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.     

Causal and Dynamic Relationships among Stock Returns,Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia

This paper examines the causal and dynamic relationships among stock returns, return volatility and trading volume for five emerging markets in South-East Asia—Indonesia, Malaysia, Philippines, Singapore and Thailand. We find strong evidence of asymmetry in the relationship between the stock returns and trading volume; returns are important in predicting their future dynamics as well as those of the trading volume, but trading volume has a very limited impact on the future dynamics of stock returns. However, the trading volume of some markets seems to contain information that is useful in predicting future dynamics of return volatility.     

Revisiting the empirical linkages between stock returns and trading volume

This paper investigates whether the empirical linkages between stock returns and trading volume differ over the fluctuations of stock markets, i.e., whether the return–volume relation is asymmetric in bull and bear stock markets. Using monthly data for the S&P 500 price index and trading volume from 1973M2 to 2008M10, strong evidence of asymmetry in contemporaneous correlation is found. As for a dynamic (causal) relation, it is found that the stock return is capable of predicting trading volume in both bear and bull markets. However, the evidence for trade volume predicting returns is weaker.     

Correlation and Volatility Dynamics in International Real Estate Securities Markets

We study international correlation and volatility dynamics of publicly traded real estate securities using monthly returns from 1984 and 2006. We also examine, for comparison, the correlations among the corresponding stock markets. A multivariate dynamic conditional correlation model captures the time-varying correlation within the full period. We confirm lower correlations between all real estate securities market returns than those between the stock market returns themselves. Some significant variations and structural changes in the correlation structure happened within the sample period. We detect a strong and positive connection between real estate securities market correlations and their conditional volatilities. We also find the international correlation structure of real estate securities and the broader stock market are linked to each other. Our results have economic motivations regarding the potential integration of international real estate securities markets and the possibility of including information on changing correlations and volatilities to design more optimal portfolios for international real estate securities.

Are Securitized Real Estate Returns more Predictable than Stock Returns?

This paper examines whether the predictability of securitized real estate returns differs from that of stock returns. It also provides a cross-country comparison of securitized real estate return predictability. In contrast to most of the literature on this issue, the analysis is not based on a multifactor asset pricing framework as such analyses may bias the results. We use a time series approach and thus create a level playing field to compare the predictability of the two asset classes. Forecasts are performed with ARMA and ARMA–EGARCH models and evaluated by comparing the entire empirical distributions of prediction errors, as well as with a trading strategy. The results, based on daily data for the 1990–2007 period, show that securitized real estate returns are generally more predictable than stock returns in countries with mature and well established REIT regimes. ARMA–EGARCH models are found to have portfolio outperformance potential even in the presence of transaction costs, with generally better results for securitized real estate than for stocks.     

Trading volume and short-horizon contrarian profits: Evidence from the Malaysian market

We provide evidence on short-term predictability of stock returns on the Malaysian stock market. We examine the relation between return predictability and the level of trading activity. This is particularly relevant in emerging stock markets, where thin trading is more pervasive. We find that the returns from a contrarian portfolio strategy are positively related to the level of trading activity in the securities. Specifically, the contrarian profits on actively and frequently traded securities are significantly higher than that generated from the low trading activity securities. We find that the differential behavior of high- and low-volume securities is not subsumed by the size effect, although for the small firms, the volume–predictability relation is most pronounced. We also suggest that the price patterns may be related to the institutional arrangement in the Malaysian stock market.     

Trading activity and price reversals in futures markets

We use the standard contrarian portfolio approach to examine short-horizon return predictability in 24 US futures markets. We find strong evidence of weekly return reversals, similar to the findings from equity market studies. When interacting between past returns and lagged changes in trading activity (volume and/or open interest), we find that the profits to contrarian portfolio strategies are, on average, positively associated with lagged changes in trading volume, but negatively related to lagged changes in open interest. We also show that futures return predictability is more pronounced if interacting between past returns and lagged changes in both volume and open interest. Our results suggest that futures market overreaction exists, and both past prices and trading activity contain useful information about future market movements. These findings have implications for futures market efficiency and are useful for futures market participants, particularly commodity pool operators.     

