Replicating Residential Real Estate Returns with Liquid Market Instruments a Case for Risk Factor Models for Everything and Everywhere

Replicating Residential Real Estate Returns with Liquid Market Instruments A Case for Risk Factor Models for Everything and Everywhere

Emilian Belev, CFA and Richard Gold Northfield Information Services, Inc. January, 2017 Webinar Is Residential Special?

• Valuation of housing inventory in the USA north of $30 Trillion

• Increased interest in direct investment from domestic and foreign institutions and individuals

• About a quarter to a third of this valuation is covered by outstanding mortgage debt; Lenders and households exposed to the downside: notoriously so in 2007-2009, a.k.a. GFC

• Homeowners, especially those intending to sell will be interested in products that will help hedge the value of their homes

• First time home-buyers saving for a down payment will be interested in investment products that mimic the returns of their intended purchase

www.northinfo.com Slide 2 Is it Special (cont’d) ?

• Real estate backs MBS and property taxes back municipal obligations. Both of which are trillion dollar asset classes

• By implication, the credit worthiness of these securities determines liquidity of interbank lending and as such the stability of the financial system

• Finally, but equally important, residential real estate is the biggest household assets for the vast majority of Americans, and as such one of a handful of key gauges of consumer confidence and national prosperity

www.northinfo.com Slide 3 Comparison with Commercial Real Estate

• Commercial Real Estate values are derived from rental lease streams. • Investor value is the value net of debt on the property.

• Residential real estate, unless purchased for investment purposes, in which case it starts to resemble more multifamily commercial real estate, derives its value from the utility of prospective residents to have a roof over their head.

• Instinctively, some economists try to measure this utility by “substitute” – rental values. Even empirically this has proved flawed as there are prolonged periods of time where rents and home values don’t move in lock step.

• Instead, we employ a concept of Effective Economic Rent

www.northinfo.com Slide 4 Effective Economic Rent Explained

• To identify it we strip the effect of leverage and the borrowing costs from home prices

• What remains is the effect of the “natural” purchasing power of prospective residents in the locality (a.k.a. “demand” or “income effect”), against the supply of housing inventory there.

• Rent is only as much a substitute as there is a clear equivalence of quality of rental and housing properties. Given that they normally appeal to different market segments, that assumption holds only partially.

• Buyers will be enticed to rent if the discount is sufficient to compensate for the compromise on quality. Renters will be enticed to buy if the home price discount is sufficient to compromise on flexibility and risk, but also face borrowing constraints. Inside this “collar” there is “substitution” effect between renting and homewnership.

www.northinfo.com Slide 5 Effective Rent Explained (cont’d)

• The effective economic rent is a concept that empirically takes into account both the “income” and “substitution” effects simultaneously

• Provided a house price level “Asset”, leverage “LTV”, average economic life of residential property “T”, mortgage rate “c”, mortgage payment “M”, periodic personal benefit “PPB “ while paying mortgage, and personal discount rate “d”, we derive economic rent “R” using the following identities:

• Asset = Equity + Liability

• Asset = PPB/(1+d)^T + M/(1+c)^T + [(R/d)/(1+d)^T]

• LTV = M/(1+c)^T / Asset

• PPB + M = R

www.northinfo.com Slide 6 S&P CoreLogic Case-Shiller Home Price Indices

• Repeat sales index: • Calculates change in value for a home adjusted for size and quality • Coverage: 20 U.S. metros as well as three price tiers (low, medium, and high) • Individual market and composite indices available for 10 and 20 city averages • Monthly index but employs three month moving average to bolster sample size arising from delays in data flows from county records

www.northinfo.com Slide 7 Federal Finance Housing Agency HPI

• Sample from securitized or purchased by Fannie Mae or Freddie Mac started in 1975 • Broad measure of home price movements: • Geographic coverage: • All-Transaction Index – All metro areas and states • Purchase-Only Index – Top 100 metros and all states • Data from conforming Freddie and Fannie mortgages • Both refinanced loans as well as sales depending on index used

www.northinfo.com Slide 8 Differences Between Case-Shiller & NHPI

1. NHPI’s geographic coverage is broader: a) Includes transactions in all states and more metro areas. 2. NHPI is an equal-weighted index while Case-Shiller is a value-weighted index. a) Expensive homes have a greater impact on the Case-Shiller Index 3. The NHPI calculates two indices: a) The “All-Transactions” Index which contains both sales and refinancing transactions with the latter relying on appraised-values b) The “Purchase-Only” Index which uses only sales price data c) Therefore, appraisal bias is less prevalent in the Case-Shiller if the NHPI All- Transactions Index is used. 4. FHFA's data comes from Fannie Mae and Freddie Mac conforming mortgages. S&P/Case-Shiller relies on data secured from county assessor and recorder offices.

