The Impact of Market Imperfections on Real Estate Returns and Optimal Investor Portfolios

This study investigates the consequences of several imperfections associated with real estate markets on pricing and optimal investor portfolios from a CAPM context. CAPM assumptions are relaxed to recognize illiquidity, the consumption and investment attributes of owner-occupied housing, and a mildly segmented market structure. The study finds that relaxing the CAPM assumptions lead to a separate pricing paradigm for financial assets, income-producing real estate and owner-occupied housing respectively, that a "dividend effect" arises for real estate as the result of illiquidity, and that illiquidity reduces the extent to which investors hold real estate in their portfolios.     

Commercial Real Estate Returns

In the commercial real estate market, which is perceived to be relatively inefficient, investors have comparative advantages; hence there are significant costs to diversification. This paper presents for the first time a series of market (or quasi-market) returns for a large data base. This data base is believed to be the most complete commercial real estate data base yet constructed. The paper empirically evaluates the benefits of diversification along various dimensions within the commercial real estate opportunity set. The analysis confirms certain aspects of prior work concerning inflation protection and diversification opportunities while concluding that even investment grade real estate investments are heterogeneous assets.     

Clustering Methods for Real Estate Portfolios

A clustering algorithm is applied to effective rents for twenty-one metropolitan U.S. office markets, and to twenty-two metropolitan markets using vacancy data. It provides support for the conjecture that there exists a few major "families" of cities: including an oil and gas group and an industrial Northeast group. Unlike other clustering studies, we find strong evidence of bicoastal city associations among cities such as Boston and Los Angeles. We present a bootstrapping methodology for investigating the robustness of the clustering algorithm, and develop a means for testing the significance of city associations. While the analysis is limited to aggregate rent and vacancy data, the results provide a guideline for the further application of cluster analysis to other types of real estate and economic information.     

The Motivation for Institutional Real Estate Sales and Implications for Asset Class Returns

Since real estate assets are sold infrequently, analyses that use samples of exclusively sold properties to estimate pricing models may be seriously in error. This paper uses data on samples of sold and unsold properties and an appropriate statistical methodology to evaluate the extent of this bias. The results clearly show that it is important to control for sales motivations and that pricing equations that ignore this source of bias may be misleading.     

Appraisal-Based Real Estate Returns under Alternative Market Regimes

In this article we use Monte Carlo simulation to study the statistical properties of real estate returns. We set up a model where transactions prices are noisy signals of true prices. We then consider a number of appraisal rules, derived from Bayesian and non-Bayesian theory, to estimate the current true price and rate of return. The class of exponential smoothing and Kalman filter rules perform well at both the disaggregate (returns on an individual property) and aggregate (returns on a real property portfolio) levels. A special case of exponential smoothing (α= 1.0) places all weight on current market data. Since this case eliminates smoothing, our results suggest that appraisers should place all weight on current data (no weight on past data) provided that they want to estimate returns rather than values. However, these results should be used with caution if sales prices are very noisy.     

A Different Look at Commercial Real Estate Returns

Commercial real estate makes up a relatively small percentage of most institutional portfolios, even though the existing literature has consistently reported attractive risk-return characteristics that would suggest much larger allocations. This discrepancy has been explained by a perceived lack of comparability between return series calculated for real estate and those calculated for other asset classes. Just as investors actively involved in the futures markets do not consider individual common stocks to be traded continuously, those active in the stock market do not consider real estate to be traded continuously. In both cases, adjustments to reported returns are necessary to achieve a degree of comparability. This study makes such adjustments, using sales data from properties that help comprise the National Council of Real Estate Investment Fiduciaries / Frank Russell Company (NCREIF/FRC) Index to generate a "transaction-driven" commercial real estate return series. Examination of the risk-return characteristics of this series shows that it is quite different from traditionally reported real estate return series and far more consistent with risk-return characteristics that have been reported for other asset classes.     

Transactions-Driven Commercial Real Estate Returns: The Panacea to Asset Allocation Models?

