Common risk factors and risk premia in direct and securitized real estate markets (original) (raw)
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The Journal of Real Estate Finance and Economics, 2013
In pricing real estate with indifference pricing approach, market incompleteness is shown to significantly alter the conventional pricing relationships between real estate and financial asset. Specifically, we focus on the pricing implication of market comovement because comovement tends to be stronger in financial crisis when investors are especially sensitive to price declines. We find that real estate price increases with expected financial asset return but only in weak market comovement (i.e., a normal market environment) when investors enjoy diversification benefit. When market comovement is strong, real estate price strictly declines with expected financial asset return. More importantly, contrary to the conventional positive relationship from real option studies, real estate price generally declines with expected financial asset risk. With realistic market parameters, we show that there is a nonlinear relationship between real estate price and financial risk. When the market comovement is strong, real estate price only increases with financial asset risk when the risk is low but eventually declines
Macroeconomic risk influences on the property stock market
Purpose -The purpose of this paper is to provide an analysis of the relationship between expected risk premia on property stocks and some major macroeconomic risk factors as reflected in the general business and financial conditions Design/methodology/approach -Employs a three-step estimation strategy (principal component analysis, GARCH (1,1) and GMM) to model the macroeconomic risk variables (GDP growth, INDP growth, unexpected inflation, money supply, interest rate and exchange rate) and relate them to the first and second moments on property stock excess returns of four major markets, namely, Singapore, Hong Kong, Japan and the UK. Macroeconomic risk is measured by the conditional volatility of macroeconomic variables. Findings -The expected risk premia and the conditional volatilities of the risk premia on property stocks are time-varying and dynamically linked to the conditional volatilities of the macroeconomic risk factors. However there are some disparities in the significance, as well as direction of impact in the macroeconomic risk factors across the property stock markets. Consequently there are opportunities for risk diversification in international property stock markets. Originality/value -Results help international investors and portfolio managers deepen their understanding of the risk-return relationship, pricing of macroeconomic risk as well as diversification implications in major Asia-Pacific and UK property stock markets. Additionally, policy makers may play a role in influencing the expected risk premia and volatility on property stock markets through the use of macroeconomic policy. JPIF 24,4 296 investigates the influence of oil prices, world industrial production, world inflation rate, world market equity return and the return on a foreign-currency index on emerging market returns. documents that the industrial production output, T-bill rate and inflation are statistically significant in explaining the US stock market excess returns. In addition, the conditional variance-covariances of the three macroeconomic factors are important drivers of the conditional stock return volatility. Other recent studies include Liljeblom and Stenius In the real estate literature, consider the influences that macroeconomic factors have on the USA office construction using vector autoregressive (VAR) models that include monthly office construction, money supply, nominal interest rates and output (GNP). suggest that the bond market risk premium and stock market capitalization are the most important macroeconomic variables in explaining the average variation in REIT returns whilst Liu and Mei (1992) find that capitalization rate, dividend yield and Treasury Bill yield explain a significant portion of US REIT excess returns. Using the VAR methodology, show that prices, nominal rates, output and investment directly influence real estate returns. In addition, the state of economy explains almost 60 percent of the variations in REIT return series. Ling and Naranjo (1997) employ nonlinear multivariate regression techniques to find that the growth rate in real per capita consumption, real Treasury Bill rate, term structure of interest rates and unexpected inflation have influence on time-varying commercial real estate returns. find that there are varying degrees of predictability among stocks, bonds, and REITs and that most of the predictability of returns is associated with the economic variables employed in the asset pricing model. In addition, there is an important economic risk premium for REITs that is not represented in conventional multiple-beta asset pricing models. More recently, Johnson (2000) examines the association between Federal Reserve monetary policy and real estate returns using REIT indices as well as an index that removes the stock market influence to isolate the returns that are unique to real estate. Their results indicate a significant association between monetary condition and the performance of real estate market. In the UK, the Granger causality test results reported by indicate that the wider economy leads the real estate market in the short term but that, with a longer lag structure, positive real estate returns may point to negative future returns in the economy. Brooks and Tsolacos (1999) develop a VAR model that includes the rate of unemployment, nominal interest rates, spread between the long-and short-term interest rates, unanticipated inflation and dividend yield. Although their results are not strongly suggestive of any significant influences of the variables on variations of the filtered property returns series, there is some evidence that the interest rate term structure and unexpected inflation have contemporaneous effects on property returns.
