Flow Change (CFC), and Yield Change (YC)?

Recall Ch.10 Appendix 10A: Property-Level Performance Attribution


Yr IRRs: 0 1 2 3 4 5 6 7 8 9 10 11

(1) Actual Oper.CF 1.0000 1.0200 1.0404 1.0612 1.0824 1.1041 1.1262 1.1487 1.1717 1.1951 1.2190(2) Actual Capital CF -11.1111 12.1899(3) Actual Total CF (=1+2) 10.30% -11.1111 1.0000 1.0200 1.0404 1.0612 1.0824 1.1041 1.1262 1.1487 1.1717 13.3850(4) Init.Oper.CF constant 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000(5) Capital CF @ Init.Yld.on(4) -11.1111 11.1111(6) Init.CF @ Init.Yld (=4+5) 9.00% -11.1111 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 12.1111(7) Capital CF @ Init.Yld.on(1) -11.1111 13.5444(8) Actual Oper. CF @ Init.Yld (=1+7) 11.00% -11.1111 1.0000 1.0200 1.0404 1.0612 1.0824 1.1041 1.1262 1.1487 1.1717 14.7395(9) Capital CF @ ActualYld.on(4) -11.1111 10.0000(10) Init.CF @ Actual Yld (=4+9) 8.32% -11.1111 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 11.0000

There are several ways one might answer this question. The approach that seems most intuitively related to the 4 basic mgt fcns is presented here

• Initial yield = 9.00%, computed from line (6) IRR.• Cash flow change component = 2.00% = 11%-9%, computed as the line (8) IRR less

the line (6) IRR: = IRR with actual CF – IRR with no CF growth, (with constant yld at initial rate).

• Yield change component = -0.68% = 8.32%-9.00%, computed as the line (10) IRR less the line (6) IRR: = IRR with actual yld chg – IRR with no yld chg, (with constant CF at initial level).

• Interraction effect = -0.02%, the difference bertween the line (3) overall IRR and the sum of the three other attributes [10.3%-(9%+2%-0.68%)].



Subject Property: IRR & Component Breakout

-4%-2%0%2%4%6%8%

10%12%14%

IRR InitYld CFchg YldChg Interaction

IRR & Components

Here is a graphical presentation of the IRR-Based property-level performance attribution we just performed:

Suppose we computed the same type of IRR component breakdown for an appropriate benchmark, that is, a NCREIF sub-index cohort spanning the same period of time


Property-Level Performance AttributionWe could compare our subject performance with that achieved by a peer universe of managers, for similar properties (e.g., Calif. Industr. bldgs):

Subject vs NCREIF Cohort Performance Comparison: IRR & Component Breakout

-5%

0%

5%

10%

15%


IRR & Components

Subject NPI Cohort


Property-Level Performance AttributionHere is the relative performance, the difference between our subject property and its benchmark, by attribute:

The above pattern could be plausibly interpreted as tentative evidence for the following hypothesis: Subject performed relatively poorly due largely to some combination of poor selection, acquisition, and operational mgt, partially offset by some combination of good disposition execution (or optimistic terminal appraisal), future-oriented capital improvements, &/or market movements during the holding period.

Subject - NCREIF Cohort Relative Performance: IRR & Component Breakout

-2.50%

-2.00%

-1.50%

-1.00%

-0.50%

0.00%

0.50%

1.00%

1.50%


IRR & Components

These property-level management responsibilities:

Initial Yield

(IY)

Cash Flow Change

(CFC)

Yield Change

(YC)

Property Selection

Acquisition Transaction Execution

Operational Management

Disposition Transaction Execution

Ex Post Usage of IRR-based Property-LevelInvestment Performance Attribution: A Management Diagnostic Tool

are related generally to

the three IRR attributes:




Here is the relative performance, the difference between our subject property and its benchmark, by attribute:

Now suppose we computed these relative performance differentials across a number of different properties (or portfolios) we have invested in.

Subject - NCREIF Cohort Relative Performance: IRR & Component Breakout

-2.50%

-2.00%

-1.50%

-1.00%

-0.50%

0.00%

0.50%

1.00%

1.50%


IRR & Components


Property-Level Performance AttributionWe might gain some insights about our property-level investment and management performance:

In this case Subject Properties #1 & 3 have similarly poor performance (rel to benchmk), due to poor initial yield & poor CF change, suggesting poor acquisition & poor operational mgt. Property #2 did better, with good InitYld & CFchg, but poor YldChg (suggesting good acquisition, but poor disposition or mgt actions that hurt future outlook (e.g., inadequate Cap.Improvement). Mkt movements can also affect these results (less so the longer the holding period).

Three Properties Comparison:Subject - NCREIF Cohort Relative Performance

-5.00%

-4.00%

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

3.00%


Subject 1 Subject 2 Subject 3


Real world example…

Source: Modified from Feng (2010).

EXHIBIT 26-3 Property-Level IRR Attributes in 42 Round-Trip Investments: Subject Property vs. NCREIF Cohort, IRR Component by Property

Total IRR Outperformers

Total IRR Underperformers

Exhibit 5 - Color-Coded Relative PPA Results Sorted by Total IRR Performance

Property Number NCREIF Bechmark IRR InitYld CFchg YldChg

12 Retail - Pacific 14.13% O O O30 Office - Southwest 11.86% O O O29 Office - Southwest 8.07% O O U2 Industrial - EN Central 6.75% O O O20 Retail - EN Central 5.87% O O O25 Industrial - Southeast 5.74% O O U26 Industrial - Southeast 5.74% O O U27 Industrial - Southeast 5.68% O O U36 Office - Pacific 5.52% U O U6 Office - Pacific 5.36% O U O41 Retail - Mountain 4.91% O U O18 Retail - EN Central 4.88% O U O5 Office - Pacific 4.68% O U O1 Office - Southeast 3.73% O U O33 Office - Northeast 3.06% U O U35 Apartment - Pacific 2.58% O U O14 Office - EN Central 2.26% O O U23 Industrial - EN Central 1.30% O U O34 Office - EN Central 0.82% O U O21 Apartment - Southeast 0.74% O U O11 Apartment - Southwest 0.29% O U U28 Retail - EN Central 0.14% O U O9 Apartment - Southwest 0.13% O U O7 Office - Southwest 0.02% O U O

Total # Outperformed 24 22 11 16Total % Outperformed 100% 92% 46% 67%Total # Underperformed 0 2 13 8Total % Underperformed 0% 8% 54% 33%

10 Apartment - Southwest -0.35% O U O15 Office - EN Central -0.52% O U O22 Apartment - Southeast -1.11% U O U24 Industrial - Southeast -1.18% O U O13 Office - EN Central -1.26% O U U8 Office - Southwest -1.47% O U O42 Office - Pacific -1.96% O O U17 Retail - Pacific -2.58% O U O40 Office - Mideast -3.03% O O U16 Office - EN Central -3.03% O U O38 Industrial - Southeast -3.99% O U O4 Industrial - Pacific -4.34% O U O3 Office - Pacific -4.89% O U U32 Office - Northeast -6.11% U U U19 Retail - Northeast -6.31% O U U31 Office - Southwest -8.71% U O U37 Office - Pacific -8.76% O U O39 Office - Northeast -15.78% U O U

Total # Outperformed 0 14 5 9Total % Outperformed 0% 78% 28% 50%Total # Underperformed 18 4 13 9Total % Underperformed 100% 22% 72% 50%

Property Number NCREIF Bechmark IRR InitYld CFchg YldChg

Results relative to benchmarks:Winners and Losers Patterns in Performance Attribution

O-U pattern in IY-CFC signaling good acquisition, poor operational

mgt holds in both winners & losers.

Client’s big winners (relative to benchmark) occurred when it broke its usual pattern of poor CFC performance (operational property level mgt during hold).



26.2 Investment Performance Evaluation & Benchmarking

• How Benchmarking Is Done• Purpose & Role of Benchmarking• Criteria of an Ideal Benchmark


How Benchmarking Is Done in the Securities Industry

3-year

Time-Wtd

Return

Investment Mgt “Style” or Asset Class

Style A

Compute ex post total TWRR of all competing managers in an active mgr “peer universe” (same “style”), over a common historical period (indicated by this range).



3-year

Time-Wtd

Return


Style A

Compute inter-quartile range of the peer universe



3-year

Time-Wtd

Return


Style A

Compute median TWRR of the peer universe



3-year

Time-Wtd

Return


Style A

Index A

Compute TWRR of a passive index representative of style.



3-year

Time-Wtd

Return


Style A

Index A

Mgr A

Compute TWRR of the subject active manager or actively-managed portfolio.