A transactions-driven commercial real estate return series is generated in this study to determine whether the reliance on appraised values in the estimation of real estate returns is the source of the reported underpricing of real estate relative to stocks, bonds, and bills when analyzed in a traditional mean-variance setting. The reported underpricing of commercial real estate would be rational if transactions-driven returns exhibit more variance than appraisal-driven returns. While we find that transactions-driven real estate returns have greater variance than appraisal-driven returns for individual properties, most of the individual property risk is idiosyncratic and diversified away at the portfolio level. Real estate continues to be a dominate asset class in mean-variance allocation models even when represented with transactions-driven indices.¹     

Estimating Returns on Commercial Real Estate: A New Methodology Using Latent-Variable Models

Despite their widespreao use as benchmarks of U.S. commercial real estate returns, indexes produced by the National Council of Real Estate Investment Fiduciaries (NCREIF) are subject to measurement problems that severely impair their ability to capture the true risk–return characteristics–especially volatility–of privately held commercial real estate. We utilize latent-variable statistical methods to estimate an alternative index of privately held (unsecuritized) commercial real estate returns. Latent-variable methods have been extensively applied in the behavioral sciences and, more recently, in finance and economics. Unlike factor analysis or other unconditional statistical approaches, latent variable models allow us to extract interpretable common information about unobserved private real estate returns using the information contained in various competing measures of returns that are measured with error. We find that our latent-variable real estate return series is approximately twice as volatile as the aggregate NCREIF total return index, but less than half as volatile as the NAREIT equity index. Overall, our results strongly support the use of latent-variable statistical models in the construction of return series for commercial real estate.     

The Effects of the Real Estate Crisis on Institutional Stock Prices

This article investigates the contagious movement of financial institutions' common stock prices in response to real estate news. The basic hypothesis is that because real estate assets are traded infrequently, the market has incomplete information about their true value. The stock price reaction by banks, thrifts and insurance companies to announcements of poorly performing real estate portfolios is studied. Consistent with the hypothesis, significantly negative reactions obtain, both within and across industries, to these announcements. Reflecting the differential regulatory environment and disclosure policies, insurance companies, in general, react more strongly to adverse real estate news. Also, the price reaction of an individual firm is significantly associated with the level of its real estate exposure.     

Institutional Portfolios: Diversification through Farmland Investment

This article demonstrates that farmland can enhance the overall performance of institutional portfolios which are currently dominated by stocks, bonds, and business real estate. Unlike previous articles on farmland returns, this article addresses the issue of "smoothing bias" associated with appraisal-based farmland returns. Improved measures of income returns to farmland are also used in developing the estimates of optimal portfolios. Parametric testing revealed that farmland continues to enter the optimal portfolios even for large increases in the variance or for large reductions in the annual returns to farmland.     

Thrift Asset-Class Returns and the Efficient Diversification of Thrift Institution Portfolios

We estimate quarterly return series from March 1984 through December 1989 for 10 classes of thrift assets using the statistical cost-accounting methodology of Hester and Zoellner (1966). We then use these return series to estimate mean-variance efficient frontiers for all thrifts, for thrifts that were well capitalized two years earlier and for thrifts that were insolvent two years earlier. Our results show that neither the asset restrictions existing before nor those in effect after passage of the Financial Institutions Reform, Recovery and Enforcement Act of 1989 would have prevented thrifts from reaching most of the portfolios along the efficient frontier. The actual portfolio chosen by well-capitalized thrifts is close to the estimated efficient frontier, while the actual portfolio chosen by insolvent thrifts is located far from the frontier in the high-risk end of investment space. These findings, coupled with the high proportion of nontraditional assets in the actual portfolio chosen by insolvent thrifts, support the hypothesis that moral hazard induced thrifts to take on investments that were excessively risky from the deposit insurer's point of view.     

