Consumer confidence or the business cycle: What matters more for European expected returns?

Answer: The business cycle.We show that consumer confidence and the output gap both affect excess returns on stocks in many European countries: When the output gap is positive (the economy is doing well), expected returns are low, and when consumer confidence is high, expected returns are also low. Consumer confidence and the output gap are also highly positively correlated. In fact, we find that consumer confidence does not contain independent information (i.e. information over and above that contained by the output gap) about expected returns. Our use of European data allows us to examine both aggregate European and local-country data on consumer confidence and output gaps. We find that even local-country consumer confidence does not contain independent information about expected returns. Our findings have asset pricing implications: We show that the cross-country distribution of expected returns is better captured when using the European output gap as a risk factor.     

中国财政周期性波动的经济稳定效应分析

经济周期是经济增长过程中不可避免的现象。为尽可能避免经济运行出现过度波动,财政政策成为各国政府调控经济运行的常用工具。通过用HP滤波方法剔除掉中国产出、财政收入、财政支出和财政赤字中的趋势成分后,用产出缺口、财政收入缺口、财政支出缺口和财政赤字缺口进行计量分析,发现中国财政周期性波动中的财政赤字波动对宏观经济产生了明显的稳定效应,并且随着市场经济的逐步完善,政府调控经济运行的能力也在逐步增强。     

Information diffusion and the predictability of New Zealand stock market returns

This paper examines the impact of international predictors from liquid markets on the predictability of excess returns in the New Zealand stock market using data from May 1992 to February 2011. We find that US stock market return and VIX contribute significantly to the out‐of‐sample forecasts at short horizons even after controlling for the effect of local predictors, while the contribution by Australian stock market return is not significant. We further demonstrate that the predictability of New Zealand stock market returns using US market predictors could be explained by the information diffusion between these two countries.     

Is the Market Portfolio a Dynamic Factor? Evidence from Individual Stock Returns

This paper uses a factor model to test whether the market portfolio is a dynamic factor in the sense that individual stock returns contain a premium linked to the conditional risk of the market portfolio. The market conditional risk is based on a decomposition of the market variance into a time-varying trend component and a transitory component. The evidence shows that the conditional market premium is rising when the permanent trend rises relative to the conditional variance. The evidence for individual stock returns supports the notion that the market portfolio is a dynamic factor. Individual stock return autocorrelations are fully explained by the time variation in the market premium. The risk premia attributed to static factors are statistically insignificant.     

Do Decomposed Financial Ratios Predict Stock Returns and Fundamentals Better?

We investigate the prediction of excess returns and fundamentals by financial ratios, which include dividend‐price ratios, earnings‐price ratios, and book‐to‐market ratios, by decomposing financial ratios into a cyclical component and a stochastic trend component. We find both components predict excess returns and fundamentals. Cyclical components predict increases in future stock returns, while stochastic trend components predict declines in future stock returns in long horizons. This helps explain previous findings that financial ratios in the absence of decomposition find weak predictive power in short horizons and some predictive power in long horizons. We also find both components predict fundamentals.     

Consumption, Aggregate Wealth, and Expected Stock Returns

This paper studies the role of fluctuations in the aggregate consumption–wealth ratio for predicting stock returns. Using U.S. quarterly stock market data, we find that these fluctuations in the consumption–wealth ratio are strong predictors of both real stock returns and excess returns over a Treasury bill rate. We also find that this variable is a better forecaster of future returns at short and intermediate horizons than is the dividend yield, the dividend payout ratio, and several other popular forecasting variables. Why should the consumption–wealth ratio forecast asset returns? We show that a wide class of optimal models of consumer behavior imply that the log consumption–aggregate wealth (human capital plus asset holdings) ratio summarizes expected returns on aggregate wealth, or the market portfolio. Although this ratio is not observable, we provide assumptions under which its important predictive components for future asset returns may be expressed in terms of observable variables, namely in terms of consumption, asset holdings and labor income. The framework implies that these variables are cointegrated, and that deviations from this shared trend summarize agents' expectations of future returns on the market portfolio.     

The empirical risk–return relation: A factor analysis approach

Existing empirical literature on the risk–return relation uses relatively small amount of conditioning information to model the conditional mean and conditional volatility of excess stock market returns. We use dynamic factor analysis for large data sets, to summarize a large amount of economic information by few estimated factors, and find that three new factors—termed “volatility,” “risk premium,” and “real” factors—contain important information about one-quarter-ahead excess returns and volatility not contained in commonly used predictor variables. Our specifications predict 16–20% of the one-quarter-ahead variation in excess stock market returns, and exhibit stable and statistically significant out-of-sample forecasting power. We also find a positive conditional risk–return correlation.     

