Local Risk,Local Factors,and Asset Prices

Firm location affects firm risk through local factor prices. We find more procyclical factor prices such as wages and real estate prices in areas with more cyclical economies, namely, high “local beta” areas. While procyclical wages provide a natural hedge against aggregate shocks and reduce firm risk, procyclical prices of real estate, which are part of firm assets, increase firm risk. We confirm that firms located in higher local beta areas have lower industry‐adjusted returns and conditional betas, and show that the effect is stronger among firms with low real estate holdings. A production‐based equilibrium model explains these empirical findings.     

基于房地产市场的我国系统性金融风险测度与预警研究

本文阐释了基于房地产市场的系统性金融风险形成机制,据此建立了分阶段、跨部门的房地产市场的系统性金融风险网络模型,并运用2006-2017年16家上市银行数据,分析和测度了我国房价大幅下跌所引发的系统性金融风险水平和结构,构建了基于房地产市场的系统性金融风险预警指标并进行测算。研究发现:在房价下跌30%的压力情景下,我国金融体系的潜在总损失总体呈级数式上升,年均增长22.70%;基于房地产市场的系统性金融风险值(SR)呈现先上升后波动下降的总体趋势;系统性金融风险(SR)的脆弱性指标(FLI)整体呈现波浪式振荡变化,且与房地产贷款/权益整体呈反向变动,系统性金融风险(SR)的传染性指标(CTI)在2012-2017年呈持续下降趋势,且与金融市场压力指数、金融机构间资产占总资产比重呈现出高度的一致性变化趋势。最后,基于房地产市场的系统性金融风险预警指标(SRWI)值呈收敛式振荡走势,表明基于房地产市场的系统性金融风险总体可控且呈收敛式下降。     

中国房地产企业间系统性风险溢出效应分析——基于尾部风险网络模型

本文以2007—2021年沪深A股上市房企为样本,首先基于SIM单指数分位数回归技术提出测量系统性风险的新指标SIM-CoVaR,并结合前沿的TENET网络模型,构造跨房地产企业风险动态传染的尾部风险网络,然后采用块模型探究房地产市场系统性风险溢出的聚类性、触发机制及传播路径,最后考察网络整体结构和宏观经济变量对房地产市场系统性风险溢出的影响。研究表明:(1)我国房地产企业间存在明显的系统性风险联动性和溢出效应,在市场动荡时期房地产部门是金融风险溢出的放大器;(2)评估系统重要性节点企业时,除考虑企业规模等内部属性,还应考虑房企间关联结构,利用系统性风险指数可有效捕捉网络中系统重要性节点;(3)跨房企的系统性风险溢出具有显著的聚类特征,尾部风险网络可被划分为4个不同的功能模块,各模块的成员及其角色呈现明显的时变特性,监管部门可据此从供给端“因企施策”;(4)网络聚集性、网络效率和网络匹配性的降低能显著降低房地产市场的系统性风险溢出效应。本文从企业微观层面探讨房地产市场风险的形成机制,为促进房地产业健康发展和防范化解宏观层面的系统性金融风险提供参考。     

基于房地产市场的我国系统性金融风险测度与预警研究

本文阐释了基于房地产市场的系统性金融风险形成机制,据此建立了分阶段、跨部门的房地产市场的系统性金融风险网络模型,并运用2006-2017年16家上市银行数据,分析和测度了我国房价大幅下跌所引发的系统性金融风险水平和结构,构建了基于房地产市场的系统性金融风险预警指标并进行测算。研究发现:在房价下跌30%的压力情景下,我国金融体系的潜在总损失总体呈级数式上升,年均增长22.70%;基于房地产市场的系统性金融风险值(SR)呈现先上升后波动下降的总体趋势;系统性金融风险(SR)的脆弱性指标(FLI)整体呈现波浪式振荡变化,且与房地产贷款/权益整体呈反向变动,系统性金融风险(SR)的传染性指标(CTI)在2012-2017年呈持续下降趋势,且与金融市场压力指数、金融机构间资产占总资产比重呈现出高度的一致性变化趋势。最后,基于房地产市场的系统性金融风险预警指标(SRWI)值呈收敛式振荡走势,表明基于房地产市场的系统性金融风险总体可控且呈收敛式下降。     

The effect of TARP on the propagation of real estate shocks: Evidence from geographically diversified banks

This study examines the effect of TARP on the propagation of real estate shocks via geographically diversified banks in the U.S. I find that TARP money provided for banks exposed to distressed areas (i.e., “affected” banks) was positively associated with small business loan originations in “non-distressed” areas (i.e., counties with smaller real estate shocks), mitigating the shock transmission. In addition, the bailout funds facilitated “affected” banks’ faster return to their pre-crisis level of franchise value. Overall, the marginal benefit of TARP funds seems to have been greater for “affected” TARP banks. I conclude that this policy helped “affected” banks cleanse/strengthen their balance sheets and recapitalize, which paved the way for increased lending.     