www.northinfo.com Slide 9 The Global Total Portfolio Risk problem

• Multiple portfolios with diverse characteristics

• Across countries, across asset classes

• Asset classes such as convertible bonds and derivatives have complex properties

• Asset classes such as private equity, private equity real estate, and infrastructure, have no visible pricing, return, or risk information

www.northinfo.com Slide 10

Segregated Solutions

• One approach: model asset class separately and aggregate risk only through covariance matrix:

• Overall covariance matrix resembles a chessboard where each square is a sub-model segment of the covariance matrix

• As aggregate number of factors increases relative to the limited number of observations, the matrix becomes unstable

• Fixing the problem by extending the historic observation period of the sub-models discounts the importance of the dynamics in the market place embedded in more recent observations

• Illiquid Assets Compound the Total Portfolio Problem. Current Illiquid modeling practice produces yet another silo factor set in the total portfolio covariance matrix

www.northinfo.com Slide 11 Fully Integrated Approach

• Employ a single parsimonious factor model across all asset classes across all geographies

• All investable assets are related to the same consistent set of factors, so interrelationships are easily observed and understood

• Limited number of factors allows for stable estimation of factor relationships, and fluid regime shifts

www.northinfo.com Slide 12 The Everything Everywhere (EE) Risk Model

• GEOGRAPHY: Five regional indices

• INDUSTRY: Six sector indices with global constituents

• ECONOMIC: • Return of Salomon Smith Barney WGBI • Percent changes in oil prices

• INVESTOR SENTIMENT / STYLE: • Dividend Yield • Market Development • Size

www.northinfo.com Slide 13 EE Factor Structure (contd.)

• CURRENCY: 69 currency factors indicating the denomination currency of a position

• CURVE: • Parallel Shift in Treasury Term Structure of Interest Rates • Changes in Slope of Term Structure – “Twist” • Changes in Curvature of Term Structure – “Butterfly”

www.northinfo.com Slide 14 EE Security Universe • Global Equities (~70 thousand instruments)

• Global Sovereign and Corporate Bonds (~600 thousand) • 2013 PRMIA Award for New Frontiers in Risk Management

• Asset-Backed Securities, Structured products, and customized coverage (~1.5 million)

• Municipal Bonds (~1.3 million)

• Futures, forwards, options on equities, currencies, interest rates, and bonds, Interest Rate and Credit Default Swaps (on demand OTC processing)

• Mutual and Hedge Funds (40 thousand global universe of funds, extensible on demand)

• Direct Real Estate, Infrastructure, and Private Equity (virtually all markets around the globe) • 2015 ARES Best Practitioner Research Award

www.northinfo.com Slide 15 Replication Fits: Economic Rent-Based on CS

8 Note: stock returns in replicating portfolio incorporate a moving average

Economic Rent CS

4 Replicating Portfolio

05/01/2010 07/01/2010 09/01/2010 11/01/2010 01/01/2011 03/01/2011 05/01/2011 07/01/2011 09/01/2011 11/01/2011 01/01/2012 03/01/2012 05/01/2012 07/01/2012 09/01/2012 11/01/2012 01/01/2013 03/01/2013 05/01/2013 07/01/2013 09/01/2013 11/01/2013 01/01/2014 03/01/2014 05/01/2014 07/01/2014 09/01/2014 11/01/2014 -2

