The predictability of returns on equity REITs and their co-movement with other assets

Recent evidence suggests that the variation in the expected excess returns is predictable and arises from changes in business conditions. Using a multifactor latent variable model with time-varying risk premiums, we decompose excess returns into expected and unexpected excess returns to examine what determines movements in expected excess returns for equity REITs are more predictable than all other assets examined, due in part to cap rates which contain useful information about the general risk condition in the economy. We also find that the conditional risk premiums (expected excess returns) on EREITs move very closely with those of small cap stocks and much less with those of bonds.     

The risk adjusted uncovered equity parity

This paper explores the risk adjusted uncovered equity parity model to investigate a degree of market integration for four Asian emerging markets relative to the U.S., Japan and the U.K. from January 1994 to July 2008. The uncovered equity parity is revised to take into account of market risk in a framework of a portfolio rebalancing model. Evidence was found to strongly support our hypotheses; Market risk is significant in international capital flows between the Asian emerging markets and the developed economies, and it can help explain the failure of a traditional uncovered equity (or interest) parity model. The relationship between returns and an appreciation of the exchange rate are divided between the Asian emerging markets and the developed economies, depending on the direction of capital flows.     

The Conditional Distribution of Real Estate Returns: Are Higher Moments Time Varying?

Previous research has shown that the returns on individual properties and listed property securities are skewed. This claim is investigated in the context of listed U.K. property companies and U.S. REITs. In particular, the shape of the conditional distribution of total monthly returns is examined for a group of 20 U.K. companies and 20 REITs. Also investigated is the claim that the skewness found in property returns varies over time. Using the model of Hansen (1994), it is found that while a large portion of property security returns in the sample do exhibit skewness in the conditional distribution only in a few instances is there time variation in the skewness parameter. There is little evidence to suggest that skewness is associated with the economic cycle.     

Mean reversion in Southeast Asian stock markets

This paper assesses the predictable component of South East Asian stock markets using a bootstrap resampling method to estimate the small sample distributions of variance ratio statistics. We find evidence of mean reversion in long horizon dollar adjusted excess returns. The robustness of the results is assessed by adjusting stock returns for potential time-varying expected returns and partial integration of these emerging markets into world capital markets. In all but one case, mean reversion is shown to be due to either time-variation of risk exposure and prices of risk or partial integration of the local market into world stock markets. These results clearly illustrate the dangers of testing market efficiency without carefully adjusting stock returns for time variation in expected returns and the partial integration of local markets into world markets.     

Is commercial real estate a good hedge against inflation? Evidence from South Africa

This study investigates the inflation hedging ability of Commercial Real Estate (CRE) in South Africa. The Vector Error Correction (VEC) model for cointegrated time series was used to investigate the long run relationship between property returns and inflation and to determine whether inflation drives property returns, and if so, to what degree it drives returns. This study finds that in the short run, CRE investments are generally a pervasive hedge against inflation. In the long run, retail and industrial property hedge against inflation, with retail property being the better inflation hedge of the two property types.     

Risk profiles: how do they change when stock markets collapse?

This paper has two main objectives: the first is to unveil the relative importance of global versus local risk factors in influencing excess returns in the emerging country stock markets; the second is to analyse how the observed risk profiles change when markets undergo a major crisis. Our main country of focus is Mexico, but we also analyse six Asian countries which went through the 1997 Asian crisis. Our findings indicate that during stable periods investors are mainly concerned about global risk factors, whereas close to a crisis they also include local factors in their information sets in forming expectations about future excess returns.     

International Diversification Strategies for Direct Real Estate

This paper will disentangle the performance of international real estate into property type performance and region selection. This helps to create an international diversification strategy for direct real estate. We use constrained cross-section regression with dummy variables for regions and property types to measure the best risk reducer. We analyze the impact of currency changes on total returns by looking at a hedged and un-hedged portfolio, both stock and equally weighted. The findings show that geographic factors have the largest influence on the volatility of international real estate returns. The average variance of the regional effects is higher than the property type effects and therefore the regional effects have a higher influence on the variation of the total portfolio. However, the regional effects are less stable through time, compared with the variance and correlation of the property type effects. Also the property type effect seems to become a more important factor for the return over time, especially when the return is expressed in local currency.     

The present value model with time-varying discount rates: Implications for commercial property valuation and investment decisions

A vector autoregressive model is developed for predicting cash flow and returns in the private (unsecuritized) commercial property markets. The model predicts both of these variables quite well during the sample period. The forecasting model is then used to develop a simple buy/sell rule for identifying property market value peaks and troughs. An improved present value model, taking account of the predictability of property returns, is described and found to track historical market values much more closely than does either the appraisal-based index or the traditional present value model with constant expected returns. Analysis in this paper suggests that most of the change in commercial property market values has been due to changes in expected returns, rather than to changes in expected future operating cash flows.     

Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis

This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.     

International diversification: A copula approach

The viability of international diversification involves balancing benefits and costs. This balance hinges on the degree of asset dependence. In light of theoretical research linking diversification and dependence, we examine international diversification using two measures of dependence: correlations and copulas. We document several findings. First, dependence has increased over time. Second, we find evidence of asymmetric dependence or downside risk in Latin America, but less in the G5. The results indicate very little downside risk in East Asia. Third, East Asian and Latin American returns exhibit some correlation complexity. Interestingly, the regions with maximal dependence or worst diversification do not command large returns. Our results suggest international limits to diversification. They are also consistent with a possible tradeoff between international diversification and systemic risk.     