Risk‐Adjusted Long‐Term Contrarian Profits: Evidence from Non‐S&P 500 High‐Volume Stocks

Can trading volume help unravel the long‐term overreaction puzzle? With portfolios of non‐S&P 500 NYSE stocks, we show that (1) both the high‐ and low‐volume (abnormal volume) contrarian portfolios earn a much higher market‐adjusted excess return than the normal‐volume contrarian portfolio, (2) however, when leverage‐induced risk is factored in, excess returns from contrarian portfolios with normal‐ and low‐volume stocks are insignificant, (3) only excess returns from high‐volume contrarian stocks are significant and cannot be explained by the time‐varying risk and return framework, and (4) such high‐volume, risk‐adjusted excess returns arise mainly from winner (glamour) stocks.     

A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns

This study uses economic policy uncertainty (EPU) indices for ten developed countries, three diffusion models, and five combination methods to forecast excess returns in the U.S. stock market. It shows empirically that, over the period January 1997 to January 2022, non-U.S. EPU indices have better predictive power for U.S. equity market excess returns than the U.S. EPU index itself. This illustrates how economic information from international markets can affect the U.S. stock market. This finding challenges the extensively recognized view that the U.S. is where important market signals are initially transmitted to other markets, suggesting that this belief is incomplete. Our outcomes are robust to a battery of tests covering model selection, model specification, forecast horizons, and the pandemic period, and their economic values are assessed. The findings are essential for the financial field to confront future fierce situations and crises.     

The Other January Effect: Evidence against market efficiency?

The Other January Effect (OJE), which suggests positive (negative) equity market returns in January predict positive (negative) returns in the following 11 months of the year, underperforms a simple buy-and-hold strategy before and after risk-adjustment. Even the best modified OJE strategy, which benefits from several ex-post adjustments, does not generate statistically or economically significant excess returns. When the OJE is tested with a method that is consistent with investor experience it is clear the OJE is no more profitable than an 11-month strategy that uses November or December as the conditioning month.     

Average correlation and stock market returns

If the Roll critique is important, changes in the variance of the stock market may be only weakly related to changes in aggregate risk and subsequent stock market excess returns. However, since individual stock returns share a common sensitivity to true market return shocks, higher aggregate risk can be revealed by higher correlation between stocks. In addition, a change in stock market variance that leaves aggregate risk unchanged can have a zero or even negative effect on the stock market risk premium. We show that the average correlation between daily stock returns predicts subsequent quarterly stock market excess returns. We also show that changes in stock market risk holding average correlation constant can be interpreted as changes in the average variance of individual stocks. Such changes have a negative relation with future stock market excess returns.     

The Risk‐Return Relation in International Stock Markets

We investigate the risk‐return relation in international stock markets using realized variance constructed from MSCI (Morgan Stanley Capital International) daily stock price indices. In contrast with the capital asset pricing model, realized variance by itself provides negligible information about future excess stock market returns; however, we uncover a positive and significant risk‐return tradeoff in many countries after controlling for the (U.S.) consumption‐wealth ratio. U.S. realized variance is also significantly related to future international stock market returns; more importantly, it always subsumes the information content of its local counterparts. Our results indicate that stock market variance is an important determinant of the equity premium.     

Output and expected returns

This paper shows for 1929–2003 U.S. data and also for international G-7 data that the ratio of share prices to GDP tracks a large fraction of the variation over time in expected returns on the aggregate stock market, capturing more of that variation than do price–earnings and price–dividend ratios and often also providing additional information about excess returns. The price–output ratio tracks long-term U.S. cumulative stock returns almost as well as the cay-ratio of Lettau and Ludvigson [2001a. Journal of Finance 56, 815–849, 2005. Journal of Financial Economics 76, 583–626], although the cay-ratio tracks variation in U.S. excess returns better. The price–output ratio, however, involves no parameter estimation and is easily constructed for non-U.S. countries.     

Conditional Risk Premiums of Asian Real Estate Stocks

This paper uses a multi-factor latent variable model to examine the time variation of expected returns on Asian property stocks. Using data from 1990 to 1997, we found strong evidence of time-varying risk premium, suggesting property development based on constant discount rate may underestimate the cost of capital. A further study using a multi-country model suggests that conditional excess returns of many crisis-stricken economies appear to move quite closely with each other. This supports the hypothesis that the risk premiums in these Asian markets move closely over time As a result, they provide a partial explanation of market contagion in the region.     

