Smoothing, Nonsynchronous Appraisal and Cross-Sectional Aggregation in Real Estate Price Indices

In this article three econometric issues related to private-equity return indices, such as real estate indices, are explored (smoothing, nonsynchronous appraisal and cross-sectional aggregation). Under certain assumptions, it is found that index returns based on appraisals follow an ARFIMA(1, d , 1) (autoregressive fractionally integrated moving average) process, where the long memory parameter ( d ) explains the level of smoothing and the AR and MA parameters represent the level of persistence in marketwide fundamentals and the nonsynchronous appraisal, respectively. The empirical results show that: (1) the level of smoothing in appraisal-based real estate indices is far less than assumed in many academic studies (2) there is weak evidence of nonsynchronous appraisal in the UK, IPD (Investment Property Databank) index and (3) marketwide fundamentals are highly persistent for the IPD index returns. On the other hand, there is no evidence of nonsynchronous appraisal or a persistent common factor in the U.S. NCREIF (National Council of Real Estate Investment Fiduciaries) index.     

Estimating the Lagging Error in Real Estate Price Indices

Real estate indices based on appraisals or sale prices of properties are known for their slow response to market news. These indices can therefore be represented (in logarithm) as the sum of a latent "true" price index and a lagging error. We show that the latent appreciation return and the lagging error can be jointly estimated in a state–space model, which has two key features. First, it employs exogenous variables known to predict asset returns to predict the latent appreciation return. Second, it incorporates known sources of the lagging error, such as the partial adjustment in observed index to the latent appreciation return and the seasonality in reappraisal quality. We find that, after the estimated lagging errors are removed, the appraisal–based National Council of Real Estate Investment Fiduciaries returns become more informative and hence exhibit (i) greater variance, (ii) weaker auto correlation, (iii) higher correlation with the returns of the securitized real estate and (iv) more timely response to market news.     

Institutional Capital Flows and Return Dynamics in Private Commercial Real Estate Markets

This article examines the short- and long-run dynamics among institutional capital flows and returns in private real estate markets. At the aggregate U.S. level, we find evidence that lagged institutional flows significantly influence subsequent returns. When disaggregating by property type at the national level, we find that capital flows predict subsequent returns in the apartment and office sectors, but not in the retail and industrial markets. At the metropolitan level, we find that the flows help explain subsequent returns in a limited number of core business statistical areas (CBSAs), although these CBSAs collectively represent about 30% of institutional capital. We find no evidence that institutional returns are predictive of future capital flows at the national or CBSA level, suggesting that institutional investors are not chasing returns.     

Risk and Return on Real Estate: Evidence from Equity REITs

We analyze monthly returns on an equally weighted index of eighteen to twenty-three equity (real property) real estate investment trusts (REITs) that were traded on major stock exchanges over the 1973–87 period. We employ a multifactor Arbitrage Pricing Model using prespecified macroeconomic factors. We also test whether equity REIT returns are related to changes in the discount on closed-end stock funds, which seems plausible given the closed-end nature of REITs.
Three factors, and the percentage change in the discount on closed-end stock funds, consistently drive equity REIT returns: unexpected inflation and changes in the risk and term structures of interest rates. The impacts of these variables on equity REIT returns is around 60% of the impacts on corporate stock returns generally. As expected, the impacts are greater for more heavily levered REITs than for less levered REITs. Real estate, at least as measured by the return performance of equity REITs, is less risky than stocks generally, but does not offer a superior risk-adjusted return and is not a hedge against unexpected inflation.     

Controlling for the Impact of Variable Liquidity in Commercial Real Estate Price Indices

Liquidity in private asset markets is notoriously variable over time. Therefore, indices of changes in market value that are based on asset transaction prices will systematically reflect intertemporal differences in the ease of selling a property. We define and develop a concept of "constant-liquidity value" in the context of a model that is characterized by pro-cyclical volume of trading. We then present an econometric model that allows for estimation of both a standard transaction-based price index and a constant-liquidity index. Our application to the NCREIF database reveals that, in the case of institutional commercial real estate investment, constant-liquidity values tend to lead transaction-based and appraisal-based indices in time, and also to display greater volatility and cycle amplitude. The differences can be significant for strategic investment policy viewed from a mean-variance portfolio optimization perspective.     

Inferring an Investment Return Series for Real Estate from Observations on Sales

Accurate measurement of the returns to real estate investment are essential to sound analysis. This paper improves upon the traditionally employed method—collecting comparable sales data. A dynamic model of real estate appraisal is developed in which agents have incomplete information, heterogeneous search costs, and varying expectations. Various types of simulation analysis of the model indicate it performs best in the sense that the return estimate converges to the true value faster than other simpler rules.     