-4

www.northinfo.com Slide 16 Replication Fits: USA - 2014

2.5

1.5

0.5

-0.5 05/01/2010 07/01/2010 09/01/2010 11/01/2010 01/01/2011 03/01/2011 05/01/2011 07/01/2011 09/01/2011 11/01/2011 01/01/2012 03/01/2012 05/01/2012 07/01/2012 09/01/2012 11/01/2012 01/01/2013 03/01/2013 05/01/2013 07/01/2013 09/01/2013 11/01/2013 01/01/2014 03/01/2014 05/01/2014 07/01/2014 09/01/2014 11/01/2014

-1 Replicating Portfolio HPI_US_2014_fit -1.5

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www.northinfo.com Slide 17 Replication Fits: USA - 2016

2.5 Replicating Portfolio HPI_US_2016_fit 2

1.5

0.5

-1

www.northinfo.com Slide 18 Replication Fits: West South Central

2.5

1.5

0.5

-0.5

-1 Replicating Portfolio

-1.5 HPI_West_South_Central

-2 www.northinfo.com Slide 19 Replication Fits: South Atlantic

-1

Replicating Portfolio HPI_South_Atlantic -2

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www.northinfo.com Slide 20 Replication Fits: West North Central

-1 05/01/2010 07/01/2010 09/01/2010 11/01/2010 01/01/2011 03/01/2011 05/01/2011 07/01/2011 09/01/2011 11/01/2011 01/01/2012 03/01/2012 05/01/2012 07/01/2012 09/01/2012 11/01/2012 01/01/2013 03/01/2013 05/01/2013 07/01/2013 09/01/2013 11/01/2013 01/01/2014 03/01/2014 05/01/2014 07/01/2014 09/01/2014 11/01/2014 Replicating Portfolio HPI_West_North_Central -2

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www.northinfo.com Slide 21 Replication Fits: Pacific

4 HPI_Pacific Replicating Portfolio 3

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-2

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www.northinfo.com Slide 22 Replication Fits: New England

4 HPI_New_England Replicating Portfolio 3

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-2

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www.northinfo.com Slide 23 Replication Fits: Mountain

4 HPI_Mountain Replicating Portfolio 3

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www.northinfo.com Slide 24 Replication Fits: North East Central

-2 Replicating Portfolio -3 HPI_North_East_Central

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www.northinfo.com Slide 25 Replication Fits: South East Central

-2

-3 HPI_South_East_Central

Replicating Portfolio -4

www.northinfo.com Slide 26 Replication Fits: Mid Atlantic

2.5 Replicating Portfolio 2 HPI_Mid_Atlantic

1.5

0.5

-1

-1.5

-2

www.northinfo.com Slide 27 Risk Factor Exposures

Factor Optimizaiton1 Optimizaiton2 Optimizaiton3 INDUSTRIAL SECTOR 0.030980322 0.022756358 0.024432894 CONSUMER SECTOR 0.081159073 0.084154002 0.089138552 TECHNOLOGY&HEALTH SECTOR 0.191926044 0.276925396 0.207423377 INTEREST RATE SENSITIVE SECTR 0.141104071 0.136105467 0.143820859 NON-ENERGY MINERALS 0.04319827 0.029567349 0.041023999 ENERGY MINERAL SECTOR 0.017258375 0.048188838 0.027947899 S B WORLD GOVT BOND INDEX -0.235982572 -0.026811777 -0.143916188 OIL PRICES IN USD 0.065396552 0.054977387 0.049067327 DEVELOPING MARKET 0.090006271 0.08673962 0.088854916 SIZE -0.297678693 -0.317667146 -0.316011571 VALUE/GROWTH 0.680480483 0.435687836 0.491999391 BLIND FACTOR 1 0.526721236 0.208550322 0.508753844 BLIND FACTOR 2 -0.21176603 -0.207971338 -0.196870845 BLIND FACTOR 3 0.157699747 0.437795589 0.323620847 BLIND FACTOR 4 0.2721833 0.179035919 0.387538895 BLIND FACTOR 5 -0.318734674 -0.160575202 -0.118455714

www.northinfo.com Slide 28 Out of Sample Replication

• Using optimizing techniques is useful in creating stable risk factor exposures

• However, out-of-sample forward-looking performance needs more robust techniques that are based on economic relationships

• Equal-weighted industry-based portfolios are less subject to idiosyncratic risk and as such expectedly more stable

• We limit the “optimization buy list” to industries whose returns have direct, and in most cases proportional economic linkages to residential real estate.