3-year

Time-Wtd

Return


Style A

Index A

Mgr ACompare subj mgr’s performance to that of:

• The passive index

• The peer universe



3-year

Time-Wtd

Return


Style A

Index A

Mgr A

Style B

Mgr B

Index B

Do the same within each style



The Importance of Style-Purity in the Benchmark:

• Not appropriate to compare performance of one style of investment against that of another for evaluating a manager who is specialized in (and hired for the purpose of) investing in one particular style.

• Multi-style managers and portfolios can be benchmarked using composite indices constructed from an appropriate combination of style-pure indices.

• Comparative analysis and diagnostics regarding the differential performance of different types (styles) of investments is facilitated by the availability of style-pure indices.


1. Communication (Client Manager).

2. Interest-Alignment (Client Manager).

3. Weed out inferior managers.

The Purpose of Benchmarking

Ex Ante Purposes (most important):

4. Identify superior managers (in combination with qualitative information).

Ex Post Purpose (less important or less feasible):


The Purpose of Benchmarking

Why is the identification of superior managers difficult in practice?

• “Superior mgr” = One who can consistently beat mkt.

• “Superior mgr” = One who can consistently beat peers.

• This is rare, and normally only marginal.

• Moving target: Mkt (& peer universe) learns & improves over time.

• But there is also a statistical reason . . .


26.B2: The Problem of Statistical Significance in Performance Measurement

• “Noise” (or randomness) in ex post returns obscures our ability to draw rigorous conclusions about managers’ abilities to consistently beat a benchmark as a result of skill (& effort) rather than luck.

• There are three sources of randomness in empirically observable real estate returns:

1.Cross-sectional (individ. prop. heterogeneity).

2.Longitudinal randomness in true mkt (volatility).

3.Measurement error (in R.E. returns).

• Any (& all) of these sources of “noise” obscures the “signal” about mgrs’ true relative abilities.

From Appendix 26B…


Numerical Example:• Quarterly returns, 3-yr comparison period.• 12 obs drawn from true difference between mgr(i) &

benchmark(B) return: E[ ri – rB ].

• Suppose favorable circumstances for making inference:• E[ ri – rB ] constant over time.• Volatility of ri & rB = 5%/qtr (each).• CORR [ ri , rB ] = +90%.

• Then mgr TWRR would have to beat benchmark by >500 basis-points per annum before we could conclude with statistical significance that the central tendency of the mgr’s return exceeds that of the benchmark return (i.e., rigorous case for skill as opposed to luck).





Calculations:• Standard error of quarterly difference in returns:

%24.2

)05.0)(05.0)(9.0(205.005.0

2

21

22

21

22

BiBiBi C

• Standard error of observed qtrly avg difference =

%675.0112%24.21 21

NBi

• X 2 std.errs for 95% statistical confidence: 2(0.675%) = 1.35%.

• Annualize: (1.0135)4 – 1 = 5.51% /yr. difference required.



26.B2 & 26.B3: Implications of The Problem of Statistical Significance in Performance Measurement

Implications:

• You cannot use purely quantitative benchmarking comparisons to rigorously identify superior managers ex post.

• Don’t apply such benchmarking mechanistically or in isolation.

• Include broader analyses and qualitative information in conjunction with quantitative benchmarking:

• Performance attribution analysis may be useful in this regard.

• And remember…



26.B3: The “real purpose” of performance evaluation…

Implications:

Ex Ante Purposes (most important):• Communication (Client Manager).

• Interest-Alignment (Client Manager).

• Weed out inferior managers.

• The ex ante role of benchmarking is not negated by the problem of lack of statistical significance:

• Even with noise, a better mgr who works harder for the client is more likely to beat the benchmark.

• Communication betw mgr & client is improved by identification of benchmark at outset of contract.



26.2.1. Criteria for an Ideal Benchmark Index

3-year

Time-Wtd

Return


Style A

Mgr A

Index A

Recall that two different types of benchmarks are often used in the securities industry:

• Passive mkt indices, &

• Peer universes.

Which of these is better as a benchmark?



In the securities industry, there is some argument that peer universes are not as good as passive market indices for benchmarking purposes:

• Peer universes suffer from “survivor bias.”

• Peer universes don’t meet all of the “Bailey Criteria”

The “Bailey Criteria”• Unambiguous• Investable• Measurable• Specified in advance• Appropriate to

Manager• Reflective of Manager



Alas, in private real estate, we don’t really have a passive market index, that is, an index that:• Covers the entire commercial property market; &• Maintains a constant set of assets.

Private real estate benchmark indices are peer universe indices:• Indices that represent the performance of (almost) the entire

population of properties held by the universe of investment managers competing for the business of the institutional “core” style of private real estate investment.

• “Active” mgt is necessary in private R.E. investment (operational control of assets).

• The NCREIF Index is a peer universe index in the US.• The IPD Index is a peer universe index in the UK.



How serious a problem is the lack of a passive market index for the private real estate investment industry?

Such an index would be very useful for research purposes.

• But, in contrast to the securities industry, the argument for the superiority of passive market indices for benchmarking purposes does not carry over to the private real estate investment industry:• There is not much of a survivorship problem in property-level indices

such as NCREIF.• Investment turnover is not rapid in R.E. indices.• Some of the “Bailey Criteria” do not make sense for the private real

estate investment industry.

e.g., perfect index investability is not possible in an asset class where unique, whole assets are traded.



Fundamental Criteria of Benchmark Indices:

1. Measurability: Quantitative comparison

2. Client Investability: Mgr hired for incremental contribution over what client could do

3. Manager No Forced Bet: Mgt Principle: Evaluation = Responsibility = Authority

4. Appropriateness (Mgr Style & Spec.):

Usefulness for client strategy implementation, fairness for mgr

5. Non-manipulatability: Credibility & ex ante role

6. Agreement in Advance: Communication & fairness



Peer universe indices (like the NCREIF Index) implement these criteria reasonably well for the private real estate investment industry. For Example:

• Peer universe benchmark indices are like a Consumer Reports of the investment industry.

• You compare a given investment manager’s performance with that of all of his relevant competitors (“peers” – managers the investor could have hired instead of the given manager: i.e., those with the same style & specialization).

Peer universe indices are reasonable and prudent measures for benchmarking private real estate performance.

Client Investability: Client could have hired any other competing mgr from peer universe, instead of subj.mgr., so peer universe is “ex ante investable.”

Manager No Forced Bet: Mgr can duplicate types of properties in peer universe index.



Some practical implications of ideal benchmark criteria:

CRITERIA:3. Manager No Forced Bet

&4. Appropriateness

• Fixed real return targets are NOT good Benchmarks.

• Direct (private) real estate investment mgrs or portfolios should NOT be benchmarked against REIT Indices.


Time-Wtd

Return


Style A

Mgr A

Index A

Thus, we are looking for style-pure, peer universe indices for benchmarking R.E. private equity funds and investment manager performance…

26.2.2: Benchmarks & Investment Styles in the Private Real Estate Asset Class:

Year 2009 2008Direct Investment 40.3 43.2Commingled Closed 34.2 31.6Commingled Open 7.9 8.4Joint Venture 10.5 11.5Other 7.1 5.3Total Private Investment 100 100Source: Pension Real Estate Association

PREA U.S. Members Only—Real Estate Investment Structure (% Private Only)

How do U.S. PFs invest in private real estate?...




Exhibit 26-9: Schematic Diagram of Institutional Real Estate Investment Management Styles: Core, (Core+), Value-Added, Opportunistic…


© 2014 OnCourse Learning. All Rights Reserved.

90100110120130140150160170180190200210220230240250260270280

1999Q4

2000Q2

2000Q4

2001Q2

2001Q4

2002Q2

2002Q4

2003Q2

2003Q4

2004Q2

2004Q4

2005Q2

2005Q4

2006Q2

2006Q4

2007Q2

2007Q4

2008Q2

2008Q4

2009Q2

2009Q4

2010Q2

2010Q4

2011Q2

2011Q4

1999

Q4

= 10

0NCREIF/Townsend Fund Indices vs NCREIF Property Index: Cumulative Total Returns, 2000-2012*

Core Funds Value-Added Funds NPI*Based on value-weighted all-funds indices, net of fees. NPI is property level gross of fees. Source: NCREIF.

2000-2012 Tot. Retns: Core Val-Add NPI

Qtrly GMean 1.5% 1.2% 2.0%

Peak-Trough -38.4% -53.8% -23.9%

Trough-1Q2012 36.6% 37.7% 32.6%

Qtrly Volatility 4.0% 5.6% 2.9%

Fund indices, unlike property-level indices, reflect actual returns achieved (net) by investors. Advent of NCREIF/Townsend Fund Indices. (Now also IPD/PREA indices). Here Core & Val-Add based on TWRRs…

Typical leverage at least: Core 20%, Val Add 50%

Exhibit 26-7:

70

Exhibit 26-8: NCREIF/Townsend Report of Real Estate Opportunistic Funds IRR Performance by Vintage Year (as of March 31, 2012)

Some styles & mgrs. are better measured by vintage-yr cohort IRR performance than by TWRR performance.


