Aggregate insider trading: Contrarian beliefs or superior information?

We decompose realized market returns into expected return, unexpected cash-flow news and unexpected discount rate news to test the relation between aggregate market returns and aggregate insider trading. We find that (1) the predictive ability of aggregate insider trading is much stronger than what was reported in earlier studies, (2) aggregate insider trading is strongly related to unexpected cash-flow news, (3) market expectations do not cause insider trading contrary to what others have documented, and (4) aggregate insider trading in firms with high information uncertainty is more likely to be associated with contrarian investment strategy. These results strongly suggest that the predictive ability of aggregate insider trading is because of insider’s ability to predict future cash-flow news rather than from adopting a contrarian investment strategy. These results hold even after we control for non-informative trades and information uncertainty.     

Explaining Returns with Cash-Flow Proxies

Stock returns are correlated with contemporaneous earnings growth,dividend growth, future real activity, and other cash-flow proxies.The correlation between cash-flow proxies and stock returnsmay arise from association of cash-flow proxies with one-periodexpected returns, cash-flow news, and/or expected-return news.We use Campbell’s (1991) return decomposition to measurethe relative importance of these three effects in regressionsof returns on cash-flow proxies. In some of the popular specifications,variables that are motivated as proxies for cash-flow news alsotrack a nontrivial proportion of one-period expected returnsand expected-return news. As a result, the R² from a regressionof returns on cash-flow proxies may overstate or understatethe importance of cash-flow news as a source of return variance.     

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.     

What Drives Firm‐Level Stock Returns?

I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash-flow expectations (i.e., cash-flow news) and changes in discount rates (i.e., expected-return news). The VAR yields three main results. First, firm-level stock returns are mainly driven by cash-flow news. For a typical stock, the variance of cash-flow news is more than twice that of expected-return news. Second, shocks to expected returns and cash flows are positively correlated for a typical small stock. Third, expected-return-news series are highly correlated across firms, while cash-flow news can largely be diversified away in aggregate portfolios.     

Pension plan solvency and extreme market movements: a regime switching approach

We develop and test a new approach to assess defined benefit (DB) pension plan solvency risk in the presence of extreme market movements. Our method captures both the ‘fat-tailed’ nature of asset returns and their correlation with discount rate changes. We show that the standard assumption of constant discount rates leads to dramatic underestimation of future projections of pension plan solvency risk. Failing to incorporate leptokurtosis into asset returns also leads to downward biased estimates of risk, but this is less pronounced than the time-varying discount rate effect. Further modifying the model to capture the correlation between asset returns and the discount rate provides additional improvements in the projection of future pension plan solvency. This reduces the perceived future risk of underfunding because of the negative correlation between interest rate changes and asset returns. These results have important implications for those with responsibility for balancing risk against expected return when seeking to improve the current poor funding positions of DB pension schemes.     

Risk management of real estate: The case of real estate swaps

Real estate swaps are a recent financial innovation based upon the principle of comparative advantage. A real estate swap is a useful tool for real estate risk management and for participating in real estate investment without the high costs associated with real estate. Potential economic benefits and costs associated with real estate swaps are considered and real estate swaps are compared to alternative tools for real estate risk management. The expected utility and effectiveness of risk management with a swap in a multiperiod framework are analyzed. The analysis finds that the subject property's return and its risk characteristics (as reflected in its correlation with interest rate and property index returns) delimit the risk management potential of a given swap position. Optimal swap positions are shown for various regions and property types based on historical return series, from the period between 1983 and 1992, and the parameters of the dynamic model developed.     

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.     

Return Relationships between Listed Banks and Real Estate Firms: Evidence from Seven Asian Economies

This paper studies the return relationships between listed banks and real estate firms in seven Asian economies before and after the Asian financial crisis. We find that listed banks were exposed to real estate risk both before and after the crisis, but that the exposure increased in the post-crisis period. After the crisis, the hidden risk of real estate collateral in the bank lending process was explicit, as was evidenced by the increased sensitivity and the structure break. In terms of causality, the returns of listed real estate firms are found to Granger-cause the returns of listed banks. However, there is mixed evidence as to whether listed bank returns Granger-cause the returns of listed real estate firms. The study is significant because it indicates the importance of lending policies in relation to the real estate market in establishing a healthy financial system.     

