Asymmetric Risk Measures and Real Estate Returns

Rational investors distinguish between extremely high and extremely low returns. The measures of investment risk should reflect such asymmetric risk perception. This study presents six asymmetric risk metrics and empirically tests their abilities in explaining the cross-sectional variations of real estate returns. It finds strong evidence that systematic downside risk is associated with a risk premium, and skewness provides significant explanatory power to the variation of cross-sectional property returns. On the other hand, co-skewness does not explain real estate returns well and is not a good systematic risk measure.     

Dynamics of Private and Public Real Estate Markets

Using five assets (T-bills, bonds, stocks, and both public and private real estate), this study investigates how cointegration of capital markets affects the dynamics of public and private real estate markets. The results show that the price indices of the five assets are nonstationary and cointegrated. Some implications for the long-term equilibrium relationship for portfolio diversification, price discovery and prediction are discussed. In a Granger causality framework, error-correction augmented VAR models (VECM) and unrestricted VAR models are compared with respect to the conclusion regarding the interaction between public and private real estate returns. VECM is also shown to improve the prediction of private real estate returns relative to an unrestricted VAR model. These results raise questions about previous research studies regarding the dynamics between public and private real estate returns. It is shown that the long-term equilibrium relationship establishes a feedback between the two real estate markets, but the private market seems to informationally lead the public one. Possible explanations are also explored.     

房产税税率、房产税收入与房地产税制度设计

基于房产税税率对房产税收入影响理论,运用数理模型,依据沪渝两市自然数据,考量房产税税率变化对房产税收入的影响.结果显示:房产税税率对房产税收入具有重要影响.若提高上海市房产税税率,房产税增收效果更明显;若下调重庆市房产税税率,房产税增收效应更显著.鉴于此,未来房地产税立法改革思路:一是坚持房地产税税负不增加;二是平衡好房地产税立法与其他收费制度的关系;三是统筹税制改革的协同推进;四是兼顾房地产税的地方财政属性;五是谨慎推进.同时,应遵循税收法定原则、地方财政原则、公平原则、确实原则、渐进原则和结构性调整原则.此外,在制度设计方面,纳税人的设计要体现财产税性质,征税范围要涵盖农村,课税对象要包括存量住房,税率要体现差异性,计税依据要由市场价格评估值确定,税收优惠要兼顾免税面积和特殊人群.     

Book Assets,Real Estate,and Returns on Common Stock

Since real estate is common to most firms, this study examines whether there is a real estate factor in common stock returns that is not completely captured by existing asset pricing models. The three-factor model of Fama and French (1993), hereafter FF, is extended to incorporate a unique real estate factor. Using his extended-FF model, we examine the returns on 53 industry portfolios of common stocks over the 1972 through 1995 time period. The results indicate that a significant 19 percent of the industries are systematically related to the real estate factor. Most interestingly, we show that the loading of the real estate factor in common stock return is related to the loading of the book-to-market equity factor in these returns. We also construct decile portfolios of common stocks based on historical sensitivities of common stock returns to the real estate factor. The coefficients on the real estate factor vary systematically across the decile portfolios. The results of our analysis suggest that portfolio managers should manage their exposure to real estate.     

How Does Appraisal Smoothing Bias Real Estate Returns Measurement?

This paper examines and clarifies several related issues about real estate return indexes. Specifically, even if real estate valuation smoothing exists at the individual property level, such errors may offset in the aggregate. Using data from commercial property appraisals and corresponding transactions, appraisal smoothing errors engender an underestimation of both the first and second moments for real estate returns. After correcting for these “underestimations,” real estate mean returns and the variance appear to be quite similar to those of stocks.     

房地产贷款中的信息不充分及其风险

房地产市场价格波动之所以能够引起银行房地产信贷损失,甚至导致金融市场和宏观经济不稳定的后果,原因是由于房地产抵押贷款中存在的测不准风险或不确定性。本文从信息不充分的视角,提出了房地产抵押贷款中的测不准风险的定义,并分析了测不准风险的特性、形成原因和特殊后果。本文认为,减少或消除不必要的不可预见和不可描述的不确定性可能是管理房地产抵押贷款违约风险,提高贷款配置效率的最好途径,这对于分析房地产市场价格波动与金融市场、宏观经济的互动关系,防止房地产价格波动对金融业和宏观经济的冲击至关重要。     

Valuation in US Commercial Real Estate

We consider a log‐linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REIT returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due to the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices are better modelled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level.     