Source: NCREIF and The Townsend Group, “Real Estate Fund Indices and Vintage Period Performance Report, 1st Quarter 2012f,” NCREIF, Chicago, 2012.

Section 26.3: Real Estate Derivatives.

• What is a Derivative?– An asset or claim whose value depends

completely on that of one or more other assets.

– Examples:• Options (Calls, Puts, etc)• Futures (on Commodities, Foreign Exchg,

Financial Indexes)• May be traded on public exchanges or OTC


How to Construct a Real Estate Index Derivative…

R.E.Index +

Contract Providing a

Claim on the R.E. Index

= R.E.Derivative

What is a derivative…


Types of Derivatives

• Forwards

• Swaps

• Others (Futures, Options, CDS, etc)

• (We will only cover Swaps here.)

What is a derivative…


SwapsExample: 1-year Swap Contract, Quarterly settle:

Swap real estate index total return for 560 bp/yr (140 bps/qtr)

Timeline:

Now (time 0) 1 Yr from Now

Price agreed now, Notional amt = $100.

No cash changes hands.

Index retn Q4 = 5%.

Long recvs $5, owes

$1.40: Net = +$3.60.

Short recvs $1.40, owes

$5: Net = -$3.60.

Index retn Q3 = 3%.

Long recvs $3, owes

$1.40: Net = +$1.60.

Short recvs $1.40, owes

$3: Net = -$1.60.

Q3

Index retn Q2 = -1%.

Long pays $1, owes

$1.40: Net = -$2.40.

Short recvs $1.40, plus $1: Net = +

$2.40.

Q2

Index retn Q1 = 0%.

Long recvs $0, owes

$1.40: Net = -$1.40.

Short recvs $1.40, owes $0: Net = +

$1.40.

Q1

(Ignore Intermed.)

( $1.40 = 5.60%*$100/4 )What is a swap…

“Short” position referred to as “floating rate

payer” in Grosv.Case

Sometimes quoted as a floating rate spread over LIBOR, but in RE swaps it’s typically a fixed absolute rate as here.


Type: Notional Value: Gross Value:Interest Rate 458.3 9.3ForEx 63.0 2.3CDS 57.3 3.2Commodity 13.2 2.2Equity-linked 10.2 1.2Unallocated 81.7 2.3

Total 683.7 20.4

Worldwide OTC Derivatives Contracts Outstanding (2008), $ Trillions

Source: BIS

“Gross Value” is actual absolute fair value (current potential cash liability) exposure both sides face.


Real estate is the largest category of physical assets (over 1/3 of national wealth) for which no

derivatives are traded…Exhibit 7-5: Approximate Aggregate Value of Asset

Classes, USA early 2000s ($Trillion)

4

17

26

17

Cash

Stocks

Bonds & Mortgages

Real Estate Equity*

*Excludes value in mortgages and corporate real estate.

During 2000s trading began:

• IPD/UK

• Case-Shiller CME

• RadarLogic (RPX)

• CMBX

• NCREIF

Got clobbered in Fin Crisis.

(But I think it will rise again.)


Source: Dhar and Goetzmann 2004 survey of U.S. pension funds for PREA.

Derivatives Can Address Major Concerns of Institutional Investors About R.E.


Mkt took off rapidly after 2004, grew to 265 contracts (£3.5B notional) written in 08Q1, then became victim of financial crisis.

0

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(GB

P M

M)

Nu

mb

er o

f C

on

trac

ts

*2004 qtrs averaged

IPD UK Swaps, New Contracts Traded by Quarter

<== Number

Value ==>

IPD Index swaps took off in U.K.


Relative to the scale of the British cash (physical) property market (IPD purchase expenditures), swaps notional trading volume took off in 2006-07 to over 100% of the property volume.

0

2000

4000

6000

8000

10000

12000Q

1 20

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Ste

rlin

g (0

00,0

00)

Per

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arte

r

IPD Swaps & Physical Property Trading Volume

Physical

Synthetic

IPD Index swaps took off in U.K.


0%

20%

40%

60%

80%

100%

120%

140%

160%

Q1

2004

*

Q2

2004

*

Q3

2004

*

Q4

2004

*

Q1

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Q2

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Q1

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Q3

2008

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Q1

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Q2

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Q3

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Q4

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Q1

2010

Q2

2010

Q3

2010

Q4

2010

Der

ivM

kt /

Pro

pM

kt

*2004 qtrs are averaged

Synthetic / Physical Trading Volume: Swap notional issuance / IPD Property ExpenditureX2

This shows the potential.© 2014 OnCourse Learning. All Rights Reserved. 81

“Iceberg” fund using derivatives returned positive during the “Great Crash” in the R.E. investment market of 2008-09…

$20

$40

$60

$80

$100

$120

$140

$160

$180

$200Ju

n-07

Aug

-07

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-07

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-07

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-08

Jun-

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-12

Cumulative Total Investment Value (Total Returns, Dividends Reinvested)June 2007 = $100

NAREIT

NPI (Apprsl Est)

TBI

Iceberg Real Est Hedge Fund



Example (1) Use of Swap (long)• U.S. Investor holds $1B in U.S. real estate; wants to diversify

20% of that into British real estate, but lacks local UK

expertise, wants diversified British property returns (UK RE

“beta,” not “alpha”).

• Sells $200M US RE, invests proceeds into riskless fixed-rate

bonds.

• Purchases (long) $200M notional amt of UK RE total return

Index swaps, 5 yr contract, (no up-front cash outflow), uses

bond investment to cover swap price (“fixed leg” or “floating-

rate pmt”).

• Receives net UK RE total return ea qtr for 5 yrs (less maybe

50 bps/yr “Ask” price spread, which is less than asset mgt

fees).

Uses of swaps…


Example (1) Continued:Mechanics of how it works…

• Suppose US RE return will be 9% less 100bps AsstMgt fee, British index retn

will be 3%, UK Swap “Ask” price = 550 bps (= 5% swapped-LIBOR fixed rate +

50 bps “Ask” spread).

• Initial portfolio: $1B US RE gives return = 9%-100bps = 8% = Pure US return

(less AsstMgt fee).

• New portf: $0.8B US + $0.2B UKswap + $0.2B bond.

• Return would be [$0.8B(9%-1%) + $0.2B(3%-5.5%) + $0.2B(5%)]/$1B =

[$64M-$5M+$10M]/$1B = $69M/$1B = 6.9% = 0.8(US Retn) + 0.2(UK Retn –

Ask spread).

• Direct 80/20 US/UK RE portf return would be (net of 100bps fees): (0.8)(9%-

1%) + (0.2)(3%-1%) = 6.8%.

• Covered long position (long index swap + riskfree bond investment of same

notional amt) provides virtually identical return as the direct 80/20 portfolio

(slightly higher due to lower mgt cost as Ask spread < AsstMgt fee).

Uses of swaps…

Synthesize Total Return

Let: Δ = (Realized – Expctd) Indx Tot Retn = rS – E[rS] Equilibrium (“fair”) price for Total Return Swap:

F = Expctd Tot Retn – Indx Risk Prem = E[rS] – RPS

Synthesize total return:Invest $100M in riskfree bond + $100M in Swap (0 CF),

Obtain on $100M: rf + rS – F= rf + (E[rS]+Δ) – (E[rS] – RPS) = rf + RPS + Δ = E[rS] + Δ = rS Tot Retn Expctn cancels. You obtain Tot Retn: rS = E[rS] + Δ

RPS = Equilibrium Risk Premium for Index.

You will obtain the Δ from the index (hence risk from index) and ex ante you will receive the equilibrium expected total return of the index. Ex post, the total return you receive will therefore only exactly equal the index reported return if the index is in equilibrium (no lag).



Example (2) Use of Swap (long)• Pension Fund’s overall mixed-asset portfolio is $1.5B stocks

+ $1.5B bonds, wants to diversify to equal 1/3 shares in

stocks, bonds, & real estate for diversification purposes

(wants R.E. beta, not alpha, not looking to “beat mkt”).

• Sells $0.5B stocks & $0.5B bonds, invests resulting $1.0B

proceeds into riskless bonds.

• Purchases (long) $1.0B notional amt of RE total return

Index swaps, 5 yr contract, (no cash outflow), uses fixed-

rate bond investment to cover swap price.

• Receives net RE total return ea qtr for 5 yrs (less 50 bps/yr

“Ask” price spread, which is less than asset mgt fees), for

fully-diversified R.E. return.