Dynamics of Asset Prices and Transaction Activity in Illiquid Markets: the Case of Private Commercial Real Estate

This paper investigates the relationship between capital flows, turnover and returns for the UK private real estate market. We examine a number of possible implications of capital flows and turnover on capital returns testing for evidence of a price pressure effect, ‘return chasing’ behaviour and information revelation. The main tool of analysis is a panel vector autoregressive (VAR) regression model in which institutional capital flows, turnover and returns are specified as endogenous variables in a two equation system in which we also control for macro-economic variables. Data on flows, turnover and returns are obtained for the ten market segments covering the main UK commercial real estate sectors. Our results do not support the widely-held belief among practitioners that capital flows have a ‘price pressure’ effect on property prices. However, we do find a significant positive relationship between lagged turnover and contemporaneous capital returns, suggesting that asset turnover provides increased price revelation which, in turn, reduces investment risk and increases property values.     

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.     

Property shares, appraisals and the stock market: An international perspective

A severe problem facing both real estate researchers and investors is the lack of reliable real estate returns data. Property shares, the shares of companies which invest in property and manage a portfolio of real estate, have been proposed as indicators of real estate performance. Property shares exist in many countries, are publicly traded, and their returns are not inherently biased. For three countries, we investigate the relationships with common stock and appraisal-based returns which property share returns exhibit. Our results indicate that property shares are closely related to the stock markets on which they trade, thereby confirming previous findings for the United States. However, property share returns also predict appraisal-based indices.     

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.     

Bank Holding Company Risk from 1976–1989 with a Two-Factor Model

This paper employs a two-factor model of security returns to investigate the intertemporal risk of bank holding company stock returns over the 1976–1989 period. Uniquely, the two-factor model is estimated in separate regressions for each of the fourteen years between 1976 and 1989, thus exposing intertemporal changes in the model coefficients. The results show that bank holding companies have increased in risk over the sample period and also reveal that much of the controversy over the two-index model stems from the transitory nature of the interest rate coefficient through time, making long time series groupings of data misspecified. The above holds for both short-term and long-term interest rates. Interest rates have little impact on bank returns.     

A dynamic equilibrium model for U-shaped pricing kernels

This paper proposes a dynamic equilibrium model that can provide a unified explanation for the stylized facts observed in stock index markets such as the fat tails of the risk-neutral return distribution relative to the physical distribution, negative expected returns on deep OTM call options and negative realized variance risk premiums. In particular, we focus on the U-shaped pricing kernel against the stock index return, which is closely related to the negative call returns. We assume that the stock index return follows a time-changed Lévy process and that a representative investor has power utility over the aggregate consumption that forms a linear regression of the stock index return and its stochastic activity rate. This model offers a macroeconomic interpretation of the stylized facts from the perspective of the sensitivity of the activity rate and stock index return on aggregate consumption as well as the investor’s risk aversion.     

Time Variation in the Covariance between Stock Returns and Consumption Growth

The conditional covariance between aggregate stock returns and aggregate consumption growth varies substantially over time. When stock market wealth is high relative to consumption, both the conditional covariance and correlation are high. This pattern is consistent with the “composition effect,” where agents' consumption growth is more closely tied to stock returns when stock wealth is a larger share of total wealth. This variation can be used to test asset‐pricing models in which the price of consumption risk varies. After accounting for variations in this price, the relation between expected excess stock returns and the conditional covariance is negative.     

Do liquidity and idiosyncratic risk matter? Evidence from the European mutual fund market

This paper examines the interaction of idiosyncratic risk, liquidity and return across time in determining fund performance, as well as across investment style portfolios of European mutual funds. This study utilizes a unique data set including returns for equity mutual funds registered in six European countries. Overall, using monthly data, we find that both liquidity and idiosyncratic risk are relevant in determining mutual fund returns. Our results are robust across different model specifications. We show that model specifications up to six factors are useful as these risk factors capture different aspects in the cross-section of mutual funds returns. The evidence regarding mutual funds subgroups is strongly in favor of the significance of liquidity, and idiosyncratic risk to a lesser extent, as risk factors. Even if liquidity and idiosyncratic risk are considered at the same time, one factor is not significantly decreasing the importance of the other factor.     

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.     

Capturing downside risk in financial markets: the case of the Asian Crisis

Using data on Asian equity markets, we observe that during periods of financial turmoil, deviations from the mean-variance framework become more severe, resulting in periods with additional downside risk to investors. Current risk management techniques failing to take this additional downside risk into account will underestimate the true Value-at-Risk with greater severity during periods of financial turnoil. We provide a conditional approach to the Value-at-Risk methodology, known as conditional VaR-x, which to capture the time variation of non-normalities allows for additional tail fatness in the distribution of expected returns. These conditional VaR-x estimates are then compared to those based on the RiskMetrics™ methodology from J.P. Morgan, where we find that the model provides improved forecasts of the Value-at-Risk. We are therefore able to show that our conditional VaR-x estimates are better able to capture the nature of downside risk, particularly crucial in times of financial crises.