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.     

Predicting bear and bull stock markets with dynamic binary time series models

Despite the voluminous empirical research on the potential predictability of stock returns, much less attention has been paid to the predictability of bear and bull stock markets. In this study, the aim is to predict U.S. bear and bull stock markets with dynamic binary time series models. Based on the analysis of the monthly U.S. data set, bear and bull markets are predictable in and out of sample. In particular, substantial additional predictive power can be obtained by allowing for a dynamic structure in the binary response model. Probability forecasts of the state of the stock market can also be utilized to obtain optimal asset allocation decisions between stocks and bonds. It turns out that the dynamic probit models yield much higher portfolio returns than the buy-and-hold trading strategy in a small-scale market timing experiment.     

Dividend Yields and Stock Returns: Evidence of Time Variation between Bull and Bear Markets

This study documents persistent shifts in the relationship between stock returns and dividend yields over bull and bear markets. The shift in this relationship appears as a separate effect, distinct from the January effect, and after controlling for firm size and systematic risk. After controlling for these other factors, dividend yield is positively related to return during bear markets but negatively related to return during bull markets. This time-varying relationship between dividend yield and stock return helps to explain the anomalous results of earlier studies.     

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.     

Identifying Bull and Bear Markets in Japan

This study investigates the returns and volatility of bull and bear markets as represented by the Tokyo Stock Price Index (TOPIX). Our results show that bull markets are characterized by high returns and low volatility and that the opposite is true for bear markets. Further, this study uncovers a relationship between the duration of bull and bear markets and the point at which the TOPIX has turned from bull to bear and vice versa. Our results indicate that a bull or bear market has a higher probability of continuing as the duration of market’s current trend lengthens. If a bull or bear market trend persists for more than nine months, its probability of continuing approaches 1. Conversely, the transition from a rising to a declining market, and vice versa, is more likely to occur when the previous trend has persisted for less than nine months.     

Market States and the Effect on Equity REIT Returns due to Changes in Monetary Policy Stance

This study investigates the effect of changes in monetary policy on US equity real estate investment trust (EREIT) returns in lower and higher return ranges during bull, bear, and volatile stock market states using quantile regression. Results show that EREIT returns are sensitive to changes in monetary policy at different EREIT return ranges in different market states. During bull markets, changes in monetary policy have a significant negative impact on EREIT when investors have lower expectations of real estate price increases, but are not effective when investors have higher expectations of real estate price increases. During volatile and bear markets, EREIT returns are not sensitive to changes in monetary policy stance. Results also show that EREIT returns respond positively to stock returns in various states and conditions.     

Liquidity Provision of Limit Order Trading in the Futures Market Under Bull and Bear Markets

Abstract:  This study investigates how limit orders affect liquidity in a purely order-driven futures market. Additionally, the possible asymmetric relationship between market depth and transitory volatility in bull and bear markets and the effect of institutional trading on liquidity provision behavior are examined as well. The empirical results demonstrate that subsequent market depth increases as transient volatility increases in bull markets. Market depth exhibits significantly positive relationship to subsequent transient volatility in bull markets. Additionally, although trading volume positively influences transient volatility in bull markets, no such relationship exists in bear markets. Liquidity provision decreases when institutional trading activity intensifies during bear markets. Thus, liquidity provision for limit orders differs between bull and bear markets.     

Are the gains from international portfolio diversification exaggerated? The influence of downside risk in bear markets

The fundamental rationale for international portfolio diversification is that it expands the opportunities for gains from portfolio diversification beyond those that are available through domestic securities. However, if international stock market correlations are higher than normal in bear markets, then international diversification will fail to yield the promised gains just when they are needed most. We evaluate the extent to which observed correlations to monthly returns in bear, calm and bull markets are captured by three popular bivariate distributions: (1) the normal, (2) the restricted GARCH(1,1) of J. P. Morgan’s RiskMetrics, and (3) the Student-t with four degrees of freedom. Observed correlations during calm and bull markets are unexceptional compared to these models. In contrast, observed correlations during bear markets are significantly higher than predicted. Higher-than-normal correlations during extreme market downturns result in monthly returns to equal-weighted portfolios of domestic and international stocks that are, on average, more than two percent lower than those predicted by the normal distribution. If the extent of non-normality during bear markets persists over time, then a US investor allocating assets into foreign markets might want to allocate more assets into foreign markets with near-normal correlation profiles and avoid markets with higher-than-normal bear market co-movements.     

An Examination of Cross-Sectional Realized Stock Returns using a Varying-Risk Beta Model

Using the dual-beta model of Bhardwaj and Brooks (1993), this study examines the cross-section of realized stock returns. Bull-market betas are significantly positively related to returns and, except for some models in January, bear-market betas are significantly negatively related to returns. These relationships are not lost even after other independent variables, including size, book-to-market equity, and an earnings-price ratio, are added to the cross-sectional regressions. Book-to-market equity is an important factor in bear, but not bull, markets. Size is important in January and in bear markets during February through December.     

Rumor Clarification and Stock Returns: Do Bull Markets Behave Differently from Bear Markets?

This paper analyzes the effects of official rumor clarification on Chinese stock returns under different market conditions. The results show that the average cumulative abnormal return after the clarification event is significantly positive in a bull market, and significantly negative in a bear market. The results are robust across various types of rumors, including rumors of mergers and acquisitions, asset restructuring, and positive changes in a firm's operations. Moreover, in both bull and bear markets, investors are unable to distinguish between rumors that prove true and those that prove false, or between strong and weak rumor denial. Furthermore, investors are also unable to adjust their strategies accordingly.     