房产

城市别墅全享价值,五期临河珍藏火热公开 距离徐家汇仅约20分钟车程的银都名墅,以近7成的土地面积建造江南园林景观。是一座城市中的森林公园。银都名墅专门挑选30年以上的成年桦树.种植在中国居住文化里象徵阖家兴旺的竹林。     

Gains From Diversifying Into Real Estate: Three Decades of Portfolio Returns Based on the Dynamic Investment Model

This paper compares the investment policies and returns for portfolios of stocks and bonds with and without up to three categories of real estate. Both domestic and global settings are examined, with and without the possibility of leverage. The portfolios were generated via the dynamic investment model based on the empirical probability assessment approach applied to past (joint) realizations of returns, both with and without correction for "smoothing" in the real estate data series. Our principal findings are: (1) the gains from adding real estate, on a semi-passive (equal-weighted) basis, to portfolios of either U.S. or global financial assets were relatively modest; in contrast, (2) the gains from adding real estate to the universe of U.S. financial assets under an active strategy were rather large (in some cases highly statistically significant), especially for the very risk-averse strategies; (3) the gains from adding U.S. real estate to a universe of global financial assets under an active strategy were mixed, although generally favorable for the highly risk-averse strategies; (4) correcting for second-moment smoothing in the real estate returns series had a relatively small impact for the more risk-tolerant strategies; and (5) there was some evidence that desmoothing resulted in improved probability estimates.     

The Fractal Structure of Real Estate Investment Trust Returns: The Search for Evidence of Market Segmentation and Nonlinear Dependency

This article presents a further test for market segmentation between the real estate market and the capital markets. We use rescaled range analysis developed in the fractal geometry literature to test for nonlinear trends in the returns series for different asset classes. We make three major conclusions: (1) the stock market displays tendencies consistent with a random walk, (2) portfolios of mortgage and equity REIT returns display tendencies consistent with a random walk and, (3) conditional upon the methods used, segmentation does not exist between different real estate markets and between the real estate and stock markets.     

The Real Estate Pricing Puzzle

The state-of-the-art with respect to pricing real estate is similar to that with respect to pricing securities just prior to the development of the CAPM. Reading the entrails of real estate markets, however, has proven a formidable task, and the problem is not limited to inadequate data. Perhaps the most important lesson to date is that available pricing models are not up to the task.     

Currency Swaps and International Real Estate Investment

This paper examines the efficacy of currency swaps as a hedging mechanism for the exchange rate risk associated with foreign investment in real estate. Earlier studies have concentrated on short-term hedging instruments such as options and forward contracts. Currency swaps are better suited for use on investments with long-term holding periods such as real estate. The findings indicate that, although hedging United States real estate investments with currency swaps suppresses most of the risk induced by currency instability, the improvements are insufficient to produce diversification gains for foreign investors in the context of mean-variance portfolio performance.     

Bank Regulatory Agreements and Real Estate Lending

Recent studies have found that banks with low capital ratios have significantly decreased their lending to the real estate sector. This correlation between real estate lending and bank capital could be the result of voluntary decisions by banks to recapitalize, or it could be the result of direct actions taken by bank regulators. We find that banks with low capital ratios reduce their real estate lending substantially more after formal regulatory actions have been initiated by regulators. Furthermore, this reduction in lending is particularly large for the categories of real estate borrowers most likely to be bank dependent.     

The Housing Market and Real Estate Brokers

The major development in this paper concerns the failure, in earlier studies, to consider interaction between alternative methods of arranging sales in the housing market. A seller may market a house by direct negotiations with buyers, without the intermediation of real estate brokers, or by listing the house with a broker. A rational seller would choose the option which offers the higher expected return on the house. In a sequence of models we argue that the seller's option of a method of sale induces competitive pressure in the choice of the commission rate by the broker. We also consider the split rate in a multiple listing system, ease of entry of brokers and the cartel hypothesis as applied to brokers. We conclude that the competitive pressure of direct negotiations between sellers and buyers, relative free entry of brokers and the inappropri-ateness of the cartel hypothesis cast serious doubt about a general consensus of opinion that the brokerage system is characterized by price fixing, excessive commissions and excessive marketing costs.