Asymmetric Information and the Predictability of Real Estate Returns

This article examines the relation between systematic price changes and the heterogeneity of investors information sets in real estate asset markets. The empirical implications rely on a theoretical economy in which information asymmetry alters the dynamic relation between returns and trading volume. We employ a filter-rule methodology to determine predictability in returns and augment the return-based conditioning set with trading volume. The additional conditioning information is necessary since the model is underspecified when predictability is based on returns alone. Our results provide new insight into the coexistence of informational and noninformational exchange in the speculative markets for real estate assets. Specifically, we find that the predictability of real estate returns is generally more indicative of portfolio rebalancing effects than an adverse-selection problem. These results are unique in addressing the time-variation in information asymmetry.     

Trading with Asymmetric Volatility Spillovers

Abstract:  We study the profitability of trading strategies based on volatility spillovers between large and small firms. By using the Volatility Impulse-Response Function of Lin (1997) and its extensions, we detect that any volatility shock coming from small companies is important to large companies, but the reverse is only true for negative shocks coming from large firms. To exploit these asymmetric patterns in volatility, different trading rules are designed based on the inverse relationship existing between expected return and volatility. We find that most strategies generate excess after-transaction cost profits, especially after very bad news and very good news coming from large or small firm markets. These results are of special interest because of their implications for risk and portfolio management.     

Predictability in Consumption Growth and Equity Returns: A Bayesian Investigation

We use a Bayesian method to estimate a consumption-based asset pricing model featuring long-run risks. Although the model is generally consistent with consumption and dividend growth moments in annual data, the conditional mean of consumption growth (a latent process) is not persistent enough to satisfy the restriction that the price-dividend ratio be an affine function of the latent process. The model also requires relatively high intertemporal elasticity of substitution to match the low volatility of the risk-free return. These two restrictions lead to the equity volatility puzzle. The model accounts for only 50% of the total variation in asset returns.     

Macroeconomic Determinants of European Stock Market Volatility

In this paper we investigate whether macroeconomic variability can explain time variation in European stock market volatility. We find that unlike the documented case of the USA, in many cases, the time variation in stock market volatility is found to be significantly affected by the past variability of either monetary or real macroeconomic factors. Our findings have important implications for capital and portfolio allocations.     

Commodities and Macroeconomic Factors: Unconditional Volatility Measures

Abstract:

This study focuses on the measurement of spillover effects from macroeconomic factors to commodity volatility. It argues that such measurement is sensitive to volatility computation and to causality testing. To this end, I analyze two commodity data sets-gold and the Continuous Commodity Index (1969-2011), and twenty-four Dow Jones futures indexes (1991-2011)-and various macroeconomic indicators. I conclude that the macroeconomic factors that influence volatility generally depend on the commodity under consideration. I also explore whether commodities of the same class experience volatility shifts around the same dates, and find that this is not the case except for energy commodities.     

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

Firm size and volatility analysis in the Spanish stock market

Using Spanish stock market data, this paper examines volatility spillovers between large and small firms and their impact on expected returns. By using a conditional capital asset pricing model (CAPM) with an asymmetric multivariate GARCH-M covariance structure, it is shown that there exist bidirectional volatility spillovers between both types of companies, especially after bad news. After estimating the model, a positive and significant price of risk is obtained. This result is consistent with the volatility feedback effect, one of the most popular explanations of the asymmetric volatility phenomenon, and explains why risk premiums are much more sensitive to negative return shocks coming from the whole market or other related markets.     

The Nature and Persistence of Initial Public Offering Aftermarket Returns Predictability

This paper examines the predictability of monthly aftermarket returns of initial public offerings during the first six years of trading. Predictability is tested under the null hypothesis of random walk using a Markov chain analysis. The evidence shows that excess returns of IPOs (adjusted for the return on the equally weighted NASDAQ index) demonstrate non-random walk behavior through the first five years of trading and random walk behavior in the sixth year. This is accompanied by predictability of monthly excess returns conditioned on the two previous months' excess returns. A trading strategy is offered to capitalize on the predictability patterns. Implementing the trading strategy is not possible due to institutional barriers, providing additional explanation for why IPOs do not reach their intrinsic values for extended periods of time.     

Macroeconomic Factors in the Dynamics of Corporate and Household Saving: Evidence from Central and Eastern Europe

This article uses panel data estimations on annual data from 10 Central and Eastern European countries to assess the effect of different macroeconomic variables on the dynamics of corporate and household saving. The analyses show that changes in the macroeconomic environment affect the saving rates in both sectors, but with marked differences across the two sectors. The differences are most pronounced for the output gap, the real interest rate, the inflation rate, and the current account balance. Some variables, including the unemployment rate and changes in the real exchange rate, are unimportant in both sectors. The different results for the two sectors underscore the importance of analyzing the factors driving the dynamics of corporate and household saving separately.     

