Real Estate Investment Funds: Performance and Portfolio Considerations

This paper presents the results of a study dealing with a number of issues regarding real estate investment. Utilizing a data set consisting of returns from two of the oldest, continuously operating commingled real estate funds (CREFs), questions relative to investment performance, inflation hedging attributes and diversification benefits are addressed. The methodology used in exploring these issues are variants of the traditional capital asset pricing model (CAPM), extended to consider uncertain inflation (CAPMUI) and an arbitrage pricing model in which real estate performance is judged relative to a more inclusive market index representing larger numbers of substitute investments. Finally, issues relative to portfolio performance are considered by constructing portfolios containing all possible combinations of real estate, stocks and bonds to assess the potential for diversification benefits and portfolio performance.     

The Composition of the Market Portfolio and Real Estate Investment Performance

This study investigates whether the composition of the market portfolio leads to different inferences on real estate performance. As a point of departure, this paper first explores whether the omission of assets in a market proxy leads to a biased measurement of investment performance. The study finds that ranking investment performance is not meaningless even though investment performance is inaccurately measured. Furthermore, the composition of the market proxy does not necessarily lead to different inferences on real estate investment performance although superior real estate investment performance arises from the omitted asset phenomenon and also from smoothing bias in general.     

Real Estate in a Mixed‐Asset Portfolio: The Role of the Investment Horizon

In this article, three oft‐mentioned special characteristics of the real estate asset market—high transaction costs, marketing period risk and return predictability—are addressed in analyzing the role of U.K. commercial real estate investments in a mixed‐asset portfolio. Due to favorable horizon effects in risk and return, the allocation to real estate in a portfolio with stocks, bonds and cash increases strongly with the investment horizon. Examining the relative importance of return predictability, transaction costs and marketing period risk for the optimal allocation to real estate, the article finds that the consideration of return predictability is very important, except for short‐term horizons. Accounting for transaction costs is crucial for short‐ and medium‐term investors. Marketing period risk appears to be negligible. Traditional mean‐variance analysis—that is, ignoring return predictability, transaction costs and marketing period risk—can be very misleading.     

Portfolio Considerations in the Valuation of Real Estate

When a real asset rises in price faster than inflation (as real estate did in the late 1970s) and rises significantly in price over an extended period (as real estate has done for the last decade and one-half), it concerns valuation and investment professionals who fear about it being over-valued. One of the reasons for such price performance may be an increase in demand due to the portfolio characteristics of the asset during the period of time in question. For real estate this means the proportion included in optimal portfolios should be significant and increasing as individual tax rates increase in an environment of increasing average tax rates.
This study uses six tax brackets (0%, 10%, 20%, 30%, 40%, 50%) and portfolios consisting of three traditional assets (NYSE common stocks, corporate bonds and small stocks) plus three types of real estate (residential, business and farmland) to demonstrate that this is what has transpired in the real estate markets. Optimal portfolio weights are derived for each asset for after-tax portfolios. Real estate in general and residential real estate especially increased as a proportion of the optimal after-tax portfolio as individual tax rates increased. Other studies are used to demonstrate an environment of increasing average tax rates.     

Commercial Real Estate Returns: An Anatomy of Smoothing in Asset and Index Returns

In this article, we investigate the commonly used autoregressive filter method of adjusting appraisal‐based real estate returns to correct for the perceived biases induced in the appraisal process. Many articles have been written on appraisal smoothing but remarkably few have considered the relationship between smoothing at the individual property level and the amount of persistence in the aggregate appraisal‐based index. To investigate this issue we analyze a large sample of appraisal data at the individual property level from the Investment Property Databank. We find that commonly used unsmoothing estimates at the index level overstate the extent of smoothing that takes place at the individual property level. There is also strong support for an ARFIMA representation of appraisal returns at the index level and an ARMA model at the individual property level.     

An Investment Model of the Demand and Supply For Industrial Real Estate

A recent inventory of industrial building in fifty-two major metropolitan areas of the country indicates that most such space is either owner occupied or single tenant. This suggests that the production of industrial space may be modeled as a firm "investment" decision. Using the completion date of each inventoried building, we construct a time series of plant completions that moves similarly to some other national investment data. We are able to successfully estimate an "accelerator" type model of plant deliveries, driven by movements in employment and the after-tax cost of corporate capital. Our model can be used to estimate a measure of excess plant capacity in the market, and historic values of this measure do move parallel to some recent industrial vacancy data.     

实物期权在房地产投资决策中应用研究

房地产项目投资具有不可逆性、高度不确定性和管理的灵活性,运用传统的净现值法不能挖掘出项目投资的这些性质所带来的价值,而应用实物期权方法进行房地产投资决策研究,不仅考虑到了房地产投资的不确定性,还体现了投资决策者的柔性管理和战略投资的价值.文章分析了传统净现值法的一些不足,介绍了实物期权的基本理论,并采用了B-S期权定价模型对房地产投资决策过程中蕴含的增长期权进行了案例分析,使得房地产投资决策更加科学合理.     

基于PP-RAGA的工业地产投资环境评价的实证研究

以辽宁省14个地级市为研究对象,在构建工业地产投资环境评价指标体系的基础上,应用基于实数编码的加速遗传算法(RAGA)的投影寻踪(PP)方法对各市的投资环境进行定量分析.在此基础上对14个地级市的工业地产投资环境进行排序与分类,将评价结果与相关研究成果进行比较,验证了评价的有效性.针对改善工业地产投资环境提出了完善的对策与建议.     