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。     

Are REITs real estate? Evidence from international sector level data

The aim of this study is to examine whether securitized real estate returns reflect direct real estate returns or general stock market returns using international data for the U.S., U.K., and Australia. In contrast to previous research, which has generally relied on overall real estate market indices and neglected the potential long-term dynamics, our econometric evaluation is based on sector level data and caters for both the short-term and long-term dynamics of the assets as well as for the lack of leverage in the direct real estate indices. In addition to the real estate and stock market indices, the analysis includes a number of fundamental variables that are expected to influence real estate and stock returns significantly. We estimate vector error-correction models and investigate the forecast error variance decompositions and impulse responses of the assets. Both the variance decompositions and impulse responses suggest that the long-run REIT market performance is much more closely related to the direct real estate market than to the general stock market. Consequently, REITs and direct real estate should be relatively good substitutes in a long-horizon investment portfolio. The results are of relevance regarding the relationship between public and private markets in general, as the ‘duality’ of the real estate markets offers an opportunity to test whether and how closely securitized asset returns reflect the performance of underlying private assets. The study also includes implications concerning the recent financial crisis.     

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.     

The cross-section of equity returns and assets’ fundamental cash-flow risk

The decomposition of consumption beta into a component driven by assets’ cash-flow news and one related to assets’ discount-rate news reveals that macroeconomic risks embodied in cash flows largely account for the cross-sectional dynamics of average stock returns. Empirically, we find that differences in expected excess returns between low book-to-market and high book-to-market portfolios are associated with differences in their cash-flow betas, and thus reflect macroeconomic, especially consumption-related risks. This result holds true for a broad set of consumption-based asset pricing models. In addition, the results indicate that the risk premium on equity markets is primarily driven by the exposure of assets’ cash-flow components to the cyclical variability of durable consumption goods.     

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.     

Volatility,the Macroeconomy,and Asset Prices

How important are volatility fluctuations for asset prices and the macroeconomy? We find that an increase in macroeconomic volatility is associated with an increase in discount rates and a decline in consumption. We develop a framework in which cash flow, discount rate, and volatility risks determine risk premia and show that volatility plays a significant role in explaining the joint dynamics of returns to human capital and equity. Volatility risk carries a sizable positive risk premium and helps account for the cross section of expected returns. Our evidence demonstrates that volatility is important for understanding expected returns and macroeconomic fluctuations.     

Detecting news in aggregate accounting earnings: implications for stock market valuation

How much news is there in aggregate accounting earnings? I provide evidence that earnings changes at the stock market level are correlated with new information about not only expected future cash flows but also discount rates. A comprehensive investigation of the link to discount rates reveals that aggregate earnings changes are tied to news about all components of the expected future stock market return, i.e., the real riskless rate, expected inflation, and the expected equity risk premium. Over the sample period studied, cash flow news and discount rate news in aggregate earnings changes covary positively and have offsetting impacts on stock market prices. As a result, stock market prices appear to be insensitive to aggregate earnings changes. The findings highlight the importance of separating cash flow news from discount rate news when evaluating the information content of accounting earnings at the stock market level. Overall, my study sheds new light on the informativeness and relevance of accounting earnings for valuation at the stock market level.     

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.     

News and the cross-section of expected corporate bond returns

We study the cross-section of expected corporate bond returns using an inter-temporal CAPM (ICAPM) with three-factors: innovations in future excess bond returns, future real interest rates and future expected inflation. Our test assets are a broad range of corporate bond market index portfolios. We find that two factors – innovations about future inflation and innovations about future real interest rates – explain the cross-section of expected corporate bond returns in our sample. Our model provides an alternative to the ad hoc risk factor models used, for example, in evaluating the performance of bond mutual funds.     

Findings from a Cross-Sectional Housing Risk-Factor Model

Housing data from the last 25 years show that returns to residential real estate in the U.S. can be volatile and vary significantly among locations. The variations in returns are driven by economically as well as geographically and psychologically motivated factors, but so far, no asset pricing model that adequately explains systematic risks in cross-sectional housing returns is widely accepted. This paper proposes an asset pricing model for housing returns that includes a market-wide return factor, an economically motivated factor derived from income growth, a geographically based factor derived from land supply elasticity and a momentum factor, which is psychological in nature. The model explains well the systematic risks in housing returns and is robust to different portfolio segmentations. Moreover, the model illustrates that local risk factors indirectly capture the risk previously attributed to market-wide price changes. While housing is not actively traded when compared to other financial assets, understanding the risk-factors that explain housing return in cross-section provides important insight for real estate investors, builders, real estate future traders, homeowners, banks and other mortgage lenders.     

Investment Plans and Stock Returns

When the discount rate falls, investment should rise. Thus with time-varying discount rates and instantly changing investment, investment should positively covary with current stock returns and negatively covary with future stock returns. Aggregate nonresidential U.S. investment contradicts both these implications, probably because of investment lags. Investment plans, however, satisfy both implications. These investment plans, from a U.S. government survey of firms, are highly informative measures of expected investment and explain more than three-quarters of the variation in real annual aggregate investment growth. Plans have substantial forecasting power for excess stock returns, showing that time-varying risk premia affect investment.     

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.