Market Memo
Real Estate Indexing:
Increasingly, Real Estate indices are used as a proxy for the private and highly illiquid real estate market. They are increasingly available; provide a range of geographies and industries and show closing prices on a consistent basis within an asset that often trades within non-transparent markets. Despite this, Real Estate Indices fail to provide a comparable representation of their underlying asset in the same fashion as publicly listed debt and equity investments. Subsequently, their overreliance may lead to unaccounted for risk exposure within real estate portfolios.
The challenges associated with using benchmarks to establish current and historical market conditions comes down to an accurate understanding of an asset’s underlying demand and subsequent pricing. Indexation and their liquid derivatives fall short of tracking these changes in real time due largely to their observation and measurement of Real Estate prices. Index’s attempt to compute real estate prices and returns through (1). Appraisals, (2). Financial market prices and (3). Adjusted privately traded prices or some combination there of. Assessing the intricacies of these methodologies warrants further and more in depth discussion, however in relation to active price tracking the illiquidity of the underlying assets still pose material challenges.
For Commercial properties the NCREIF Property Index (NPI), which can be found at www.ncreif.org is the most established and widely used index in the United States. The Index, published by the National Council of Real Estate Investment Fiduciaries (NCREIF) a not for profit industry organization, is derived from appraisals of its memberships properties. Quarterly, members of NCREIF are required to submit data regarding the value of their properties from which the prices of the index and sub-indexes (bifurcated by asset and geographic location) are computed.
Every Quarter members of NCREIF report the value of their assets based upon either DCF or the Comparable Sales method, the NPI is also reported every quarter however, NPI properties are not necessarily appraised every quarter. In fact, most properties are appraised once per year or once every two to three year periods. This largely results from the time, cost and energy required to conduct valuations and the requirement for appraisers to be paid. For members of NCREIF contributing to the NPI as well as for any other property owner, there is a balance between the cost and benefits. Instead of conducting and paying for frequent valuations it is not atypical for real estate owners to adjust past valuations to account for capital expenditures, often called “desktop appraisals.”
Even when appraisals are performed accurately and frequently, their use introduces the potential for data smoothing, which significantly alters the implied risk/return spectrum of the underlying assets. Data Smoothing occurs assessing returns when the prices used in have been dampened relative to the volatility of the real asset’s unobservable but underlying price. In the case of real estate, when appraisals are used in place of the asset’s true market value and provide dampened price changes, then the resulting return series persistently underestimates an understates the volatility of the true returns as well as their correlation with other asset classes within an investors portfolio.
For example, the NCREIF is calculated on an unleveraged basis as if the properties measured were acquired entirely with equity and no debt financing in order to reduce the volatility of their returns in relation to returns of real estate acquired with leverage. Subsequently, interest charges are not deducted. Additionally, NPI returns are calculated on a before tax basis and do not include income tax effects. Lastly, the returns are calculated on a property basis and then value-weighted for the index’s calculation where more highly valued properties receive a larger weighing. Data smoothing can be necessary to filter out white noise and irrelevant information but it is important to remember that it may also alter the nature of some significant takeaways.
It remains important to remember that appraisals conducted in any time series are not real time. They are always reflecting on a perceived value at particular period in time and since there is not the benefit of observing the future that period in time is always lagging. In addition to the potentially lagged nature of both the DCF and comparable properties approach being relatively backward looking, appraisals themselves maintain a very human element to their production making them highly susceptible to heuristics, biases and failures of judgment. In the case of appraisals, anchoring or the compulsion to overly rely on initial information further compounds challenges associated with the relevance of appraisals and data smoothing for indexation. In the case of appraisals it often manifests in the appraisers recollection of historical performance of a certain asset or geographic region without as much focus paid to current market conditions resulting in distorted prices between what is reported and what a buyer may be willing to offer. This may lead to inflated prices of real estate in a period of declining performance for the asset; alternatively it may lead to a compressed value during a period of growing market strength and increased demand.
The appraisal system itself is not real time and maintains an inherent lag and divergence to market prices that is amplified by the human element of return valuations. Although this is perfectly understandable considering the illiquidity of real estate, it often goes overlooked while assessing investment risk and portfolio performance. For example, assume you have two investments providing returns over five periods.
| HPR | Investment 1 | Investment 2 |
| 1 | -1.00% | -2.00% |
| 2 | 4.00% | 3.00% |
| 3 | 5.00% | 4.00% |
| 4 | -2.00% | -1.00% |
| 5 | 2.00% | 2.00% |
| Correlation | 96.28% | |
Assessed side by side, these investment maintained a high degree of correlation with one another, that is to say their return distributions were comparable in both their timing and size. Now, assume that Investment 2 is a index based off of highly illiquid assets. The index has the exact same returns however; they are reported one period later due to illiquidity and appraisal lags.
| HPR | Investment 1 | Investment 2 |
| 1 | -1.00% | 3.00% |
| 2 | 4.00% | 4.00% |
| 3 | 5.00% | -1.00% |
| 4 | -2.00% | 2.00% |
| Correlation | -35.14% | |
The true correlation between the returns of the two investments may be close to 96.28%. However, the measured correlations between the assets due to their lag is -35.14%. The underestimated correlation may indicate greater opportunities for diversification however, it also provides a glimpse at hidden portfolio risk.
Assessing risk-adjusted returns within the field of investment management is art as well as a science. Despite this, the imaginative necessity is often overlooked in relation to anything that maintains the illusion of objective facts. As an investment professional across any asset class, your expected to develop, underwrite and ultimately justify what is purchased, held and sold both at the time of entry as well as upon reversion (which in real estate can often be materially different). However at no point throughout an investment’s time horizon does the investor develop the ability to predict the future. Further complicating the matter, the leading indicators of the risk and return spectrum are established using historical information i.e. variance which ultimately shows not downside risk but deviation from the mean returns over whatever historical period is being examined. Real Estate Indexing does not create these conditions, however for institutional investors their ready availability greatly increases the tendency of fund managers to improperly allocate their exposure across asset classes.