Uses of swaps…

Example (2) Continued:Mechanics of “beta” exposure…

• Let rST, rBD, rRE be the ex ante expected total return to stocks, bonds, and RE respectively.

• Let ΔST, ΔBD, ΔRE, be the realization of the “volatility” (unpredictable component of return) of stocks, bonds, and RE respectively: E[Δ]=0. (Hence: ex post realized retn = r+Δ.)

• Old portf retn = ($1.5/$3.0)(rST+ΔST) + ($1.5/$3.0)(rBD+ΔBD) = 0.5(rST+rBD) + 0.5(ΔST+ΔBD). Last term means portf has half beta stocks + half beta bonds.

• New portf actual investment holdings are $1.0B stocks, $1.0B bonds, $1.0B riskfree bonds. But by mechanics shown previously…

• New portf retn = ($1.0/$3.0)(rST+ ΔST) + ($1.0/$3.0)(rBD+ΔBD) + ($1.0/$3.0)(rRE+ΔRE) = 0.33(rST+rBD+rRE) + 0.33(ΔST+ΔBD+ΔRE). Last term means portf has 1/3 stock beta + 1/3 bond beta + 1/3 RE beta.

Uses of swaps…



Example (3) Use of Swap (short)

• Real estate developer/asset mgr has specialized expertise enabling it to “beat the market” in northeast apartment property development & asset mgt (positive “alpha”)

• Owns $1B worth of such property, feels will beat mkt by 2%/yr, but feels NE apt market is headed for a downturn over next 3 yrs.

• Takes $1B notional amt short position in NE Apt R.E. Index Swap, 3-yr contract (0 cash flow), @ bid price = fixed 5% – 50 bps bid spread.

• Continued…

Uses of swaps…


Example (3) continued…• If market falls, say, 10%, then fund’s properties fall 8% (alpha =

2%), loses $80M, but gains $100M + 45M from swap short: Net

CF = 100-80+45 = +$65M.

• If market rises, say, 12%, then fund’s properties gain 14%

(alpha = 2%), gains $140M, but pays $120M less 45M on swap

short: net CF = 140-120+45 = +$65M.

• Fund is hedged for 3 yrs (“Property Mkt Value Insurance”), same

outcome (+$65M) no matter what happens in apt mkt.

• 0-NPV alternative is to sell all $1B worth of property, invest in

LIBOR @ 5%, earn $50M no matter what happens in apt mkt.

• Difference (+$15M) is “alpha harvest” (net of 50bps “bid”

spread, i.e.: $20M-$5M), no matter what happens in apt mkt.

Uses of swaps…


Example (4) Levered Short Hedge• Same Apt developer/asset mgr as before (with $1B

property & +2% alpha returns)…

• Follows same swap short strategy as before, only

now also borrows $900M against the hedged

portfolio @ 5% (since hedge has reduced volatility,

fund can borrow very high LTV at low rate).

• Uses loan to pay out $900M to investors.

• Now the remaining $100M equity in fund is facing

earnings of +$65M - $45M = +$20M, +20% return

for sure, no matter what happens in apt mkt! (But more risky…)

Uses of swaps…


Example (4) Continued:How the risk comes in…

• Suppose the +2% alpha does not materialize. Suppose

properties earn 0 alpha.

• Then hedge produces $45M no matter what (instead of

previously calculated $65M), which net of $45M loan

interest 0% return (on $100M equity).

• Suppose idiosyncratic risk in properties &/or “basis risk” in

index (difference betw index vs NE Apt mkt) causes funds’

properties to underperform index by 1%.

• Then hedge produces $35M no matter what, which net of

$45M loan interest is loss of $10M or 10% on $100M

equity.

Uses of swaps…

Use of Derivatives: Summary

• Example (1) Long (UK Index): – Fast, Efficient Diversification w/in R.E., inclu intl.

• Example (2) Long (Mxd Asset Mgr):– Fast, Efficient Diversification into highly diversified R.E.,

obtaining RE “beta.”

• Example (3) Short (Alpha Harvest):– Hedge mkt exposure, earn alpha no matter what (lay off

“beta,” keep “alpha”)

• Example (4) Levered Short Hedge:– Lever the above: “Long-Short Engineering”

Watch out! Risk!

Only the last of these four examples is particularly “risky.”Example (3) is actually a type of “insurance” or “laying off” of risk.


Property Objectives Financial Objectives

Property Expertise Financial Mkt Expertise

Property Ownership & Control

Physical & Financial Characteristics of the

Property

Physical Performance of the Property

Financial Performance of the Property & Mkt

Exh.26-11:The Traditional Structure: Joined at the hip…


Property Objectives Financial Objectives

Property Expertise Financial Mkt Expertise

Property Ownership & Control

Physical & Financial Characteristics of the

Property

Physical Performance of the Property

Financial Performance of the Property

Exh.26-11: Potential Structure with Derivatives: Disarticulation…

Financial Performance of the Market

R.E. Derivatives

R.E. Derivatives (short)

Property owners’ performance based on their specific expertise (“alpha”)

Investment industry performance based on their expertise (“beta,” fin engrg)

Greater Flexibility & Specialization; Enhanced Profitability & Efficiency© 2014 OnCourse Learning. All Rights Reserved. 94

Equilibrium Swap PriceSuppose (2-yr swap index TR for fixed):• Riskfree rate = rf = 4% (or it could be LIBOR if that is the

swap); • Real estate index equilibrium risk premium (over rf ) is 3%.• Lag in index and/or mkt gives index -7%/yr “overhang”

during contract period (RE mkt has recently fallen about 14% price drop, assuming 2-yr lag in index)…

Equilibrium expected total return is: rf + RPS = 4% + 3% = 7%.

Index consensus expected total return (2yr) is (per ann): E[rS] = rf + RPS + lag = 4% + 3% - 7% = 0%/yr.

Long position will pay price F as high as (no higher than):

FL ≤ rf + lag = 4% + (-7%) = -3%, or equivalently:

FL ≤ E[rS] – RPS = 0% – 3% = -3%

Why?...© 2014 OnCourse Learning. All Rights Reserved. 95

Equilibrium Swap PriceLong position will pay price F as high as (no higher

than):

FL ≤ rf + lag = E[rS] – RPS = -3%. Why?...

Will earn 4% on riskfree bond of notional amt,

Plus expected 0% on index return

Minus price of F = -3% (neg price is pos$$):Expected return on overall position (covered long

swap):

= 4% + 0% – (-3%) = 7%

= Equilibrium (“fair”) expected return on investment with risk equal to that of RE index (provides equilibrium index risk premium of 3%).


Equilibrium Swap PriceSuppose you had agreed to pay F = 0% (expected return

on index, here: recv indx retn for free).

Then expected return on overall position (covered long swap):

= 4% + 0% – 0% = 4%

You would face expected return = 4%, no higher than riskfree rate rf .

Yet you are fully exposed to the index risk on your investment equal to the notional amount.

If you are satisfied with a 4% expected return, why not just invest riskfree, avoid the index risk?...


Equilibrium Swap PriceShort position will take price F as low as (no lower than):

FS ≥ rf + lag = E[rS] – RPS = -3%. Why?...

Will earn expected 7% on covering real estate of same risk as index (true return no lag),

While paying expctd RE retn 0% on swap,

Plus receive F = -3% (i.e., will pay 3%):

Expected return on overall position (covered short swap):

= 7% – 0% + (-3%) = 4% = rf

= Equilibrium (“fair”) expected return on riskfree investment (short cancels RE systematic risk exposure, swap pmt F is riskless).


Pricing Lesson:• The equilibrium (“fair”) swap price for a swap of a RE index

for a fixed leg is F = rf + L (for a total return swap), where: L = “Lag Effect” = Expctd Retn – Equilibr Expctd Retn: E[rS] – EE[rS] L = Risk Differ (propmkt – index) + momentum in index L = (RPP – RPS) + m : mkt been strong m > 0, mkt been weak

m < 0. For NCREIF Index (appraisal-based), I believe RPP ≈ 200-400 bps, RPS ≈ 100-300 bps, (RPP – RPS) ≈ 100-200bps.

• Note: For a private mkt-based index swap, F is not generally the expected return on the real estate index, nor is it generally exactly the riskfree rate or LIBOR: (generally: L <> 0).

• rf + L is equivalent to the forecasted return on the index minus the equilibrium risk premium for the index:

F = E[rS] – RPS. (I believe for NPI: RPS ≈ 100-300bps.)

• For a capital return swap the fair price is rf + L Minus the RE Income Return, or: F = E[gS] – RPS , gS = cap retn.

