Real Estate

Homes typically represent a substantial fraction of investor wealth. Are there reliable relationships between U.S. home prices and the U.S. stock market? For example, does a rising stock market stimulate home prices? Do falling home prices point to offsetting liquidation of equity positions. Do homes effectively diversify equity holdings? Measurements are:

• Monthly levels of the non-seasonally adjusted S&P/Case-Shiller U.S. National Home Price Index (Home Price Index) during January 1987 through February 2021 (34 years), with release lag about two months.
• Annual median sales prices for existing homes pieced from from RealEstateABC.com [no longer available], National Association of Realtors and Federal Reserve Bank of St. Louis during 1968 through 2020 (53 years).
• Annual median sales prices for new homes during 1963 through 2020 (58 years), and contemporaneous levels of the S&P 500 Index.

Using these sources, we find that:

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What is the total return to U.S. single family (house) rentals? In their February 2021 paper entitled “Total Returns to Single Family Rentals”, Andrew Demers and Andrea Eisfeldt analyze total returns to U.S. single family rentals, decomposed into net rental yield and house price appreciation. To estimate net rental yields, they:

• Weight city-level gross rental yields by number of rental houses in each ranked tenth (decile) of house prices to account for prevalence of low-priced houses.
• Empirically estimate rental operating and renovation costs as a fraction of home value, size or rent.
• Apply state-specific or city-specific real estate taxes and vacancy rates.

Using monthly home prices and rental estimate inputs by zip code for the 30 largest U.S. cities during 1986 through 2014, they find that: Keep Reading

What returns and risk should investors expect from private property (real estate, privately owned infrastructure, collectibles and non-corporate business equity), characterized by infrequent trading, inexact market values and noisy returns? In their March 2021 paper entitled “Real and Private-Value Assets”, William Goetzmann, Christophe Spaenjers and Stijn Van Nieuwerburgh survey current research on private property returns and risks. They provide a rough value of U.S. private property and summarize research findings from 11 papers, focusing on: measurement of risk, return and liquidity; and, (2) drivers of variation in valuations and investment behavior. Based on relevant government and association data and recent/current papers, they find that: Keep Reading

Personal residences represent the largest asset class allocation for many U.S. investors. What return do they generate, how do their returns relate to stock market returns and how do they vary across Metropolitan Statistical Areas (MSA)? In their January 2019 paper entitled “The Cross-Section of Expected Housing Returns”, Esther Eiling, Erasmo Giambona, Ricardo Lopez Aliouchkin and Patrick Tuijp examine how U.S. residential real estate returns vary across MSAs. They also examine relationships between MSA residential real estate returns and both U.S. stock market returns and overall U.S. residential real estate returns. Using monthly Zillow Home Value Index levels for 571 MSAs, zip code population data from the U.S. Census Bureau and U.S. stock market returns during April 1996 through December 2016, they find that:

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How do housing, equities and government bonds/bills perform worldwide over the long run? In their February 2018 paper entitled “The Rate of Return on Everything, 1870-2015”, Òscar Jordà, Katharina Knoll, Dmitry Kuvshinov, Moritz Schularick and Alan Taylor address the following questions:

1. What is the aggregate real return on investments?
2. Is it higher than economic growth rate and, if so, by how much?
3. Do asset class returns tend to decline over time?
4. Which asset class performs best?

To do so, they compile long-term annual gross returns from market data for housing, equities, government bonds and short-term bills across 16 developed countries (Australia, Belgium, Denmark, Finland, France, Germany, Italy, Japan, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, the UK and the U.S.). They decompose housing and equity performances into capital gains, investment incomes (yield) and total returns (sum of the two). For equities, they employ capitalization-weighted indexes to the extent possible. For housing, they model returns based on country-specific benchmark rent-price ratios. Using the specified annual returns for 1870 through 2015, they find that:

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Are illiquid assets competitive as investments with liquid financial assets over the long run? In his March 2016 paper entitled “The Long-Term Returns to Durable Assets”, Christophe Spaenjers summarizes long-term returns for three types of illiquid assets since the start of the 20th century:

1. Houses and farmland.
2. Collectibles (art, stamps, wine and violins).
3. Gold, silver and diamonds.

He focuses on capital gains but comments on ancillary costs and potential associated income where relevant. Using available monthly price indexes for these assets from a variety of sources during 1900 through 2014, he finds that: Keep Reading