Economic Risk Factors and Commercial Real Estate Returns

A great deal of research has focused on the links between stock and bond market returns and macroeconomic events such as fluctuations in interest rates, inflation rates, and industrial production. Although the comovements of real estate and other asset prices suggests that these same systematic risk factors are likely to be priced in real estate markets, no study has formally addressed this issue. This study identifies the growth rate in real per capita consumption, the real T-bill rate, the term structure of interest rates, and unexpected inflation as fundamental drivers or state variables that systematically affect real estate returns. The finding of a consistently significant risk premium on consumption has important ramifications for the vast literature that has examined the (risk-adjusted) performance of real estate, for it suggests that prior findings of significant abnormal returns (either positive or negative) that have ignored consumption are potentially biased by an omitted variables problem. The results also have important implications for dynamic asset allocation strategies that involve the predictability of real estate returns using economic data.     

开征物业税对我国房地产市场的影响分析

开征物业税有利于转变政府职能,使政府的税源更依赖于环境的建设,而不是过多地依赖于土地出让;有利于减轻开发商在房地产开发初期的资金压力,降低其经营风险,吸引更多的开发商进入,促进房地产业的竞争,增进消费者福利;有利于鼓励和实现房地产的自住性需求;有利于抑制房地产市场的投资和投机行为。但由于开征物业税会导致房地产开发成本和进入壁垒降低,也可能造成房地产开发过度,产生房地产泡沫。     

The Predictability of Short-HorizonStock Returns

This examines the predictability of short-horizonstock returns in the UK. We show that the subsequentreturn reversal of previous extreme performers isunlikely to be caused by either lead-lag effects orinventory imbalances, the most likely explanationbeing market overreaction. A market or trading basedexplanation is reinforced by the finding that thesereturn reversals are asymmetric, being lesssignificant after bad news. Further, we find that thelower transacting stocks exhibit the stronger returnreversals, in direct contrast to both the existing USevidence and the implication that liquidity effectscan explain the return reversals.     

物业税开征对房地产市场的影响效应分析

由物业税的税负归宿理论剖析入手,通过建立相关模型,可对目前市场上两种描述物业税开征以后开发成本或房价下降的前景有代表性的方案加以实证测算,并按照物业税等价替代成本下降部分的原则,在采用辅助变量法的基础上,建立一个自回归分布滞后模型,从而进一步了解物业税税率的改变对商业物业租金价值变化带来的影响.     

Commercial Real Estate Return Performance: A Cross-Country Analysis

This paper investigates the return performance of publicly traded real estate companies. The analysis spans the 1984–1999 time period and includes return data on over 600 companies in 28 countries. The return data reveal a substantial amount of variation in mean real estate returns and standard deviations across countries. Moreover, standard Treynor ratios, which scale country excess returns by the estimated beta on the world wealth portfolio, also reveal substantial variation across countries in excess real estate returns per unit of systematic risk. However, when we estimate Jensens alphas using both single and multifactor specifications, we detect little evidence of abnormal, risk-adjusted returns at the country level. We do, however, find evidence of a strong world-wide factor in international real estate returns. Furthermore, even after controlling for the effects of world-wide systematic risk, an orthogonalized country-specific factor is highly significant. This suggests that real estate securities may provide international diversification opportunities.     

A Real Estate Price Index for Thin Markets

This article examines a time-series-based method for estimating real estate price indexes for markets that have few transactions. The proposed method is more parsimonious than the conventional repeat sale or hedonic methods. Also, it is potentially more accurate and less prone to outliers. It achieves this by linking current transactions to preceding transactions, thereby increasing the set of comparable transactions on which to base the index. My experiments confirm that the time-series price index fares much better in thin markets than a benchmark hedonic index. It remains close to the true index when there are few transactions and it does not have the volatility of the benchmark index. While the time-series-based index developed in this article does better than the benchmark hedonic index, one surprise result is that the hedonic index is itself quite robust in small samples.     

The Relative Importance of Stock, Bond and Real Estate Factors in Explaining REIT Returns

This paper examines the link between REIT, financial asset and real estate returns, and tests whether it changed subsequent to the “REIT boom” of the early 1990s. The main focus is on answering the question do REIT returns now better reflect the performance of underlying direct (unsecuritized) real estate? We develop and implement a variance decomposition for REIT returns that separates REIT return variability into components directly related to major stock, bond, and real estate-related return indices, as well as idiosyncratic or sector-specific effects. This is applied to aggregate REIT sector (NAREIT) returns as well as returns to size and property-type based REIT portfolios. Our results show that the REIT market went from being driven largely by the same economic factors that drive large cap stocks through the 1970s and 1980s to being more strongly related to both small cap stock and real estate-related factors in the 1990s. There is also a steady increase over time in the proportion of volatility not accounted for by stock, bond or real estate related factors. We also find that small cap REITs are “more like real estate” compared to larger cap REITs, at least over the 1993–1998 period. We argue that this could be a result of the institutionalization of the ownership of larger cap REITs that took place in the 1990s.     