Risk framework for Real Estate Investment Returns
This research paper's purpose is to help to a better assessment of different factors that impact real estate investment returns (properties, listed and non-listed funds). Mostly macroeconomic and other country-specific factors are considered in this research paper because data is scarce to consider other factors. Using a database from Morgan Stanley Capital International's International Property Database, I applied different regression techniques (mainly ordinary least squares method) to find whether there is a meaningful correlation between independent factors considered in the model and real estate investment returns. Multiple regressions will be applied based on different countries and different datasets. Two of these regressions are from the United States of America which are time-series analyses based on annual and quarterly data series. Additional two of these regressions are based on a cross-sectional database which includes twenty-four countries from a database of Morgan Stanley Capital International's International Property Database. And the last regressions are based on data from Osaka city of Japan, which is again from the MSCI IPD database. Contradicting results were found between regressions. In the time-series regressions, I found that Real and Nominal GDP growth are significant factors. In the cross-sectional regressions, I found that inflation and interest rates are significant factors. In the Osaka city case, I found a cointegration relationship between interest rates and cap rates used for the valuation of real estate investment returns.
Economic Risk Factors and Commercial Real Estate Returns
Journal of Real Estate Finance and Economics, 1997
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.
Equity and fixed income markets as drivers of securitised real estate
Review of Financial Economics, 2009
This paper re-examines the sensitivity and importance of interest rates and stock market price behavior on securitised property by decomposing their long-run impact between transient and permanent effects. This is achieved in a framework that accounts for endogenously determined structural breaks within the data. The results provide a different perspective on the relationship securitised property has with these markets and sheds new light on their long-run interaction. Once structural breaks are accounted for the results show that securitised property is driven by both interest rate and stock market changes, regardless of the type of securitised property being examined. Evidence also points to companies with increased debt-to-asset ratios and companies that are tax-exempt entities are still all influenced by both the equity and fixed income markets over the long-run period, although the influence these factors have do vary across time.
Bank risk and real estate: An asset pricing perspective
The Journal of Real Estate Finance and Economics, 1995
While a number of papers have investigated the time-series behavior of expost bank stock returns and real estate returns, no study has comprehensively studied the relationship between ex ante risk premiums on both assets and 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 the ex anre pricing of risk in the market for bank stocks. We tind 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.
Market conditions, risk, and real estate portfolio returns: Some empirical evidence
The Journal of Real Estate Finance and Economics, 1991
This research examined the return behavior of a portfolio of American and New York Stock Exchange real estate firms. A dummy variable procedure was used to test for excess return and/or change in risk behavior across market conditions. The findings were as follows. First, no excess return was found for any model specification. Second, no changes in beta were found using the benchmark approach. The beta shifted when an up market was defined as a nonrecessionary period; the beta behaved procyclically. However, the subperiod tests indicated that effect was transitory and period specific.
SSRN Electronic Journal, 2015
The last decade's boom and bust in U.S. commercial real estate (CRE) prices was at least as large as that in the housing market and also had a large effect on bank failures. Nevertheless, the role of CRE in the Great Recession has received little attention. This study estimates cohesive models of short-run and long-run movements in capitalization rates (rent-to-price-ratio) and risk premiums across the four major types of commercial properties. Results indicate that CRE price movements were mainly driven by sharp declines in required risk premia during the boom years, followed by sharp increases during the bust phase. Using decompositions of estimated long-run equilibrium factors, our results imply that much of the decline in CRE risk premiums during the boom was associated with weaker regulatory capital requirements. The return to normal risk premia levels in 2009 and 2010 was first driven by a steep rise in general risk premia that occurred after the onset of the Great Recession and later by a tightening of effective capital requirements on commercial mortgage-backed securities (CMBS) resulting from the Dodd-Frank Act. In contrast to the mid-2000s boom, the recovery in CRE prices since 2010 has been mainly driven by declines in real Treasury yields to unusually low levels. Our findings have important implications for the channels through which macro-prudential regulation may or may not be effective in limiting unsustainable increases in asset prices.
Risk and return in real estate
The Journal of Real Estate Finance and Economics, 1991
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.