Temporal and Spatial Information Diffusion in Real Estate Price Changes and Variances

This article examines patterns of temporal and spatial diffusion of real estate price changes. In addition to means, changes in volatility are tracked in reaction to substantial new information, estimated with GARCH-M methods. The data covers towns in Connecticut and near San Francisco. There is evidence of negative feedback at short lags, contrary to previous research on housing and other assets. There is also evidence of a moving average error process which tends to reverse recent shocks. Significantly positive spatial information diffusion is found from neighboring towns in Connecticut but none in control tests on nonneighboring towns. The results also include evidence of a risk-reward tradeoff in housing price changes in the San Francisco area.     

Return Risk and Cash Flow Risk with Long-term Riskless Leases in Commercial Real Estate

This paper presents a conceptual analysis of some of the key fundamentals that underlie the risk characteristics of commercial real estate returns. In particular, the relationship between the property's return risk and its cash flow risk is explored. This relationship is important because it is the return risk that should matter most to investors, yet it is the cash flow risk or market risk about which we may have the most objective information and the most intuition. This is because real estate assets are generally unsecuritized and trade too infrequently to observe time series of returns (including appreciation) that could be used to directly study the risk characteristics of the returns. By explicitly incorporating the possibility of cash flows governed by riskless long-term leases, this paper also explores the relationship between lease term and both cash flow risk and return risk.     

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。     

The Risk and Return of Commercial Real Estate: A Property Level Analysis

I compare the performance of the index‐based time series approach and the cross‐sectional approach in estimating factor loadings of nontraded assets, and show that the latter likely provides less biased and more efficient estimates. I then use the cross‐sectional approach to estimate the loadings of privately owned commercial real estate on the Fama and French (1993) factors, the Pastor and Stambaugh (2003) liquidity factor, and two bond market factors, using a sample of 14,115 properties in the 1977–2012 period. I find statistically significant loadings, of which the signs seem consistent across property types, but the magnitude varies. Using the time series approach on the same data, I find insignificant loadings on virtually all factors. To investigate the sources of the weak results from the time series approach, I conduct a Monte Carlo simulation in which both approaches are correctly specified and indices can be estimated perfectly. Simulation results suggest that the cross‐sectional approach provides more accurate estimates under reasonable market conditions.     

A Further Examination of Appraisal Data and the Potential Bias in Real Estate Return Indexes

Recent articles by Giliberto [2] and Geltner [1] examine the biases inherent in the use of appraisal data in real estate performance measurement. This note takes another look at the direction and magnitude of any bias in holding period returns. Using appraisal data from a commingled real estate fund, we show that in actual application the size of the holding period return bias can be quite small and this bias may have no appreciable effect on real estate return indexes.     

房地产行业信用满意度相关因素灰色关联性分析

当前房地产企业信用缺失现象严重,这对房地产市场的健康发展产生很大的负面影响.文章引入灰色关联分析模型并运用灰色相关分析的原理,借助DPS软件,通过对中国12个典型城市的房地产行业信用满意度与相关因素进行关联实证分析,并按相关程度排列出次序.经过分析研究得出以下结论:良好的房地产行业信用满意度与房地产投资及房价增长呈正相关关系,但是房地产行业利润多少与房地产信用满意程度关系不大.如果房地产诚信缺失,企业不会因为诚信缺失而遭致惩罚,失信成本过低,这也是部分房地产企业漠视企业诚信的原因.     

Real Estate for the Long Term: The Effect of Return Predictability on Long-Horizon Allocations

We examine how the predictability of real estate returns affects the risk of, and optimal allocations to, real estate for investors of differing investment horizons. Returns to direct real estate are mean reverting, and risk decreases with horizon. This is driven by a tendency for property transaction prices to overshoot inflation. Mean reversion in real estate returns is weaker than that of equities, resulting in real estate having similar risk to equities for long-term investors. However, optimal portfolios have large allocations to direct real estate at all horizons, and the allocation increases with horizon. Finally, we find that real estate investment trusts are a redundant asset class for investors with access to direct real estate as an asset class, but they do have a role in optimal allocations when direct property investment is not feasible.     

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.     

Errors in Variables, Links between Variables and Recovery of Volatility Information in Appraisal-Based Real Estate Return Indexes

The present article proposes a multivariate approach to unsmoothing appraisal-based real estate return indexes to recover the true market volatility information in real estate returns. It scrutinizes the role played by errors in variables, in conjunction with an analysis of other economic activities relevant to real estate returns, to exploit the functional relationship and the mechanism of interactions between real estate returns and these economic activities. Appraisal smoothing can therefore be detected and corrected properly and efficiently, without presuming a weakly efficient real estate market. The approach is then applied to U.K. real estate indexes as empirical examples. The results suggest a reasonable volatility in U.K. real estate investment that is close to reality. It is found that the volatility of the true market return on real estate is 1.5404–1.9282 times that of the return on the appraisal-based indexes, in contrast to figures of 2.4862–5.8720 produced by the fully unsmoothing procedure.