The Dynamic Relation Between Stock Returns, Trading Volume, and Volatility

We examine the dynamic relation between returns, volume, and volatility of stock indexes. The data come from nine national markets and cover the period from 1973 to 2000. The results show a positive correlation between trading volume and the absolute value of the stock price change. Granger causality tests demonstrate that for some countries, returns cause volume and volume causes returns. Our results indicate that trading volume contributes some information to the returns process. The results also show persistence in volatility even after we incorporate contemporaneous and lagged volume effects. The results are robust across the nine national markets.     

Asymmetric Volume‐Return Relation and Concentrated Trading in LIFFE Futures

This study demonstrates that intraday volume and return on LIFFE interest rate and currency futures exhibit an asymmetric volume‐return relationship characterised by significantly larger volume associated with negative returns than with non‐negative returns. This finding is unlike the stylised asymmetric relation often observed in equity markets, where the volume on price rise is larger than the volume on price decline. The asymmetric relationship in LIFFE futures is also found to be dynamic as the direction of asymmetry can reverse during the day. It has been argued in the past that a costly short sale restriction that requires a higher transaction cost on a short position than on a long position is responsible for the asymmetric effect in equity markets. Since such a restriction is absent in futures markets, they should not exhibit any asymmetric volume behaviour. Based on the results of this research, the costly short sale hypothesis is rejected. An alternative explanation of the asymmetric relation observed in futures is presented based on recent information models that take into consideration asymmetrically‐informed traders, their dispersion of beliefs, quality and quantity of the information signal, and how the traders process it. The paper also confirms a strong U‐shape trading pattern in 15‐minute volume, but no such pattern is identified in intraday returns.     

Volatility Transmission in the Real Estate Spot and Forward Markets

How shocks in one market influence the returns and volatility of other markets has been an important question for portfolio managers. In the finance literature, many studies found evidence of volatility spillovers across international markets, as well as between spot and futures markets. Although real estate is often regarded as a good vehicle for diversification, the dynamics of its volatility transmission have been largely ignored. This paper provides the first study to examine volatility spillovers between the spot and forward (pre-sale) index returns of the Hong Kong real estate market through a bivariate GARCH model. Transaction-based indices were used so that our volatility modelling was free from any smoothing problem. Our results showed that real estate returns exhibited volatility clustering, and the volatility of the forward market was more sensitive to shocks than the spot market. Moreover, volatility was mainly transmitted from the forward market to the spot market, but not vice versa.

Striking oil: Another puzzle?

Changes in oil prices predict stock market returns worldwide. We find significant predictability in both developed and emerging markets. These results cannot be explained by time-varying risk premia as oil price changes also significantly predict negative excess returns. Investors seem to underreact to information in the price of oil. A rise in oil prices drastically lowers future stock returns. Consistent with the hypothesis of a delayed reaction by investors, the relation between monthly stock returns and lagged monthly oil price changes strengthens once we introduce lags of several trading days between monthly stock returns and lagged monthly oil price changes.     

The predictability of real estate returns and market timing

Recent evidence suggests that all asset returns are predictable to some extent with excess returns on real estate relatively easier to forecast. This raises the issue of whether we can successfully exploit this level of predictability using various market timing strategies to realize superior performance over a buy-and-hold strategy. We find that the level of predicability associated with real estate leads to moderate success in market timing, although this is not necessarily the case for the other asset classes examined in general. Besides this, real estate stocks typically have higher trading profits and higher mean risk-adjusted excess returns when compared to small stocks as well as large stocks and bonds even though most real estate stocks are small stocks.     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

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.     

How does trading volume affect financial return distributions?

We assess investors' reaction to new information arrivals in financial markets by examining the relationships between trading volume and the higher moments of returns in 18 international equity and currency markets. Our volume-volatility results support extant information theories and further contribute new evidence of cross market relations between volume and volatility. We also find that the direct impact of volume on the level of negative skewness is less significant for more diversified regional portfolios. Furthermore, the negative interaction between volume and kurtosis can be explained by the differences of opinion in financial markets. We observe stronger interdependence among higher moments in reaction to significant events, but the strength is dampened by trading volume. This result is consistent with trading volume being a source of heteroskedasticity in asset returns.     