Diversification Issues in Real Estate Investment

Real estate asset management has been and will continue to be a topic of great interest. Specifically, does real estate warrant inclusion in an efficient portfolio? And if so, how much should be invested in real estate? This article reviews the extant literature in the area of real estate diversification and helps identify the reasons that there exists so much divergence in the answer to the question, “How much in real estate?” Moreover, diversification as it relates to real estate is discussed in reference to both mixed-asset portfolios and for diversification within the real estate asset class. Directions for future research are also discussed.     

System Dynamics Modeling of Chinese Urban Housing Markets for Pedagogical and Policy Analysis Purposes

This paper reports on the current state of a project to develop a system dynamics (SD) model for urban housing markets in China, aimed at facilitating policy analysis and supporting practical educational tools that might reach large numbers of potential entrepreneurs in China. Although numerous academic papers have applied SD models to real estate markets over the past generation, the technique remains relatively unknown and little used both in the academic economics literature and, more to the point, among practitioners and educators in the real estate community. Yet SD has the potential to address key needs among these constituencies, and extend and complement upon traditional economic methods. SD models are focused on modeling market transitions toward long-run equilibria, facilitating the study of the details of causality and the dynamic path of the market and features that are prominent in the history of housing markets in emerging markets. Different from intensive data-driven economic models, SD models are structural-based operational models that can more easily accommodate the actual non-market features and unique institutional components of these emerging real estate markets, where long-range historical data are not readily available. SD can provide intuitive and transparent model structures that should be able to improve pedagogy for educating large numbers of potential real estate entrepreneurs particularly in emerging market countries. For demonstration, in the present paper we choose to focus on the China-specific features of ‘speculative demand’ and ‘land financing scheme’, and use the newly developed SD model to explore the effects of land supply, “command-and-control” versus “market-driven” policies for housing in China. It is important to note, however, that while we chose China for the purposes of our study, the same technique can be applied to any emerging real estate market. Moreover, our research here can be seen as a stepping stone: Before a generalized SD model for emerging markets can be developed, it is both reasonable and appropriate to construct a model that is constrained to a manageable subset of the overall market space.     

The sensitivity of bank stock returns to real estate

According to the Federal Reserve Board, banking firms have recently been shifting significantly larger portions of their loan portfolios into real estate. This increase in real estate lending has caused concern about the continuing economic health of banks on the part of state and federal regulators, since changes in real estate returns, evidenced by changes in property value, can potentially have a significant impact on bank default risk and profit-ability. However, concerned parties do not seem to have explicitly considered the relationship between mortgage default risk and the specific characteristics of real estate investments.This study examines the sensitivities of stock returns for different bank groups, based on the percentage of total loans in real estate and the percentage of loans in five different mortgage categories (construction and development loans, farmland loans, one- to four-family residential loans, multifamily residential loans, and nonresidential and nonfarm loans), to changes in real estate market returns. This is done by developing and using a three-index model.The results of this study indicate that bank stocks, overall, are very sensitive to changes in real estae returns. Banks, with a larger portion of their total loans invested in all types of real estate loans, except farmland loans, are most sensitive to changes in real estate returns.     

用“附加值”加分

不断挖掘“附加值”,不仅可以体现地产PEA9专业性,更能在竞争中为自己加分。随着“大资管时代”的启幕,2014年再去探究开发商基金与非开发商基金孰优孰劣似乎显得过于落伍了。开发商做基金已然成为国内地产基金最主流的模式之一。     

The risk and return of private equity real estate funds

This study employs an asset pricing approach to quantify the exposure of private real estate funds to both private and publicly traded real estate risk factors. The analysis includes the creation of specific performance indices and the use of methods seeking to address some of the inherent issues with private real estate fund data, such as the high degree of serial correlation in observed total returns. The use of the Driessen et al. (2012) estimator leads to markedly higher risk factor coefficient estimates than seen in the prior literature and estimated with time series regression.     

广东省房地产金融风险实证分析

房地产金融风险特指银行等金融机构为房地产业提供资金的筹集、融通、清算等金融服务活动中,由于各种事先无法预料(即不确定)因素的影响,使金融机构的实际收益与预期收益发生背离,从而蒙受经济损失的可能性。本文通过参考现有房地产金融风险分析的主要因素,从金融机构、房地产开发企业及购房者这三个方面对当前房地产市场的风险状况进行分析,并通过定量的方法估算当前广州房地产市场的投机程度,最后提出相应防范房地产金融风险的建议。     

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.     

Performance of Thinly Traded Assets: A Case in Real Estate

Thinly traded private assets do not fit into the traditional finance paradigm of a liquid and well‐functioning market where trading is continuous and instantaneous. Since private assets cannot be bought and sold easily, they bear liquidity risk. Classical finance theories cannot properly gauge the performance of illiquid private assets because they implicitly assume such illiquidity is trivial. This paper proposes an alternative performance metric for the illiquid private asset, which explicitly captures liquidity risk in a formal analysis. Applying the new performance metric, we are able to explain the decades‐old “real estate risk premium puzzle.”     