Pricing the Swap…


Contents of this presentation…

1. IntroductionNeed & Opportunity for the PureProperty™ Product

2. What are PureProperty™ Indices?

3. PureProperty™ Indices as an Information Product- Comparison of PureProperty™ & Private CRE Market

4. PureProperty™ Indices as an Investment Product- CRE total return replication.

5. Technical Appendix

26.3.3: Solving the Index Problem


Commercial real estate (CRE) is a large share of total investable wealth ($Trillions)

Bonds; 38

Stocks; 15

CRE; 9

Houses, 16

12% of total investable wealth


$15 Trillion U.S. Pension Fund Assets…

IRA Accounts, 31%

401k Accounts, 25%

Private Pensions, 15%

Federal Pensions, 9%

State/Local Pensions, 19%

Defined Benefit (DB):

$6.6 trillion

Defined Contribution (DC): $8.6 trillion& growing.

DB plans often fall short of their stated CRE targets

DC plans need new vehicles for making CRE investments.


PureProperty™ Investment Can Address Long-standing Concerns Institutional Investors Have About CRE


Source: Dhar and Goetzmann 2004 survey of U.S. pension funds for PREA.

Problems with investing in private real estate…

• Illiquidity

• Large transactions costs

• Large investment management costs

• Large capital outlay requirements

• Difficulty measuring asset values

• Infrequent return measurement

• Impossibility of short positions


REITs now own over twice as much CRE assets as are tracked by the NCREIF Index…

Generally similar types of properties as NCREIF (large, institutional quality).

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sImplied Stock Mkt Valuation of REIT Property Assets

Stk Mkt Cap / (1 - Avg LTV)

REIT Property Asset Valuation NCREIF Property Asset Valuation

As of 2Q2012: Properties Asset Val (B) Avg Val/PropPureProperty™ Indices 25,516 $689.8 $27,034,018NCREIF Property Index 7,299 $310.7 $42,572,799


Need & Opportunity for the PureProperty™ Product…

• It has always been a challenge to index CRE investment performance.

• There is a need for new vehicles to allow investment in, and hedging of, real property assets.

• The REIT industry provides a way to tap the informational efficiency and liquidity of the stock market to help plug these gaps:

• Information

• Investability





3. PureProperty™ Indices as an Information Product- Comparison of PureProperty™ & Private CRE Market




Methodology: De-levered Regression Model…

• REIT returns are de-levered using monthly cost of capital plus each REIT’s capital structure– Retrieves property asset performance– Allows for direct comparisons with NCREIF Property Index (NPI)

and transactions-based indexes• Index weights are derived by weighted regression using each

REIT’s property holdings by property type (sector), location (region), and sector-region combination– Pure exposure to target sector/region, no exposure to others– Identifies “best” estimate of actual changes in unlevered property

values (optimal diversification via GLS regression)• Exact methodology of the FTSE-NAREIT PureProperty™ Indices is

patented by NAREIT & MIT.


Office Portfolio Return:

.01

21

83

83

81

89

43

10050

41

100150

41

10050

43

100150

43

41

10050

41

43

100150

10050

100150

RORIRORIRO

RIRO

RIRORIRORR

Industrial Portfolio Return:

PureOffice

PureIndust

The basic idea: Technical…

.10

21

89

81

83

83

43

41

100150

41

43

10050

100150

10050

RIRIRORIRO

RIRORIRORR

To simplify for illustration, suppose:• 2 market segments: Office & Industrial; Returns = “RO,” “RI.”• 2 firms: Firm 1 & Firm 2; Returns = “R1,” “R2.”• Both firms with no debt and no investment other than in properties.

Suppose: Firm 1: 75% Office, 25% Industrial.

Firm 2: 25% Office, 75% Industrial.

Construct two portfolios:• Office Portfolio: $150 Long Firm 1 + (-$50 )Short Firm 2.• Industrial Portfolio: (-$50) Short Firm 1 + $150 Long Firm 2.


The De-levered Approach

• Combine market value of equity and book value of debt to get implied asset value

• Exposed to REIT property returns• Not exposed to REIT financing decisions• Lower volatility than REIT equity• Investment is divided between REIT equity and fixed

income instruments


Total Return Performance ComparisonPureProperty Index vs All Equity REIT Index

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

All Equity REIT Index

PureProperty Index

-33.2%

-68.3%

Not exposed to REIT financing decisions.


• Natl Composite Headline Index (value-wtd)*• 6 National Sectors (Apts,Ind,Off,Ret,HC,Hotel)*• 4 All-sector Regions (E,MW,S,W)*• Office

– East, MidWest, South, West• Apartments

– East, MidWest, South, West• Retail

– East, MidWest, South

*Investable (11 indices)

The initial set of 22 PureProperty™ Indices…





3. PureProperty™ Indices as an Information Product:- Comparison of PureProperty™ & Private CRE

Market




The “information product”…

• Consider PureProperty Indices as an information product

• Aimed at helping to track commercial property price movements

• Useful for market analysis, industry research, academics, financial regulators

Consider a brief history of price information indices for U.S. commercial real

estate…


First: NCREIF Property Index (NPI), since 1982, appraisal-based

Based on small (but important) population (pension funds), law requires regular re-appraisal. (U.S. GAAP does not require appraisals.)Tracks same-property valuations & total returns. Appraisals lag & smooth market values, but widely accepted & used by industry.

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1

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6

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8

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9

5/7/

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1

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1

1999

Val

ue

= 1

000

Quarterly

U.S. Institutional Commercial Property Composite Capital Value, 2000-2011: Various types of indices...

NCREIF NPI (appraisal-based)

(X-axis is all weekdays; gaps in data are stock market holidays.)Composites are value-weighted.

115

2005: NCREIF-based “TBI,” transaction based

Originally developed at MIT Center for Real Estate, now produced by NCREIF, based on same population as NPI, but transaction prices of sold properties. “Hedonic price model” approximated by ratio: TBI(t) = (P(t)/A(t))NPI(t).

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Val

ue

= 1

000

Quarterly



NCREIF TBI (transaction based)


116

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1

1999

Val

ue

= 1

000

Quarterly




Moodys/RCA CPPI


1st CRE index using repeat-sales methodology. Based on larger population of properties than NCREIF: Real Capital Analytics (RCA) database of all sales > $2,500,000. Tracks same-property prices (not total returns). Similar method to Case-Shiller.

2006: RCA-based “CPPI,” repeat-sales index (transactions based)

117

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Val

ue

= 1

000

PureProperty Daily, Others Quarterly




Moodys/RCA CPPI

FTSE/NAREIT PureProperty (REIT-based)


Daily-updated index, based on de-geared REIT share prices. REITs are “pure plays” in commercial property. Index statistically infers movements in underlying property assets implied by movements in REIT share prices. Uses information efficiency and liquidity of stock market.

2012: FTSE-NAREIT PureProperty™ Indices, stock mkt based…

118

Cumulative Total Returns 2000-2012Q2. PureProperty™ appears more volatile than NCREIF TBI. But in an important & realistic sense this is misleading…

90010001100120013001400150016001700180019002000210022002300240025002600270028002900300031003200330034003500

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PureProperty Daiily, TBI Quarterly

Institutional Core Commercial Property Composite CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty Natl Composite

NCREIF NTBI Natl Composite


Show at same frequency. Both indices evaluated at end of each calendar quarter. Now which index appears “more volatile”?...

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Both indices valuated as of end of calendar quarters




This is a more fair comparison. Here the PureProperty does not appear more volatile. 120

Now here is actually a more complete picture of the relationship of the information provided by the PureProperty™ versus the NCREIF index…

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0

PureProperty Daily, TBI Quarterly




PureProperty™ doesn’t “sweep under the rug” the daily movements between quarter endpoints. The private market index has gaps in its information provision that the PureProperty™ fills.

121

PureProperty volatility is comparable to private market indices at annual frequency…

0%

2%

4%

6%

8%

10%

12%

14%

NCREIF NPI (Appraisal)

NCREIF TBI (Transaction)

FTSE/NAREIT PureProperty

Annual Volatility, CY 2000-2011:

10.6%

12.9%

11.2%


PureProperty volatility is comparable to TBI at quarterly frequency… (based on 50 qtrs of data)

0%

1%

2%

3%

4%

5%

6%




Quarterly Volatility, CY 2000-2012Q2:

2.9%

5.7%

11.2%

5.6%

NPI (appraisal-based) volatility is lower at quarterly frequency due to smoothing.Does not represent liquid volatility.


PureProperty™ less autocorrelation implies more informationally efficient index (less inertia)…

0%

5%

10%

15%

20%

25%

30%

35%




Annual 1st-order Autocorrelation, CY 2000-2011:

News fully reflected in prices quickly Low autocorrelation.Private market is sluggish, takes time to reflect news in prices.