Assessing the Real Estate Pricing Puzzle: A Diagnostic Application of the Stochastic Discounting Factor to the Distribution of REIT Returns

This article applies a general asset-pricing framework and the volatility bounds methodology of Hansen and Jagannathan (1991) to REIT returns. The state of real estate asset pricing remains somewhat of a puzzle relative to the identification of state variables and the structural form of models. This article offers a framework whereby real estate asset-pricing models and data can be diagnosed to answer questions about the shortcomings. In addition, several nominated discount processes are investigated for success in pricing real estate securities. Although the nominated specifications demonstrate some success in satisfying the restrictions on the first and second moments of the real estate returns distribution, they do not successfully price the securities under a no-arbitrage condition. This result calls into question previous real estate performance studies that employ these risk-adjustment processes.     

The Variation of Economic Risk Premiums in Real Estate Returns

We examine the predictable components of returns on stocks, bonds, and real estate investment trusts (REITs). We employ a multiple-beta asset pricing model and find that there are varying degrees of predictability among stocks, bonds, and REITs. Furthermore, we find that most of the predictability of returns is associated with the economic variables employed in the asset pricing model. The stock market risk premium is highly important in capturing the predictable variation in stock portfolios, and the bond market risk premiums (term and risk structure of interest rates) are important in capturing the predictable variation in bond portfolios. For REITs, however, both the stock and bond market risk premiums capture the predictable variation in returns. REITs have comparable return predictability to stock portfolios. We conclude that there is an important economic risk premium for REITs that are not captured by traditional multiple-beta asset pricing models.     

The Predictability of Short-Horizon Stock Returns

This examines the predictability of short-horizon stock returnsin the UK. We show that the subsequent return reversal of previousextreme performers is unlikely to be caused by either lead-lageffects or inventory imbalances, the most likely explanationbeing market overreaction. A market or trading based explanationis reinforced by the finding that these return reversals areasymmetric, being less significant after bad news. Further,we find that the lower transacting stocks exhibit the strongerreturn reversals, in direct contrast to both the existing USevidence and the implication that liquidity effects can explainthe return reversals. JEL Classification: G10, G11, G12     

房地产信贷、价格及市场供求关系研究

本文通过对2000年以来上海房地产信贷与房地产市场关系的实证分析,发现房地产信贷对房地产市场的影响主要表现在需求方而不是供应方,房地产信贷增长对房地产价格和房地产销售量增长有明显的促进作用,但对房地产开发投资没有明显的影响。房地产信贷增长主要由银行流动性状况决定,而不取决于房地产市场状况,但房地产市场供需状况会影响到房地产信贷结构变化,在价格上升时个人购房贷款增长明显,在价格下降时开发贷款增长明显。在短期内,银行信贷可作为平稳房地产市场波动的手段之一,但对于长期而言,只有构建完善的住房供应体系才能保持房地产市场的长期稳定。     

国外房地产业发展现状和政策调控

房地产业的发展由于其投入的资金巨大，对相关产业的带动性强和关系到全国人民的生活环境和生活质量，所以世界各国政府对其都相当重视。国际经济在进入二十一世纪后稳步发展，促进了世界各国的房地产发展。本文通过对日本、美国、俄罗斯和新加坡等国的房地产发展和政府对房价上涨采取的相关调控政策的分析，作为我国房地产健康和持续发展的参考和借签。     

我国房地产业蕴含的金融风险及相关政策调整

本文对当前我国房地产业发展的总体情况和存在的突出矛盾进行了考察,并在此基础上,总结了上个世纪80年代以来发生的典型房地产泡沫危机,分析了房地产泡沫危机和金融危机的关系,以及目前我国房地产业潜在的风险．提出了促进我国房地产业健康发展的政策建议．自去年开始,我国政府针对房地产市场过热的问题实行了从紧的宏观调控措施．这次宏观调控的效果显现时间与美国由次贷问题引发的金融危机相重合。在国内经济政策调整和国际经济环境恶化这样一个大背景下．正确判断我国房地产市场发展情况,分析房地产市场与金融运行之间的相互影响,对于稳步实施房地产业政策调整。防范房地产泡沫与金融风险,促进房地产业、金融和经济的健康发展具有重要意义。