Real estate pricing is a function of supply and demand. Since each market has different underlying demand drivers and supply constraint characteristics,
Market volatility, defined as beta (β), is not necessarily a negative feature. Markets with higher volatility often outperform the NPI index in an upturn of the real estate cycle. However, like leverage, this characteristic can also accentuate a market decline.
Applying theconcept of beta suggests a potential investment strategy during the anticipated real estate recovery, with an overweighting of high-beta property sectors and markets.
The total risk of a portfolio is comprised of market risk and asset specific risk. Asset specific risk can be diversified away while market risk cannot. Market risk is commonly measured as beta. Beta is a quantitative measure of the volatility of a market, a property sector or a portfolio relative to a broad market index.
Generally speaking, a beta of 1 indicates that the market’s returns move in line with the broad market index. A beta of 1.2 means that the asset’s return is likely 20% more volatile than the broad market index return, while a beta of 0.8 means that the asset’s return is 20% less volatile than the broad market index return.
The closer the connection to the economy, the higher the beta.
Using the above definition, we calculated beta for all five property sectors [Exhibit 1]. Despite having the highest average total return, the
This makes sense because hotels rely on daily room rentals, which suffer immediately and dramatically during economic downturns, but generally recover more quickly as well.
Historically, demand for office space is also sensitive to economic conditions, as employers have historically tended to overreact by hiring and firing too quickly in good times and bad.
The retail sector has historically had a beta slightly lower than the NPI index, supported by resilient consumer spending and longer leases. This longstanding trend may be changing, however, as the retail sector is experiencing a severe dislocation in the current downturn.
The apartment sector has the lowest beta among the five property sectors, as steady demand for housing has typically made it less sensitive to the economic environment than the other sectors.
We also calculated betas for four major property sectors for each of the metro areas tracked by the NCREIF index. Typically, a market with a higher beta relative to the NPI index tends to have higher returns when the index is increasing and lower returns when the index is decreasing.
To illustrate this market behavior, in Exhibit 2 we compare historic returns of two office markets — New York, a high-beta market, and Washington, D.C., a low-beta market.
The New York office market has shown greater volatility than the D.C. office market. The employment characteristics in these two markets likely explain some of this difference. New York’s economy is heavily weighted to the relatively volatile financial services industry, while the D.C. metro area has a concentration in historically less volatile sectors such as government, health care, education, and the defense industry.
Total returns for the New York office market have been much lower than the D.C. office market during the last two downturns, but significantly higher during the upturn [Exhibit 3].
Who benefits from beta?
We believe that understanding beta behavior may be useful in identifying opportunistic markets as well as in managing portfolio risk. An investment strategy focused on beta would seek higher returns by timing the real estate market cycle and taking on calculated market risk, with the goal of out-performing the market benchmark NPI index [Exhibit 4].
The strategy requires a thorough understanding of market fundamentals and an estimate of future market performance. In the early part of a market recovery it may be desirable to be overweight in the high-beta sectors and markets to maximize portfolio return. As the market moves towards a peak, the portfolio would shift to overweight the low beta sectors and markets in order to minimize potential losses during the downturn.
Of course, a portfolio with a higher beta will inherently have higher risk, which could negatively impact portfolio returns. In addition, the calculated betas shown here are derived from historic
David Lynn is managing director and head of U.S. research and investment strategy with ING Clarion based in New York.