Predictability and Persistence of the Price Movements of the S&P/Case-Shiller House Price Indices

This paper examines persistence in price movements and predictability of the US housing market both on a local level across 20 cities in the US and on a nationwide level. We use a time series approach instead of often applied multivariate approaches to exclude potential biases across local markets and provide trading strategies to compare predictability across markets and to test whether or not the detected persistence can be exploited by investors to earn excess returns. The results from the monthly and quarterly transaction-based S&P/Case-Shiller house price indices from 1987 to 2009 provide empirical evidence on strong persistence. This is confirmed by both parametric and non-parametric tests for nominal and real house prices based on expected inflation. Furthermore, the empirical findings suggest that investors might be able to obtain excess returns from both autocorrelation-based and moving average-based trading strategies compared to a buy-and-hold strategy, although the results depend on the transaction costs individual investors face.     

The Inflation Hedging Characteristics of US and UK Investments: A Multi-Factor Error Correction Approach

Historic analysis of the inflation hedging properties of stocks has produced anomalous results, with stocks often appearing to offer a perverse hedge. This has been attributed to the impact of real and monetary shocks to the economy, which influence both inflation and asset returns. It has been argued that real estate should provide a better hedge: however, empirical results have been mixed. This paper explores the relationship between commercial real estate returns and economic, fiscal and monetary factors and inflation for US and UK markets. Comparative analysis of general equity and small capitalization stock returns is carried out with inflation divided into expected and unexpected components. The analyses are undertaken using an error correction approach. In the long run, once real and monetary variables are included, asset returns are positively linked to anticipated inflation but not to inflation shocks. Adjustment processes are, however, gradual and not within period. Real estate returns, particularly private market returns, exhibit characteristics that differ from those of stocks.

Rational Delays: The Case of Real Estate

Real estate markets, for both commercial real estate and single family homes, typically respond to a large negative demand shock with a period during which the volume of transactions and liquidity of real estate declines. Explanations for these periods have focused on overly optimistic owners, imperfections in real estate markets and/or minimum down payment requirements. These are important characteristics of real estate markets, but they do not provide a satisfying explanation for the long-term declines in the number of transactions and liquidity of real estate that frequently follow negative demand shocks. This paper presents estimates, for a specific real estate market (Los Angeles single family dwellings), of the option-like value of an owners interest in a property. Our estimates imply that when an owner has little or negative equity, the value of waiting to sell is likely to exceed the net carrying cost. Consequently, the option value of a potential sellers interest may eliminate the possibility of an otherwise mutually advantageous transaction.     

The bivariate GARCH approach to investigating the relation between stock returns,trading volume,and return volatility

We use a bivariate GJR-GARCH model to investigate simultaneously the contemporaneous and causal relations between trading volume and stock returns and the causal relation between trading volume and return volatility in a one-step estimation procedure, which leads to the more efficient estimates and is more consistent with finance theory. We apply our approach to ten Asian stock markets: Hong Kong, Japan, Korea, Singapore, Taiwan, China, Indonesia, Malaysia, the Philippines, and Thailand. Our major findings are as follows. First, the contemporaneous relation between stock returns and trading volume and the causal relation from stock returns and trading volume are significant and robust across all sample stock markets. Second, there is a positive bi-directional causality between stock returns and trading volume in Taiwan and China and that between trading volume and return volatility in Japan, Korea, Singapore, and Taiwan. Third, there exists a positive contemporaneous relation between trading volume and return volatility in Hong Kong, Korea, Singapore, China, Indonesia, and Thailand, but a negative one in Japan and Taiwan. Fourth, we find a significant asymmetric effect on return and volume volatilities in all sample countries and in Korea and Thailand, respectively.     

Discovering REIT Price Discovery: A New Data Setting

This study decomposes real estate investment trust (REIT) returns into two components: (1) real returns, and (2) public returns. The real returns are based on the changes in the private, appraisal-based net asset values of REITs, whereas the public returns are measured by the variations in REITs’ premiums/discounts. This study then investigates the price discovery of REIT prices. The results indicate that lagged public returns are useful in predicting real returns. In addition, the study documents concurrent factor exposures for public returns and lagged factor exposures for private returns under a variety of asset pricing models. Overall, the results are consistent with the notion that public markets are more efficient in processing information.