Quantifying Real Estate Risk

This article addresses two major issues with the current practice of real estate investment analysis: 1) applying finance theory without modification and 2) ignoring illiquidity in formal analysis.The authors develop a new, closedform ex ante risk metric that quantifies illiquidity risk and integrates it with real estate price risk.Such integration provides a formal and easy-to-use analytical tool for real estate pricing and enables an apples-to-apples comparison between the performances of real estate and financial assets. Using commercial real estate data, the authors demonstrate that the conventional risk measure significantly understates the true risk of real estate. Their results also reveal the relative importance of price and illiquidity risk components to the total ex ante risk.

One of the most important differences between investing in private real estate and investing in financial assets is that real estate is a thinly traded market (i.e., investors cannot trade in and out of positions at the asset’s fair market value whenever desired). Unlike investors in the securities market, real estate investors face not only the risk of an uncertain asset price, but also the risk of illiquidity (i.e., the uncertain time necessary to make a sale). Correct investment decision making requires both risks to be properly measured against the asset’s expected return so that a fair comparison among alternative opportunities can be made.

Unfortunately, the current state-of-the-art of real estate valuation seems to have issues in properly measuring both of these risks. For example, a recent survey reported by the Yale School of Management (Goetzmann and Dhar [2005]) revealed that leading institutional investors and fund managers expressed two serious concerns about how investment decisions are made: 1) the accuracy and reliability of measuring real estate return and risk using historical data, and 2) the lack of a formal approach to handling the biggest risk factor—illiquidity risk. These concerns are clearly justified in light of the current practice of real estate valuation.

Take ex post real estate performance, for example; the convention is to compute single-period performance (i.e., the quarterly or annual return) from historic data (or index) to represent the periodic risk and return of a multiperiod investment. This may not be a problem with financial assets because the security returns over time are generally considered to be independent and identically distributed (i.i.d.). But it is problematic to real estate because real estate returns have been found to exhibit strong serial persistence and are not i.i.d. The non-i.i.d. nature of real estate returns implies that the ex post real estate performance is holding-period dependent. That is, the average return and risk per period vary across different investment horizons. Ignoring the time dependence of real estate returns leads to underestimation of ex post real estate risk, especially when real estate performance is compared with that of financial assets, such as in the context of mixed-asset portfolio construction.

If the ex post price risk is biased in the current real estate valuation, the illiquidity risk has been largely ignored. Currently, formal real estate investment analysis almost exclusively relies on the classical finance theories that are based on the paradigm of a complete and liquid market where assets are traded instantaneously and continuously. It is well understood that real estate does not fit into such a paradigm and that illiquidity risk can significantly alter an investor’s valuation decisions and portfolio selections because presumably any risk-averse investors must consider the potential loss of welfare due to the inability to sell at will. But in the absence of alternative theories, real estate researchers have to continue the practice of applying theories designed for the efficient and thickly traded securities market to the thinly traded real estate market. This implies a rather ironic reality—the valuation of the illiquid asset ignores illiquidity itself.

The objective of this article is to develop a formal analytical framework to address these two problems. Specifically, we develop a closed-form ex ante risk metric that converts and integrates illiquidity risk with real estate price risk. Such integration provides a formal analytical tool for illiquid asset pricing and enables apples-to-apples comparison between the performances of real estate and financial assets. Our results show that the periodic ex ante real estate risk is affected by the holding period through a trade-off effect: the illiquidity risk declines as holding period increases, while the price risk increases at the same time. Therefore, the total ex ante risk is not necessarily reduced by increasing the holding period. This offsetting effect suggests that an optimal holding period may exist, for which the overall real estate risk is minimized. Using real-world data, we provide an empirical demonstration of this insight and reveal the relative importance of price and illiquidity risk components to the total ex ante risk. Download the full article here.