An analysis of real-estate risk using the present value model

The current study uses a present value model that allows for a time-varying expected discount rate in conjunction with a VAR process to decompose real-estate risk. The study finds that the variance ofunexpected returns accounts for most of the total risk with cash-flow risk accounting for twice as much of the unexplained real-estate risk although discount rate risk is also an important factor. This dominance of cash-flow risk is found to result in a weaker mean reversion process for real estate relative to stocks. Another finding is that real estate investors tend to become apprehensive about the future when news on future cash flow is good, and thus they demand higher expected future returns.     

房产税对宏观经济的影响效应研究

本文扩展Dong et al.(2019)通过企业家对住房地产和实体经济投资进行资产组合决策,把房价、投资、消费和产出等重要经济指标纳入主流新凯恩斯框架,考虑银行能否区分贷款是投入实体经济还是房地产业两种情形,分析了房产税引入住房市场前后对宏观经济的影响效应。研究结果表明:开征房产税对房地产开发投资、房价和新住房生产具有明显的抑制作用,对实体经济投资则具有正挤入效应增加和负抵押效应减少的双重效应。从短期看,当银行无法区分企业贷款是投入实体经济还是房地产业时,因前期的负抵押效应大于正挤入效应,总实物资本减少,产出下降;当可清晰区分二者时,负抵押效应变为小于正挤入效应,总实物资本增加,产出上升。鉴于推出房产税对宏观经济影响较为复杂,应充分权衡利弊,采取必要辅助措施趋利避害。     

Real Estate Ownership, Leasing Intensity, and Value: Do Stock Returns Reflect a Firm’s Real Estate Holdings?

Little is known about the effects of real estate ownership and leasing on the stock return characteristics of public firms. In this study, we first examine the sensitivity of retail firm returns to a real estate factor over the period 1998?C2008. The retail industry is chosen because of the significant use of real estate in a typical retail firm??s production function. Consistent with our expectations, retail stocks exhibit positive real estate risk exposure, even after controlling for sensitivity to general market risk as well as other standard risk factors. The second part of our analysis examines whether the intensity of real estate ownership and the use of off-balance operating leases to finance real property holdings are reflected in the market and real estate betas of retail stocks. We find that greater use of off-balance sheet operating leases is associated with higher market betas. In fact, the use of operating leases appears to have a larger impact on sensitivity to market risk than does the use of on-balance sheet debt. Our findings also confirm our hypothesis that real estate intensive firms display significantly greater exposure to a real estate factor. Moreover, our results strongly suggest that investors are fully aware of the risk associated with off-balance sheet operating leases.     

房产税对宏观经济的影响效应研究

本文扩展Dong et al.(2019)通过企业家对住房地产和实体经济投资进行资产组合决策,把房价、投资、消费和产出等重要经济指标纳入主流新凯恩斯框架,考虑银行能否区分贷款是投入实体经济还是房地产业两种情形,分析了房产税引入住房市场前后对宏观经济的影响效应。研究结果表明:开征房产税对房地产开发投资、房价和新住房生产具有明显的抑制作用,对实体经济投资则具有正挤入效应增加和负抵押效应减少的双重效应。从短期看,当银行无法区分企业贷款是投入实体经济还是房地产业时,因前期的负抵押效应大于正挤入效应,总实物资本减少,产出下降;当可清晰区分二者时,负抵押效应变为小于正挤入效应,总实物资本增加,产出上升。鉴于推出房产税对宏观经济影响较为复杂,应充分权衡利弊,采取必要辅助措施趋利避害。     

Bank risk and real estate: An asset pricing perspective

While a number of papers have investigated the time-series behavior ofex post bank stock returns and real estate returns, no study has comprehensively studied the relationship betweenex ante risk premiums on both assetsand the time-varying nature of such premiums in relationship to economic and real estate market conditions. In this study, we investigate how the changing nature of bank risk taking, especially in the real estate market, has affected theex ante pricing of risk in the market for bank stocks. We find that the time variation in bank risk premiums are partly determined by interest rate and real estate market conditions. We also discover that the real estate factor has been important for banks in the 1980s.     

Risk and return in real estate

Basic information is provided on the returns and risks from 1978 through 1985 for unleveraged equity real estate compared with stocks and bonds. Data sources include the Russell-NCREIF index, the Evaluation Associates index, and the Goldman Sachs equity real estate investment trust index. Findings reveal that the aggregate return for the publicly traded equity real estate investment trust index in nearly twice that of the other real estate series, and more than twice that of the Standard & Poor index. The equity real estate investment trust is far more volatile than the other two real estate series. Neither the Goldman Sachs nor the other two indexes exactly measure the returns or risks on equity real estate. The volatility of the equity real estate investment trust leads it to overstate the risk of this investment category, while the other two indexes are not return indexes. Estimates from this study indicate that real estate risk lies plausibly midway between that of stocks and bonds, in the 9 percent to 13 percent range.