Appraisal-based index is smoothed and lagged.© 2014 OnCourse Learning. All Rights Reserved. 124

PureProperty™ less autocorrelation implies more informationally efficient index (less inertia)…

News fully reflected in prices quickly Low autocorrelation.TBI has some statistical “noise” at quarterly frequency Negative autocorrelation.

Appraisal-based index is highly smoothed and lagged at quarterly frequency.

-20%

0%

20%

40%

60%

80%

100%




Quarterly 1st-order Autocorrelation, CY 2000-2012Q2:

125

Lead/Lag cross-correlations confirm PureProperty leads private market indices (less inertia, more pricing “news”)…

Positive correlations between PureProperty & NCREIF lagged (t+L) implies PureProperty lead. Negative lagged correlations (t-L) reflect cycle.PureProperty leads TBI 2 qtrs, NPI 4 qtrs (average).

-20%

-10%

0%

10%

20%

30%

40%

t-4 t-3 t-2 t-1 t t+1 t+2 t+3 t+4

Quarter of PureProperty Ahead (+) or Behind (-) Private Mkt Index

Lead-Lag (Qtrly, 2000-2012Q2):Correlation betw PureProperty Qtr "t" &

Private Mkt Index Lead/Lagged

NCREIF (appraisal) NCREIF (transactions)





3. PureProperty™ Indices as an Information ProductComparison of PureProperty™ & Private CRE Market




The “investment product”…

• Consider PureProperty Indices as an investment product.

• Any of 11 investable indices can support ETFs.

• Useful for portfolio allocation, as a unique asset in its own right, appeals to DB & DC pension funds.

• Represents a large class of physical capital.

• Any of all 22 indices useful for synthetic investment in private real estate, best basis for derivatives.

• Useful for portfolio rebalancing, targeting.

• Useful for hedging targeted or generalized commercial property risk.


Private market replication: Cumulative Total Returns 2000-2012Q2.

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0







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"East Region" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI



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"Midwest Region" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI



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"South Region" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI



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"West Region" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI



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"Apartment" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty Natl Apts

NCREIF NTBI Apts



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"Industrial" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty Natl Industrial

NCREIF NTBI Industrial



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"Office" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty Natl Office

NCREIF NTBI Office



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"Retail" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty Natl Retail

NCREIF NTBI Retail


PureProperty™ Investable Core Sectors: Cumulative Total Returns 2000-2012.

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7/10

/201

2

2000

Val

ue

= 1

000

PureProperty™ Indices Cumulative Total Returns, National Core Sectors: 2000-2012

Apartments

Industrial

Office

Retail


PureProperty™ Investable Regions: Cumulative Total Returns 2000-2012.

900

1000

1100

1200

1300

1400

1500

1600

1700

1800

1900

2000

2100

2200

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3100

3200

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350012

/31/

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2

12/3

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99 =

100

0PureProperty™ Indices Cumulative Total Returns, Regions: 2000-2012

East

Midwest

South

West


PureProperty™ Non-Investable Sector/Region Combination Indices:

800

1000

1200

1400

1600

1800

2000

2200

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2600

2800

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99 V

alu

e =

100

0


"East Region Apartment Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

12/3

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99 V

alu

e =

100

0


"East Region Office Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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1

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1/19

99 V

alu

e =

100

0


"East Region Retail Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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00

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1

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1/19

99 V

alu

e =

100

0


"Midwest Region Apartment Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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1

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2012

12/3

1/19

99 V

alu

e =

100

0


"Midwest Region Office Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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99

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2000

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00

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2001

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2002

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2002

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7/9/

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2011

7/10

/201

1

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2012

12/3

1/19

99 V

alu

e =

100

0


"Midwest Region Retail Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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2000

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00

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2001

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1

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2012

12/3

1/19

99 V

alu

e =

100

0


"South Region Apartment Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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2000

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00

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2011

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1

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2012

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1/19

99 V

alu

e =

100

0


"South Region Office Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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99

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2000

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00

7/2/

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1/1/

2002

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2002

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2003

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2007

1/6/

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7/7/

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1/7/

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7/9/

2010

1/8/

2011

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/201

1

1/9/

2012

12/3

1/19

99 V

alu

e =

100

0


"South Region Retail Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

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2000

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1/20

00

7/2/

2001

1/1/

2002

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2002

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2003

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2004

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2007

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2010

1/8/

2011

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/201

1

1/9/

2012

12/3

1/19

99 V

alu

e =

100

0


"West Region Apartment Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

12/3

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99

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00

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1/1/

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1/2/

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1/3/

2005

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2007

1/6/

2008

7/7/

2008

1/6/

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7/8/

2009

1/7/

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7/9/

2010

1/8/

2011

7/10

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1

1/9/

2012

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99 V

alu

e =

100

0


"West Region Office Properties" CumulativeTotal Return Indices, 2000-2012: REIT-based PureProperty™ & Private Market-based Transactions Price Indices

PureProperty

NCREIF NTBI

Useful for synthetic investment (derivatives), & as information products.

PureProperty™vsNCREIF TBI2000-2012

East:A, O, R

Midwest:A, O, R

South:A, O, R

West:A, O





3. PureProperty™ Indices as an Information ProductComparison of PureProperty™ & Private CRE Market




Technical AppendixRegression Method

Simple Stylized Numerical Example…


Technical Appendix Consider the classical construction of a hedge portfolio:

Observe:• Return all periods t to target asset k = rk

t (presumably not directly tradable: hence, you need a hedge to mimic it).

• Returns all periods t to a set of tradable hedge assets i = rit , where

(i = 1, 2, …, N)

Example: Hedge returns to k = Office, Industrial Properties:

Period (t ):Office Retn

Indust Retn

1 10% 0%2 0% -10%

Tradable hedge assets are two REITs i = REIT 1, REIT 2:

REIT (i ):Office

HoldingsIndust

Holdings1 75% 25%2 25% 75%


Technical AppendixClassical construction of a hedge portfolio

Assuming stock mkt efficiently reflects returns to Office & Indust properties in REIT returns, the returns to the two REITs, ri

t , are:

Since (recall) the underlying rkt returns are:

Period (t ):REIT 1

RetnREIT 2

Retn1 7.5% 2.5%2 -2.5% -7.5%

Tradable hedge assets are two REITs i = REIT 1, REIT 2:

REIT (i ):Office

HoldingsIndust

Holdings1 75% 25%2 25% 75%

Period (t ):Office Retn

Indust Retn

1 10% 0%2 0% -10%



For each target k the N-dimensional vector of estimated coefficients on the hedge vehicles is the set of optimal weights on the individual hedge vehicles in the hedge portfolio (OLS for illustr).

Perform longitudinal regression of target returns onto hedge assets returns:rk

t = H rit + εt

In our numerical example 2 targets, Office & Industrial…

LHS:

t =Office Retns:

REIT 1 Retns

REIT 2 Retns

1 10% 7.5% 2.5%2 0% -2.5% -7.5%

Regress:RHS: LHS:

t =Indust Retns:

REIT 1 Retns

REIT 2 Retns

1 0% 7.5% 2.5%2 -10% -2.5% -7.5%

Regress:RHS:

TiiTi rrrH )()()(ˆ 1




5.0

5.1

075.0025.0

025.0075.0

075.0025.0

025.0075.0

075.0025.0

025.0075.0ˆ1 TT

officeH

e.g., For the office hedge…

5.1

5.0

075.0025.0

025.0075.0

075.0025.0

025.0075.0

075.0025.0

025.0075.0ˆ1 TT

retailH

& for the industrial hedge…



H(i) wts on: Office Indust

REIT 1 1.5 -0.5REIT 2 -0.5 1.5

H(i) weights for:

In our numerical example…

t =Office Retns:

Indust Retns:

1 10% = 0% =2 0% = -10% =(1.5)(-2.5%) + (-0.5)(-7.5%)

Indust hedge:(-0.5)7.5% + (1.5)2.5%(-0.5)(-2.5%) + (1.5)(-7.5%)

Office hedge:(1.5)7.5% + (-0.5)2.5%

Thus we replicate the target returns we were trying to hedge…

For each target k the N-dimensional vector of estimated coefficients on the hedge vehicles is the set of optimal weights on the individual hedge vehicles in the hedge portfolio (OLS for illustration).



Technical AppendixThe PureProperty method inverts the classical procedure

Target asset k does not trade liquidly and we cannot observe its liquid return (though it does trade illiquidly and we can thereby observe a less efficient – lagged – representation of its return)

Can observe:• Returns all periods t to a set of tradable hedge assets i = ri

t , where (i = 1, 2, …, N), namely, exchange-traded REITs.

• Holdings in all periods of all target assets k by all hedge assets i (the REITs’ property holdings), label this NxK matrix “Xt.”

