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Prior research has documented the role of information uncertainty in the cross-sectional variation in stock returns. Miller (1977) hypothesizes that if information uncertainty is caused by differences of opinion, prices will reflect only the positive beliefs due to short-sale constraints. These anomalous stock price behaviors may result from mispricing. In contrast, Merton (1974) asserts that default risk is a function of the uncertainty in the asset value process. Information uncertainty may be subsumed by credit or default risk. The paper aims to discuss these issues.

The authors employ various sorting techniques and Fama-MacBeth Regressions to test the hypotheses.

The authors provide empirical evidence consistent with Merton’s (1974) default risk hypothesis and inconsistent with Miller’s (1977) mispricing hypothesis.

Risk aversion and not misplacing is the primary factor driving information-related anomalies in equities markets.

It would be quite difficult to find arbitrage opportunities in equities markets because there appears to be little, if any, mis-pricing due to information uncertainties.

This study provides important information about the primary underlying information-related source of certain empirical anomalies in the cross-section of stock returns.

The purpose of this paper is to examine the investment behavior of Pakistani stock market participants, specifically with respect to their tendency to exhibit herd behavior.

The study employed two different methodologies suggested by Christie and Huang (1995) and Chang et al. (2000) to test herd formation. Results are based on daily and monthly stock of KSE-100 index for the period 2002-2007.

Results based on daily and monthly stock data from Karachi Stock Exchange indicate the non-existence of herd behavior for the period 2002-2007 and find no support for the rational asset pricing model and investor behavior found inefficient. This study denied proved evidence of herding due to market return asymmetry, high and low trading volume states and asymmetric market volatility. Macroeconomic fundamentals have insignificant role in decision-making process of investor therefore has no impact on herding behavior. However, during liquidity crisis of March 2005, Pakistani stock market exhibit herding behavior due to asymmetry of information among investors, presence of speculator and questionable badla financing-local leverage financing mechanism.

In future, this study can be improved by employing stock returns portfolios based on market capitalization or sector wise portfolio returns from KSE-100. Furthermore by identifying those factors that cause market to be overall inefficient and define the pattern of the investor trading activities.

For an accurate valuation of assets investors should incorporate the herding factor.

As the assets are mispriced, investor behavior is uncertain and markets are inefficient, foreign investors should invest with caution, as large numbers of securities are needed to achieve the same level of diversification than in an otherwise normal market.

In Karachi Stock Exchange, it is first attempt to uncover the herding behavior. This paper contribute to the body of knowledge by investigating the herding behavior in the emerging markets since most of the previous study concentrate more on the developed markets. Furthermore, the study also analyzed the herding behavior in different economic condition and includes economic variables and examines asymmetric effect. This study presents an integrated model to test herding behavior in Pakistani equity market. Consideration of said behavioral effect in the decision-making process of investor will make the decisions more rational and optimal.

This study examines several aspects of active portfolio management by equity hedge funds between 1996 and 2013. Consistent with the idea that cross-sectional return dispersion is a proxy for the market’s available alpha, our results show that equity hedge funds achieve their strongest performance during periods of elevated dispersion. The performance advantage is robust to numerous risk adjustments. Portfolio managers may use the current month’s dispersion to plan the extent to which the following month’s investment approach will be active or passive. We also estimate the active share for equity hedge funds and find an average of 53%. We further document the average annual expense ratio for managing hedge funds’ active share to be about 7%. This figure is remarkably close to active expense ratios reported previously for equity mutual funds, which may be interpreted as evidence of uniform pricing for active portfolio management services.

The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.

This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.

At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.

The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.

Financial analysts have been found to be overconfident. The purpose of this paper is to study the ramifications of that overconfidence on the dispersion of earnings estimates as a predictor of the US business cycle.

Whether aggregate analyst forecast dispersion contains information about turning points in business cycles, especially downturns, is examined by utilizing the analyst earnings forecast dispersion metric. The primary analysis derives from logit regression and Markov switching models. The analysis controls for sentiment (consumer confidence), output (industrial production), and financial indicators (stock returns and turnover). Analyst data come from Institutional Brokers Estimate System, while the economic data are available at the Federal Reserve Bank of St Louis Economic Data site.