Forecasting Bull and Bear Markets: Evidence from China

This article extends previous empirical research to forecast Chinese bull and bear stock markets by using three types of binary probit time series models, which are static, autoregressive, and dynamic autoregressive models. This study shows that the dynamic auto regressive model performs the best both in- and out-of-sample. The inflation and market return variables significantly affect the market forecast. The dynamic autoregressive model has successfully forecast the bull and bear markets since 2007. The investment strategy based on this model performs better than the simple buy-and-hold strategy, especially after the Chinese government reformed the non-tradable shares in 2005.     

Monetary policy and stock returns: Financing constraints and asymmetries in bull and bear markets

We examine asymmetries in the impact of monetary policy surprises on stock returns between bull and bear markets in the period 1994 to 2005. We ask how these impacts respond to the relative ability of firms to obtain external finance. We find that the impact of a surprise monetary policy in a bear market is large, negative, and statistically significant, and this holds across size decile portfolios. The impact of a surprise policy action in a bear market for most industries is significantly greater than the impact of surprise monetary policy in a bull market. Controlling for the capacity for external finance, stock returns of firms in bear states respond more than firms in bull states. Capacity for external finance is more important in a bear market, as it partially mitigates the larger impact of monetary policy in a bear market.     

The wandering weekday effect in major stock markets

This paper reports a wandering weekday effect: the pattern of day seasonality in stock market returns is not fixed, as assumed in the Monday or weekend effects, but changes over time. Analysing daily closing prices in eleven major stock markets during 1993–2007, our results show that the wandering weekday is not conditional on average returns in the previous week (the “twist” in the Monday effect). Nor does it diminish through the period of analysis. The results have important implications for market efficiency, and help to reconcile mixed findings in previous studies, including the reported disappearance of the weekday effect in recent years.     

PORTFOLIO MANAGEMENT: THE ROLE OF CALIBRATION,SHARPNESS, AND UNCERTAINTY

I evaluate the out‐of‐sample predictability of several major indicators for bull and bear markets in monthly S&P 500 series with three quadratic probability score components: calibration, sharpness, and uncertainty. I find that uncertainty limits the trend characterization and thus provides a new perspective from which to identify bull and bear markets. I also find that sharpness plays a key role in determining portfolio returns. Trading strategies that capitalize on sharpness generate higher Sharpe ratios and portfolio returns. The Aruoba–Diebold–Scotti business conditions index is the most profitable indicator for both medium‐ and long‐term trends.     

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.     

How loss averse are investors in financial markets?

We investigate loss aversion in financial markets using a typical asset allocation problem. Our theoretical and empirical results show that investors in financial markets are more loss averse than assumed in the literature. Moreover, loss aversion changes depending on market conditions; investors become far more loss averse during bull markets than during bear markets, indicating their more profound disutility for losses when others enjoy gains. Contrary to most previous results, we find that investors are more sensitive to changes in losses than changes in gains.     

The efficiency of the buy-write strategy: Evidence from Australia

We examine the performance of the buy-write option strategy (BWS) on the Australian Stock Exchange and analyse whether such an investment opportunity violates the efficient market hypothesis on the basis of its risk and returns. This study investigates the relationship between buy-write portfolios returns and past trading volume and other fundamental financial factors including dividend yield, firm size, book to market ratio, earnings per share (EPS), price earnings ratio and value stocks within these portfolios. We also test the profitability of the buy-write strategy during bull and bear markets. Consistent with the literature, it is observed that BWS offers superior risk adjusted returns for low levels of out-of-moneyness and contrary evidence is observed for deeper out-of-money portfolios. Consistent with a preference for options with a maturity of around 3 months in Australia, this research shows that quarterly rebalancing periods offer better returns for the BWS.     

Day-of-the-week and intraday effects in stock returns

This study examines day-of-the-week effects using hourly values of the Dow Jones Industrial Average. We find that over the 1963–1983 period the weekend effect has sifted from characterizing active trading on Monday to characterizing the non-trading weekend. Over the early part of our sample period negative returns characterize each hour of trading on Monday, while the return from Friday close to Monday open is positive. In the most recent subperiod, Monday average hourly returns after noon are all positive and the weekend effect is due to negative average returns from Friday close to Monday open.     

Lack of consumer confidence and stock returns

This paper investigates the link between the lack of consumer confidence and stock returns during market fluctuations. Using a Markov-switching framework, we first focus on whether the shock to consumer confidence has asymmetric effects on stock returns. We also examine whether the decreased confidence pushes the stock market into bear territory. Empirical evidence using monthly returns on Standard & Poor's S&P 500 price index suggests that market pessimism has larger impacts on stock returns during bear markets. Moreover, the lack of consumer confidence leads to a higher probability of switching to a bear market regime.     

On the characteristics and performance of long-short, market-neutral and bear mutual funds

We evaluate the return performance of long-short, market-neutral and bear mutual funds using multi-factor models and a conditional CAPM that allows for time-varying risk. Differences in the bearish posture of these mutual funds result in different performance characteristics. Returns to long-short mutual funds vary with the market, returns to market-neutral mutual funds are uncorrelated with the market and returns to bear mutual funds are negatively correlated. Using the conditional CAPM we document significant changes in the market-risk exposure of the most bearish of these funds during different economic climates. We then assess the flow-performance relationship for up to 60 months following up and down markets and find that investors direct flows towards market-neutral and bearish funds for several months after down markets. Market-neutral funds provide a down market hedge, but bear funds do not generate the returns that investors hope for.