www.northinfo.com Slide 29 Single Industry Performance vs. National Case-Shiller Index

5 Northfield Industry A Case Shiller 4

-1

-2

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www.northinfo.com Slide 30 Out-of-Sample Optimized Performance

2.5

1.5

1 Portfolio A Portfolio B Portfolio C 0.5 Portfolio D Portfolio E 0 Case Shiller

-0.5 02/01/2011 04/01/2011 06/01/2011 08/01/2011 10/01/2011 12/01/2011 02/01/2012 04/01/2012 06/01/2012 08/01/2012 10/01/2012 12/01/2012 02/01/2013 04/01/2013 06/01/2013 08/01/2013 10/01/2013 12/01/2013 02/01/2014 04/01/2014 06/01/2014 08/01/2014 10/01/2014 12/01/2014 02/01/2015 04/01/2015

-1

-1.5

www.northinfo.com Slide 31 Can we do better ?

• Yes, in general long short portfolios tend to produce much tighter fits in our optimization work

• Something simpler can be done.

• Looking at previous graph looks like smoothly adjusting the cash drain / cash leverage can produce returns much more in line with the followed index

www.northinfo.com Slide 32 Out of Sample With Dynamic Cash

2 Portfolio A Portfolio B 1 Portfolio C Portfolio D 0 Portfolio E Case Shiller -1

-2

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www.northinfo.com Slide 33 Interesting Observation about LTV and Cash Content

Holding Percent

Industry A 2.2 LTV annual average Year for new mortgages (source FHLMC) Industry B 5.3 2008 0.73 Industry C 9.6 2009 0.68 Industry D 12.0 2010 0.79

*$$$ 70.9 2011 0.78

2012 0.78

2013 0.77

2014 0.76

www.northinfo.com Slide 34 Single Industry Performance vs. Case-Shiller Index 1 yr later

Northfield Industry A 5 Case S.

-1

www.northinfo.com Slide 35 Case-Shiller Index Levels

www.northinfo.com Slide 36 Case-Shiller and NIS Industry “A” Performance

120

115

110

105

Northfield Industry A 100 Case Shiller

www.northinfo.com Slide 37 Same Comparison Several Months Later

106

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102

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100

99 Northfield Industry A 98 Case Shiller 97

96 03/01/2016 04/01/2016 05/01/2016 06/01/2016 07/01/2016 08/01/2016 09/01/2016

www.northinfo.com Slide 38 Dr. Nefario’s Principle

• Any object that has been shrunk with a Shrink Ray will eventually return to its normal size, the bigger the original object, the quicker it will return to its original size (Source: Despicable Me).

• Corollary applied to return correlations derived from level correlations : Otherwise stable correlations might get blurred or reverse sign but eventually are expected to return to their normal levels

• In other words: If two cyclical series have strong (positive or negative) correlation, the proportional change transformations of the series can have either the same sign as the original series or the opposite, provided that the turning points in the series occur at approximately the same points, and the convexity of the original series remains unchanged on the increase or decrease of the series. Lesson: Stick to your guns

www.northinfo.com Slide 39 The Options

• Backward/Forward Contracts

• Another not so obvious but real world option is…. Options • A portfolio of liquid and common type of options can achieves the smoothing • Portfolio is self-financing when the expiry of the options is the span of the smoothing average (costless hedge) • If expiry is less than average span, investor pays a moderate premium for the portfolio (cost of hedge) given that they are buying into a partly pre-visible average (smoothed) value into the future

www.northinfo.com Slide 40 Index-like Smoothing with Derivatives

86 Derivative Replication 84 Strategy

82 Simulated Performance of 80 Real Estate Index (scaled to 100 based value) 78

76 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

www.northinfo.com Slide 41 Conclusion

• Important milestone in risk modelling of • Directly owned residential real estate • Mortgages • Municipal debt

• Also a gateway to providing important investment and hedging products for both institutions and individuals

• Stable estimation of risk exposures, portfolio weights, and good out of sample performance

• Connects seamlessly even this asset class in the framework of multi-asset class portfolio risk management without creation of a new silo

• The approach can be applied both to Case Shiller as well as NHPI indices.