On estimating the expected return on the market: An exploratory investigation

The expected market return is a number frequently required for the solution of many investment and corporate finance problems, but by comparison with other financial variables, there has been little research on estimating this expected return. Current practice for estimating the expected market return adds the historical average realized excess market returns to the current observed interest rate. While this model explicitly reflects the dependence of the market return on the interest rate, it fails to account for the effect of changes in the level of market risk. Three models of equilibrium expected market returns which reflect this dependence are analyzed in this paper. Estimation procedures which incorporate the prior restriction that equilibrium expected excess returns on the market must be positive are derived and applied to return data for the period 1926–1978. The principal conclusions from this exploratory investigation are: (1) in estimating models of the expected market return, the non-negativity restriction of the expected excess return should be explicity included as part of the specification: (2) estimators which use realized returns should be adjusted for heteroscedasticity.     

Options Trading and the CAPM

This article studies equilibrium asset pricing when agents facenonnegative wealth constraints. In the presence of these constraintsit is shown that options on the market portfolio are nonredundantsecurities and the economy's pricing kernel is a function ofboth the market portfolio and the nonredundant options. Thisimplies that the options should be useful for explaining riskyasset returns. To test the theory, a model is derived in whichthe expected excess return on any risky asset is linearly related(via a collection of betas) to the expected excess return onthe market portfolio and to the expected excess returns on thenonredundant options. The empirical results indicate that thereturns on traded index options are relevant for explainingthe returns on risky asset portfolios.     

MACROECONOMIC VARIABLES AND SEASONAL MEAN REVERSION IN STOCK RETURNS

In this paper I investigate whether seasonal mean reversion in stock portfolio returns is related to common macroeconomic risk factors. I decompose excess returns into explained and unexplained returns using a multifactor pricing model. The explained excess returns exhibit January mean reversion; the unexplained excess returns do not. The mean reversion can be attributed to the components of return related to unexpected inflation, bond default premium, and market risk. The results do not depend on the time-series properties of the portfolio betas. Bond default premia and excess market returns are mean reverting in January.     

Oil market uncertainty and excess returns on currency carry trade

This paper examines the role of oil market uncertainty on currency carry trade payoffs. We find that oil market uncertainty can impact currency carry trade excess returns. When oil market uncertainty rises, expected currency excess returns will increase. Our findings are robust to alternative measures of oil market uncertainty and, after controlling for traditional uncertainties, different types of oil shocks. The results also hold well in both developed and emerging markets, as well as for oil-related currencies, non-oil currencies, commodity currencies, and non-commodity currencies. Additionally, oil market uncertainty can be priced in the cross section of currency carry trade excess returns. This effect can be explained by investors becoming more risk averse under high oil market uncertainty and requiring greater compensation for bearing such risk. Moreover, our measure of oil market uncertainty, the downside risk from the oil market, is quite different from that of traditional aggregate measures.     

DUAL BETAS FROM BULL AND BEAR MARKETS: REVERSAL OF THE SIZE EFFECT

Significant firm-size-related differences in abnormal returns and systematic risks occur in bull and bear market months from 1926 to 1988. Potential differential return premiums between recessions and expansions appear to be captured by the varying risk model and not the constant risk model. Using a dual-beta market model to adjust for risk differences in bull and bear markets, we find that large firm stocks on average earn significant positive excess returns and small firm stocks earn significant negative excess returns. Superior performance of large firm stocks is even more pronounced outside January.     

Is There a Size Effect in the Pricing of Stocks in the Chinese Stock Markets?: The Case of Bull Versus Bear Markets

Size effect studies generally suggest that a return premium exists for small firms. While the size effect has mostly disappeared in recent years in mature markets (e.g., US and UK), it remains mostly strong in developing markets. The purpose of this paper is to examine the relationship between firm size and excess stock returns in the Chinese stock markets, and to examine this effect in both a bull and bear market. No studies have previously examined these relationships in the Chinese markets. The results of the study indicate that a size effect exists in the Chinese stock markets over the 6-year period from 1998 to 2003. We find small firms have significantly greater excess returns than large firms. Moreover, small firms are found to have a stronger reaction to the direction of the market than large firms. Small firms have significantly greater positive excess returns than large firms during the bull market. However, small firms have significantly greater negative returns (using total market value), or no significant difference in returns (using float market value) during the bear market period.