美国房地产周期与经济衰退的可预测性研究

本文对房地产周期与收益率曲线反转对经济衰退的预测两个变量的联合预测进行了理论探讨和实证检验。实证结果表明,房地产周期和收益率曲线反转的联合预测力远大于单变量预测力。将本文实证结果应用于2006年以来经济数据的分析表明,从预测角度看美国经济将在2007-2008年间进入衰退。     

Assessing the Economic Significance of Return Predictability: A Research Note

The predictability of stock returns is often assessed using classical statistical significance from predictive regressions. Statistical inference, however, can belie the economic importance with which investors regard various predictors. This paper examines the influence that predictors have on an investor's optimal portfolio allocations. The results show that return predictability is sufficient to induce horizon effects in optimal allocations. After incorporating estimation risk, however, little evidence of predictability remains. We also assess the relative importance of three predictor variables. While dividend yield is the most important predictor, optimal allocations are also sensitive to the term spread and the relative bill rate.     

Time-Varying Variance Risk Premium and the Predictability of Chinese Stock Market Return

A number of studies have shown that the variance risk premium (VRP), defined as the difference between risk-neutral and physical expected variances, has strong predictive power for the excess stock market return, and this predictability peaks at 3- to 6-month prediction horizons. However, little research presents empirical evidences for Chinese stock market due to the absence of option market. Under general equilibrium asset pricing framework, this article estimates time-varying VRP using the Chinese stock market data. We find that the estimated VRP predicts the excess Chinese stock market return, and this forecasting power is stronger at 4- and 5-month horizons, which is consistent with the findings of existing literature.     

Good volatility,bad volatility,and the cross section of cryptocurrency returns

This paper examines the predictability of realized volatility measures (RVM), especially the realized signed jumps (RSJ), on future volatility and returns. We confirm the existence of volatility persistence and future volatility is more strongly related to the volatility of past positive returns than to that of negative returns in the cryptocurrency market. RSJ-sorted cryptocurrency portfolios yield statistically and economically significant differences in the subsequent portfolio returns. After controlling for cryptocurrency market characteristics and existing risk factors, the differences remain significant. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.     

Non‐linear Predictability of Value and Growth Stocks and Economic Activity

Recent empirical evidence suggests that stock market index returns are predictable from a variety of financial and macroeconomic variables. We extend this research by examining value and growth portfolios constructed by book-to-market ratio, and consider whether such predictability is evident here. Further, we assess whether such predictability is better characterised by a non-linear form and whether such non-linear predictability can be exploited to provide superior forecasts to those obtained from a linear model. General non-linearities are examined using non-parametric techniques, which suggest possible threshold behaviour. This leads to estimation of a smooth-transition threshold model, with the results indicating an improved in-sample performance and marginally superior out-of-sample forecast results.     

中国宏观经济变量平稳性分析

本文采用目前国际上普遍应用的DF和ADF检验方法，对我国主要宏观经济变量的平稳性及单整阶数进行了单位根检验，研究结果显示中国宏观经济变量在5％显著性水平上都是非平稳的。     

Predictability of structural co-movement in commodity prices: the role of technical indicators

This paper investigates the financialization and structural co-movement of several commodity futures using factor variance decomposition and predictability of technical indicators and macro variables. We find that financialization is still a dominant player in the commodity market and that recent commodity price fluctuations can be significantly and robustly forecasted by technical analyses of commodity index investments. Moreover, the co-movement of commodities is demonstrated by variance decomposition and explained as commodity index investment, which provides evidence of financialization. The overall empirical analysis reveals that technical indicators and macro variables can statistically and economically forecast the indexed investment and off-index trading, respectively, which indicates that they are suitable predictors of the commodity markets.     

Unconditional and Conditional Distributional Models for the Nikkei Index

We investigate alternative unconditional and conditional distributional models for the returns on Japan's Nikkei 225 stock market index. Among them is the recently introduced class of ARMA-GARCH models driven by α-stable (or stable Paretian) distributed innovations, designed to capture the observed serial dependence, conditional heteroskedasticity and fat-tailedness present in the return data. Of the eight entertained distributions, the partially asymmetric Weibull, Student's t and asymmetric α-stable present themselses as the most viable candidates in terms of overall fit. However, the tails of the sample distribution are approximated best by the asymmetric α-stable distribution. Good tail approximations are particularly important for risk assessments. This revised version was published online in August 2006 with corrections to the Cover Date.     

Modeling the Conditional Covariance Between Stock and Bond Returns: A Multivariate GARCH Approach

To analyze the intertemporal interaction between the stock andbond market returns, we assume that the conditional covariancematrix follows a multivariate GARCH process. We allow for asymmetriceffects in conditional variances and covariances. Using dailydata, we find strong evidence of conditional heteroskedasticityin the covariance between stock and bond market returns. Theresults indicate that not only variances, but also covariancesrespond asymmetrically to return shocks. Bad news in the stockand bond market is typically followed by a higher conditionalcovariance than good news. Cross asymmetries, that is, asymmetriesfollowed from shocks of opposite signs, appear to be importantas well. Covariances between stock and bond returns tend tobe relatively low after bad news in the stock market and goodnews in the bond market. A financial application of our modelshows that optimal portfolio shares can be substantially affectedby asymmetries in covariances. Moreover, our results show sizablegains due to asymmetric volatility timing.