Example: Hedge returns to k = Office, Industrial Properties:

Tradable hedge assets are two REITs i = 1, 2; Xt matrix is:

REIT (i ):Office

HoldingsIndust

Holdings1 75% 25%2 25% 75%



Assuming stock mkt efficiently reflects returns to Office & Industr properties in REIT returns, the returns, ri

t ,to the two REITs are (as before):

Period (t ):REIT 1

RetnREIT 2

Retn1 7.5% 2.5%2 -2.5% -7.5%

Perform cross-sectional regression of hedge asset returns onto target holdings shares:

rit = Xt,i (rk

t) + ηt,i

In our numerical example 2 periods…

LHS:

REIT:Period 2 Retns:

Office Holdings

Industr Holdings

1 -2.5% 75.0% 25.0%2 -7.5% 25.0% 75.0%

RHS:Regress:

LHS:

REIT:Period 1 Retns:

Office Holdings

Industr Holdings

1 7.5% 75.0% 25.0%2 2.5% 25.0% 75.0%

Regress:RHS:



For each period t the K-dimensional vector of estimated coefficients on the target holdings is the set of liquid returns on the target assets.

)()()()(ˆ1 i

tTi

tit

Tit

kt rXXXr

Perform cross-sectional regression of hedge asset returns onto K target holdings shares:

rit = Xt,i (rk

t) + ηt,i

In our numerical example, retrieve (previously unobservable)…

Office Indust1 10% 0%2 0% -10%

r(k ) returns for:Period t :



00.0

10.0

025.0

075.0

75.025.0

25.075.0

75.025.0

25.075.0

75.025.0

25.075.0ˆ

1

1

TT

kr

e.g., For Period 1…

& for Period 2…

)()()()(ˆ1 i

tTi

tit

Tit

kt rXXXr

10.0

00.0

075.0

025.0

75.025.0

25.075.0

75.025.0

25.075.0

75.025.0

25.075.0ˆ

1

2

TT

kr



The regression also recovers the NxK hedge portfolio weights, as: rk

t = H rit …

Tit

it

Tit XXXH )()()(ˆ 1


REIT 1 1.5 -0.5REIT 2 -0.5 1.5

H(i) weights for:

In our numerical example (as before)…

)()()()(ˆ1 i

tTi

tit

Tit

kt rXXXr

Office Indust1 10% 0%2 0% -10%

r(k ) returns for:Period t :

In our numerical example, retrieve (previously unobservable)…



Tit

it

Tit XXXH )()()(ˆ 1

H(i)

wts on: Office IndustREIT 1 1.5 -0.5REIT 2 -0.5 1.5

H(i) weights for:

These hedge portfolio weights represent long/short portfolios of REITs, weights which sum to 1.0 unit of exposure to the target property mkt sector and 0 exposure to all other sectors:

“Pureplay Portfolios”

t =Office Retns:

Indust Retns:

1 10% = 0% =2 0% = -10% =(1.5)(-2.5%) + (-0.5)(-7.5%)

Indust hedge:(-0.5)7.5% + (1.5)2.5%(-0.5)(-2.5%) + (1.5)(-7.5%)

Office hedge:(1.5)7.5% + (-0.5)2.5%

Thus (as before) we recover the (here unobservable) target returns we are interested in (pure office, pure industrial):

rkt = H ri

t …



5.15.0

5.05.1

75.025.0

25.075.0

75.025.0

25.075.0

75.025.0

25.075.0ˆ1 TT

H

e.g., For our Office & Retail PureProperty example…

Tit

it

Tit XXXH )()()(ˆ 1


REIT 1 1.5 -0.5REIT 2 -0.5 1.5

H(i) weights for:

t =Office Retns:

Indust Retns:

1 10% = 0% =2 0% = -10% =(1.5)(-2.5%) + (-0.5)(-7.5%)

Indust hedge:(-0.5)7.5% + (1.5)2.5%(-0.5)(-2.5%) + (1.5)(-7.5%)

Office hedge:(1.5)7.5% + (-0.5)2.5%


Domains of Macro-Level Real Estate Investment Decision Making:

1. Strategic Investment Policy & Decisions

2. Tactical Investment Policy & Decisions

3. Implementation of Investment Policy

Investors Lacking Sufficient Resources, Specialized Expertise, or Legal Authority to Directly Manage Their

Own Investments

The Professional Investment Management Industry

CLIENTS

SERVES

From CD Appendix 26A: The Institutional Landscape


“Fiduciary Relationship”

• Investment managers often operate in a “fiduciary relationship” with their investor clients.

• When the relationship is not strictly-speaking “fiduciary” in a legal sense, it often still has much of the same characteristics…

Fiduciary Relationship• Binds the agent in a role of trust for the principal party.

• Requires the agent to act in the best interest of the principal party.

• Requires certain standards of reporting & decision making, e.g.:

• The “Prudent Investor” Criterion.

• Legal fiduciary relationship sets up formal accountability, potential legal liability.



26.A2 Salient Features of Real Estate Investment Management

Characteristics of Real Estate Requiring Specialized Investment Expertise:• Underlying space markets highly segmented, heterogeneous (Ch.1).• Private asset mkt (search mkt trading of unique, whole assets) • Search function (must find individual assets)• Transaction execution (negotiation, deal structuring, closing)• Lack of asset mkt informational efficiency (asset price “noise,” inertia) Unique due

diligence & decision issues.• Asset operational mgt responsibility & opportunity

Operational Mgt Responsibility Important in L.R. Success:• High transaction costs Long holding periods Long time span over which

investor governs operations Can have meaningful impact on investment performance.

• Cash yield orientation of R.E. investment total return (mostly in y not g) Large part of investment performance directly impacted by on-going operations.



157

26.A3 Responsibilities & Functions of the Investment Manager

1) Investment advisory services:– How should client invest in R.E.: Strategy (allocation, styles), Tactics

(timing, reallocation, buy/sell), mgt (vehicles).

2) Asset selection and transaction execution: – “Acquisitions Dept” (but also dispositions).– Search, Find, Diligence, Negotiate/Structure, Close.

3) Investment product development:– Vehicles, Structures, Innovation? (arbitrage?).

4) Asset management:– “Asset Mgt Dept”– Portfolio-level, Responsible for “property mgt.”

5) Support functions: Communications & Research:– Gather, Analyze info, support investment decision making, firm

marketing, client communication.

Not all firms provide all five functions.



158

26.A4 Private Real Estate Investment Products• Open-End Co-mingled Funds (CREFs) or Unit Trusts (PUTs):

– On-going portfolio of properties (no finite life)– Investors can buy in (cash out) at regular frequent intervals (monthly, quarterly).– Based on NAV (appraisal-based) of fund.

• Closed-End funds or unit trusts & RELPs: – Portfolio of properties but– Investors can only buy in a beginning (capitalization phase, then fund is “closed”).– Planned liquidation after specified no. of years (but some flexibility).– “RELPs” marketed to individuals in 1980s (for tax shelter).

• Private REITs: – A way to structure R.E. funds.– Facilitates ownership transfer, potential IPO (“incubator REIT”)– >100 shareholders, 5/fewer

• Discretionary Separate Accounts: – Investor hires mgr to buy and manage properties on investor’s behalf, with the manager

having the discretion as to which properties to buy and sell. – Each separate account is managed on behalf of a single investor, allowing a more

“custom-tailored” service for larger investors.– For larger investors.

• Non-discretionary Separate Accounts– Even larger investors, requires some in-house R.E. expertise.


26.A5 The real estate investment management firm: objectives and strategic considerations

Clients’Perceptions,

Needs, & Preferences

Cap.MktEnv..& Events

R.E.Space & Asset Mkts

ManagerActions

Client Capital FlowTo/from Manager

Manager Investment

PerformanceFor

Clients

AssetsUnder

Management

Equity Returns&

Incentive Fee RevenueBase Fee Revenue

Value of Management Firm


Industry Associations and Real Estate Information Standards

• NCREIF (National Council of Real Estate Investment Fiduciaries)

• PREA (Pension Real Estate Association)

• NAREIM (National Association of Real Estate Investment Managers)

• NAREIT (National Association of REITs)

• CREFC (Commercial Real Estate Finance Council) For mortgages & CMBS.

AIMR(Association for Investment Management & Research):

• CFA designation• Investment Performance Reporting

Standards

Real Estate Information Standards (REIS)




Appendix 26B: Issues in Benchmarking Private Real Estate

• Population vs sample implications.• Controlling for risk.• Segment weighting in the benchmark

index.• Valuation methodology.• IRR vs TWRR benchmarking.


Population vs Sample Implications

Is the ideal benchmark index an entire population, or is it a sample?

What is the difference and why does it matter?

Census of entire population No need for statistical inference.