Which is worse with respect to sustaining retirement income: sacrificing potential investment portfolio growth early, or exposing mortgage debt to interest rates later? In his November 2015 paper entitled “Incorporating Home Equity into a Retirement Income Strategy”, Wade Pfau simulates different strategies for incorporating home equity into a retirement plan (both income assurance and legacy) via a Home Equity Conversion Mortgage (reverse mortgage). A reverse mortgage is a non-recourse loan that enables many U.S. homeowners to tap (untaxed) up to $625,000 of home value. The different strategies are:

1. Ignore Home Equity: A baseline not comparable to the other strategies.
2. Home Equity as Last Resort: Delay opening a reverse mortgage line of credit until the investment portfolio is exhausted.
3. Use Home Equity First: Open a reverse mortgage line of credit at the start of retirement and draw upon it first, letting the investment portfolio grow.
4. Sacks and Sacks Coordination Strategy: Open a reverse mortgage line of credit at the start of retirement. Draw upon it (until exhausted, with no repayments) only after years when the investment portfolio loses money.
5. Texas Tech Coordination Strategy: Open a reverse mortgage line of credit at the start of retirement. Draws upon it (until exhausted) when investment portfolio balance falls below an estimated 80% of a required wealth glidepath. Pay it down when investment portfolio balance rises above an estimated 80% of required wealth glidepath.
6. Use Home Equity Last: Open a reverse mortgage line of credit at the start of retirement. Use it only after the investment portfolio is exhausted.
7. Use Tenure Payment: At the start of retirement, implement a reverse mortgage tenure payment (life annuity) option, with the balance of annual spending drawn from the investment portfolio.

For each strategy, he runs 10,000 Monte Carlo simulations of a 40-year retirement based on historical annual distributions of 10-year bond yield, equity premium, home appreciation, short-term interest rate and inflation rate. Annual withdrawals and investment portfolio rebalancings (to 50% stocks and 50% bonds) occur at the start of each year. Assuming initial home value $500,000, initial tax-deferred investment portfolio value $1 million, annual withdrawal 4% of initial investment portfolio value ($40,000, subsequently adjusted for inflation) and marginal tax rate 25% for investment portfolio withdrawals, he finds that: Keep Reading

Is producing real estate (farmland, timberland, energy delivery infrastructure and commercial properties) a good investment? In his May 2013 paper entitled “The Performance of Direct Investments in Real Assets: Natural Resources, Infrastructure and Commercial Real Estate”, Martijn Cremers investigates the performance of direct investments in natural resources (farmland and timberland), energy infrastructure Master Limited Partnerships (MLP) and commercial real estate. He considers return, risk‐return trade‐off, downside risk, diversification benefits relative to U.S. stocks and U.S. Treasury bonds, exposure to stock market shocks and inflation hedging power. Data for natural resources and commercial real estate investments are voluntarily reported by members (mostly pension funds) of a U.S. trade association. These data include property management fees. Data for energy infrastructure investments are based on the Alerian MLP Infrastructure Index, reflecting the performance of 25 publicly traded MLPs. Using quarterly and annual investment performance data during 1978 through 2012 for real estate and monthly data during 1996 through 2012 for energy infrastructure, he finds that: Keep Reading

A subscriber suggested testing the diversification power of SPDR Barclays International Real Estate (RWX) as a distinct asset class. To check, we add RWX to the following mix of asset class proxies (the same used in “Simple Asset Class ETF Momentum Strategy”):

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for RWX and the average pairwise correlation of RWX monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without RWX. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for RWX and the above nine asset class proxies from April 2007 (first return available for RWX) through April 2013 (73 monthly returns), we find that: Keep Reading

Are returns on real estate usefully predictable? In the June 2012 version of their book chapter entitled “Forecasting Real Estate Prices”, Eric Ghysels, Alberto Plazzi, Walter Torous and Rossen Valkanov examine the evidence of predictability in U.S. residential and commercial real estate markets. They review methodologies used in constructing widely used real estate price indexes. They then survey the key empirical findings from academic studies of short-run momentum and long-run reversals in real estate returns. Finally, they test the ability of different variables (past stock market return, stock market dividend yield, 3-month Treasury bill (T-bill) yield relative to its 12-month moving average, inflation rate, term spread between 5-year and 3-month maturities, combination of forward interest rates and industrial production growth) to predict real estate returns as calculated from several price indexes and a real estate investment trust (REIT) index. Using monthly and quarterly index levels for the real estate market proxies and values for the predictive variables as available, focusing on 1991 through 2010, they find that: Keep Reading