The Gains from Corporate Selloffs: The Case of Real Estate Assets

Recent financial economics literature has hypothesized that variations in market structure influence the distribution of gains from corporate restructuring between buyers and sellers. We test this hypothesis using data on restructuring involving real estate assets by isolating the effects depending on multiple versus single bidders, acquisition frequency and transaction type. While we find gains for both buyers and sellers, the buyers gain only when they make few purchases. Those firms pursuing an acquisition strategy show no gains around the specific acquisition announcements. Additionally, both buyers and sellers are more likely to have a positive reaction to the announcement when the transaction is property rather than a division or subsidiary.     

The Role of Real Estate in the Portfolio Allocation Process

This study explores the role of direct real estate investment in a portfolio context incorporating the real estate imperfections of indivisible assets and no short sales. Mean-variance efficient portfolios are calculated using Treasury-bills, bond and equity indices together with cash flows and appraised values from a set of twenty-two properties having an aggregate appraised value of $336 million. Real estate diversification benefits are shown to be the greatest with smaller properties and are most advantageous at higher target levels of return. The study suggests that a 9% allocation to real estate is optimal, rather than the 20% figure suggested in other studies.     

Commercial Real Estate Rental Index: A Dynamic Panel Data Model Estimation

Using the actual quarterly rental income generated in the years between 2001 and 2010 by over 9,000 NCREIF commercial properties, we construct a commercial real estate rental index and estimate the time series properties (e.g., mean‐reversion speed and volatility) of market‐wide rental growth using a dynamic panel data model. The dynamic panel data model has several advantages over a standard hedonic regression. In addition, we incorporate age effects into our panel data model, and by doing so we correct the age bias in the repeated sales method and in the simple average method. Our estimates show that rental growth is cyclical but it generally lags behind broader economic growth. Surprisingly, the long‐term average rental growth is significantly lower than what is usually perceived, and the volatility of rental growth can be significantly under estimated when the conventional methods are adopted. We also find significant cross‐property type and cross‐region variations in the rental adjustment process. In contrast to the existing literature, we find a strong negative relation between rental growth and cap rate, and that this relation is significantly stronger than that between NOI growth and cap rate. Finally, we establish an empirical relation between price return and rental growth in the commercial real estate market.     

实物期权理论在房地产投资决策中应用

房地产业是我国经济增长的引擎和支柱产业,又是一个涉及到各行各业的产业,其受国家政策、环境变化、地区经济和文化影响大,存在很大的不确定性。针对这种不确定性,引入实物期权理论研究了房地产投资决策架构和投资分析方法。     

房地产投资分析浅析

房地产投资分析是房地产投资决策的基础，所涉及的内容较多。章通过对消费、投资地域、资金筹集和投资项目4个方面分析，详细地阐述了影响房地产投资决策的各种主要因素，提出将房地产投资风险降至最低的建议。     

商业地产投资的实物期权特性及应用框架研究

商业地产开发投资中存在投资的不可逆性、外部环境的不确定性和决策的灵活性,因而具有实物期权特性。从确定要解决的问题、分析不确定性的来源、鉴别关键的不确定性因素、识别实物期权类型、构建期权定价模型、计算项目价值、检查计算结果和重新设计8个方面,构建了商业地产投资决策的实物期权分析框架。     

基于IFAHP的房地产企业投资风险评价

房地产企业投资是一个高风险行业,为避免投资失误,提高决策水平,进行房地产企业投资风险评价具有一定的理论和实践意义。针对房地产企业投资风险的复杂性和不确定性,在借鉴近期国内有关房地产企业投资风险相关研究和分析基础上,利用问卷调查法对投资风险因素进行了识别,构建了风险评价指标体系,并采用改进模糊层次分析法对风险指标体系进行了评价分析,从理论上找出影响房地产企业投资的关键风险因素,为房地产企业投资风险评价提供了较为合理的参考依据,使投资决策更为科学。     

REIT and Commercial Real Estate Returns: A Postmortem of the Financial Crisis

In the years surrounding the financial crisis, the share prices of equity Real Estate Investment Trusts (REITs) were much more volatile than the underlying commercial real estate prices. To better understand this phenomenon we examine the cross‐sectional dispersion of REIT returns during this time period with a particular focus on the influence of their capital structures. By looking at both the debt ratio and the maturity structure of the debt, we separate the pure leverage effect from the effect of financial distress. Consistent with leverage and financial distress costs amplifying the price decline, we find that the share prices of REITs with higher debt‐to‐asset ratios and shorter maturity debt fell more during the 2007 to early‐2009 crisis period. Although REIT prices rebounded with the bounce back in commercial real estate prices, financial distress costs had a permanent effect on REIT values. In particular, we find that REITs with more debt due during the crisis period tended to sell more property and issue more equity in 2009, when prices were depressed.     

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.     

我国房地产业投资绩效分析

自实行住房分配货币化以来,中国的房地产业进入了快速发展时期。当前,以房价为核心的舆论和调控备受关注。通过运用数据包络分析（DEA）法,评价了自1998年以来中国房地产业的投资绩效问题。深入分析房价不断高涨而调控措施不力的原因,以期寻求更加全面科学的调控途径和办法,从而促进房地产业健康持续发展。