Sampling Can’t avoid statistical inference issues.

Ideal benchmark index = Entire peer universe population:• Practical feasibility to include entire peer universe (almost).• Legalistic function, Avoid “error” in comparisons.

Ideal asset class research index = Scientific sample:• Asset class too large, Census impractical.• But peer universe is not a “scientific” sample.

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Implications for appropriate index construction methodology…

N

itit r

Nr

1,

1

Index as Sample Equal-weighted returns (EW):

Index as Population Value-weighted returns (VW):

N

iti

t

tit r

V

Vr

1,

1

1,

Population vs Sample Implications

164


The Problem:

• The Capital Market naturally provides higher returns (on avg over LR) for “more risky” assets.

• Manager must not be able outperform benchmark simply by investing in more risky assets or using leverage.

• Hence, we need to CONTROL FOR RISK.

26B.4. Controlling for Risk

165


Two ways to control for risk:

• Quantitatively, using “risk-adjusted returns,” by adjusting the mgr’s ex post return to reflect the market’s “price of risk.”

• Non-quantitatively, using “style-based benchmarking,” by constraining manager to same style (similar-risk) assets, same style & risk as his benchmark.


166


i

fii

rrTR

Beta = Amount of “Risk” AS IT MATTERS TO THE CAPITAL MARKET.

This enables Portfolio “i”’s ex ante excess return, E[ri-rf], to be ADJUSTED FOR RISK.


The Quantitative Approach: e.g., The Treynor Ratio

167


The Quantitative Approach: e.g., The Treynor Ratio

Avg. Excess Return

Beta

SML

1

rM - rf

0

ri - rf

TRi

βi


168


26B.4. Controlling for RiskWithin the private real estate investment industry, we must rely primarily on the “Non-Quantitative” (Style-Based) Approach to controlling for risk. Why?

169


26B.4. Controlling for RiskWithin the private real estate investment industry, we must rely primarily on the “Non-Quantitative” (Style-Based) Approach to controlling for risk.

• We cannot effectively quantify risk in the private real estate asset class in the way that it matters to the capital market, so we cannot quantify risk-adjusted return measures with sufficient credibility for use in benchmarking.

• The property market cannot distinguish between the amount of risk in different types or locations of properties (so long as they are all “institutional-quality”).

170



Horiz. Axis is Beta wrt “National Wealth Portf,” but that doesn’t matter.

Within the private real estate investment industry, we must rely primarily on the “Non-Quantitative” (Style-Based) Approach to controlling for risk. Recall Ch.22 (sect.22.3)

171


At this level of detail, WITHIN A GIVEN STYLE of the (instl) R.E. asset class, the market cannot distinguish stable, reliable differences at the property level in “beta,” the risk that matters.


Therefore, we not only cannot, but we need not adjust for risk, as long as the manager & his benchmark are both confined WITHIN A GIVEN STYLE of the institutional RE asset class.

Within the private real estate investment industry, we must rely primarily on the “Non-Quantitative” (Style-Based) Approach to controlling for risk.

172


Real Estate “Styles” are a bit vaguely defined:• Domestic “Core”• Value-added/Opportunistic• International• etc (NCREIF currently working on standardized style

definitions).


Discrete style/risk categories defined by:• Property size limits;• Leverage limits;• Development project exposure limits (occupancy).

In practice, this approach requires considerable specification & elaboration betw agent & principal at outset of mgt contract, & perhaps on-going.

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Example:• Fund restricted to fully-stabilized core property investments, but

allows use of high leverage (up to 75%, at discretion of fund mgr).

• Appropriate benchmark & risk control could be either:

1. Peer universe of all (& only) other such funds, or

2. NCREIF Index adjusted for leverage using a WACC formula, with a pre-specified target leverage ratio:

rE = rD + (rP – rD)LRWhere: rE = Levered equity return,

rD = Debt return,

rP = Property (unlevered) return (NPI),

LR = Leverage ratio (V/E), pre-specified.

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26B.4. Controlling for RiskSome implications of style-based benchmarking:

• Fixed real return targets are not good benchmarks.

• Direct property investment should not generally be benchmarked against a REIT Index, however:

• Property operational level performance comparisons & attribution analyses may be of interest for diagnostic purposes at the property-level across all properties of a given type, including different types (or styles) of investor/owners.

• Comparisons across styles or peer groups are of interest at a broader level, relevant for strategic investment and asset class research (as opposed to agent performance evaluation benchmarking, per se).

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26B.1. Matching Evaluation, Responsibility, & Authority:Segment weighting in the benchmark index

Definition:Real estate asset market “segment”

= Property type & geographic location.

• Suppose manager has discretion to allocate capital across more than one segment.

• Then benchmark should include all the segments manager could choose among.

• But what should be the allocation weights across the segments in the benchmark index?

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• No single general rule for benchmark segment allocation weights.

• Weights should be “appropriate.” Should reflect: Client’s objectives for the manager; Manager’s specialization and; Manager’s range of discretion over allocation policy.

• General management principle involved is:

RESPONSIBILITY AUTHORITY

EVALUATION

Equate responsibility to authority, & evaluate accordingly.


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General implications:

• Peer universe sub-indexes should often be used to construct custom-weighted benchmark, with weights fixed in advance (i.e., NPI used only for benchmark within-segment return performance).

• Example: • Mgr hired to place capital into industrial & office properties at her

discretion:• Benchmark = 50% NPI Office + 50% NPI Industrial.

• In absence of clear reason otherwise, simple equal-weighting may make sense.

• Typical mgr will avoid bet against benchmark, so benchmark weight should reflect client’s allocation target objective. (e.g., skew weights accordingly).


178


Note:

Previous general point about fixing benchmark weights in advance to reflect client’s target objective for the mgr holds not only for market segment weighting in the benchmark, but also for other characteristics of the benchmark, such as the degree of leverage, the allocation across different styles (e.g., development exposure), etc. (e.g., for benchmarking a multi-style manager).


179


• A reasonable (& popular) alternative is to use the peer universe weights (e.g., NPI weights for the segments the mgr has discretion to invest in).

• Rationale is “client investability” criterion:– It’s what client would have gotten (ex ante) if they had chosen a

“typical” alternative (competing) mgr.

Other alternatives for benchmark segment weighting:


180


Other alternatives (continued):

• Theoretical alternative: Use market weights – Share of each segment in total asset class market value.

• Advantage of this approach:• May reflect mgr’s relative ability to find available properties.• May reflect relative ability of market to absorb new capital.

• Problems with this approach:• Since CAPM doesn’t work well for R.E., we don’t know if market

weights are theoretically optimal from a portfolio strategy perspective.

• Empirically it is difficult to precisely determine the market weights.


181


Ch. 25: Valuation Methodology

How asset & portfolio values are measured or estimated in constructing the benchmark index (and also in computing the subject manager’s performance record).

• Fundamental issue relevant not just for benchmarking.

• Issue that is unique and particular to private real estate.

Fundamental source of the problem is that in private real estate markets:• unique, whole assets are traded• infrequently and irregularly through time, • in deals that are privately negotiated between one buyer and

one seller.

(All three of these characteristics differ from securities mkts.)

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IRR vs TWRR Benchmarking

Benchmarking is an exercise in comparison of multi-period returns.

Recall from Chapter 9 that there are two types of multi-period return measures (TWRR & IRR), and that:

• TWRR is the standard performance measure in the securities industry and in traditional (“core”) real estate investment.

• TWRR is neutral with respect to the timing of capital flow in and out of the investment.

• IRR reflects such timing, and

• IRR can be computed without regular periodic “marking-to-market” (appraisals).

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IRR benchmarking is the standard practice in the private capital (e.g., “venture capital”) investment industry.

It is also appropriate for performance evaluation in at least two applications in the real estate investment industry:• Benchmarking certain types of “opportunistic” real estate

investments, most notably development projects.• Property-level performance attribution of the type described

earlier in this lecture.

Because, in both cases:• The subject investments are often not regularly marked-to-

market, and• The responsible investment managers (whose performance is

being evaluated) are largely responsible for cash flow timing decisions that can significantly effect returns.


184



IRR-Based benchmarking requires the use of:Inception-date Cohorts

(or “Acquisition-date cohorts”)

• IRR is computed since inception (or acquisition) of portfolio (or property).

• IRR is computed for appropriate benchmark cohort, defined as similar investments with same inception (or acquisition) date, over same period of time as subject.

• Benchmark cohort IRR normally “pooled” (all cash flows aggregated together each period).

• Terminal (current) value must be estimated for all assets remaining in pool at end of evaluation period, based on appraisal at terminal point in time.

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In real estate, IRR-based benchmarking will often require the use of simulated IRR cohorts as the benchmark, because of lack of sufficient data.

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