A rise in the dispersion of analyst forecasts is a significant predictor of turning points in the US business cycle. Financial analyst uncertainty of earnings estimate contains crucial information about the risks of US business cycle turning points. The results are consistent with some analysts becoming overconfident during the expansion period and misjudging the precision of their information, thus over or under weighting various sources of information. This causes the disagreement among analysts measured as dispersion.

This is the first study to show that analyst forecast dispersion contributions valuable information to predictions of economic downturns. In addition, that dispersion can be attributed to analyst overconfidence.

To test the Miller Price Optimism Model using a new proxy for heterogenous expectations and to examine if high differential stocks behave like glamour stocks and low differential stocks behave like value stocks.

Whisper/analyst forecast differentials were measured for a sample of stocks, combined into portfolios and held for one month. If the Miller model was supported, high differential stocks were expected to have lower portfolio returns than low differential stocks due to the greater divergence between optimistic whisper forecasts and rational analysts consensus forecasts.

High differential quintiles had significantly lower future returns than low differential quintiles supporting the Miller model. High differential stocks resembled glamour stocks while low differential stocks behaved like value stocks.

These results pertain to the ultra‐short time horizon of two months prior to the earnings announcement. Future research should replicate this study for a longer 3‐12 month time horizon.

Ultra short‐term investors should hold glamour stocks and long term investors should hold value stocks. Rising volatility suggests that investors should define the time horizon for holding assets.

It is one of only two studies that directly uses earnings forecasts as a proxy for heterogenous expectations. It adds to the sparse literature on whisper forecasts. It may be used by academicians studying price optimism effects and institutional investors following stock returns during earnings announcements.

The purpose of this paper is to answer a fundamental question – are individual stock picks by a particular internet investment community informative enough to beat the market? The author observes that the stock picks by the CAPS community are reflective of existing information and portfolios based upon CAPS community stock rankings do not generate abnormal returns. The CAPS community is good at tracking existing performance but, it lacks predictive ability.

The study uses a unique data set of stock ratings from Motley Fools CAPS community to determine the information content embedded in these ratings. Observing predictive ability of this web-based stock ratings forum will raise questions about the efficiency of the financial markets. The author forms stock portfolios based on stocks’ star ratings, and star rating changes, and test if the long-short portfolio strategy generates significant α after controlling for single, and multi-factor asset pricing models, such as Fama-French three-factor model and Carhart four-factor model.

The paper finds no evidence that the CAPS community ratings contain “information content,” which can be exploited to generate abnormal returns. CAPS community ratings are good at tracking existing stock performance, but cannot be used to make superior forecasts to generate abnormal returns. The findings are consistent with the efficient market hypothesis. Furthermore, the author provides evidence that CAPS community ratings are themselves determined by stock performance rather than the other way around.

The study employs a unique data set capturing the stock ratings of a very popular web-based investment community to evaluate its ability to make better than random forecasts. Besides applying well-accepted asset pricing models to generate α, the study conducts causality tests to discern a causal relation between stock ratings and stock performance.

The purpose of this paper is to identify the effective measures for heterogeneity and to uncover the relationship between investor heterogeneity and stock returns.

The paper employs dispersion in analysts’ earnings forecasts and unexpected trading volume as proxies of heterogeneity. Portfolio strategies and Fama-Macbeth regression are used to uncover the relationship between the two proxies and stock returns in the Chinese A-share market.

The result indicates that stock returns are significantly related to unexpected trading volume, i.e., higher unexpected trading volume implies higher stock returns now but lower future stock returns. In contrast, there is no statistically significant relationship between analysts’ forecast dispersion and stock returns.

The findings suggest that unexplained trading volume is an effective measure for investor heterogeneity in the Chinese A-share market.

This study aims to analyze the herding behavior in Southeast Asian stock markets. A cross-sectional absolute deviation of the returns approach is used to identify the presence of herding. Individual stocks and market returns were employed on each stock market on a daily basis during the period of January 2008 to December 2014 from five countries selected to obtain the necessary data. The samples observed consisted of stocks having higher liquidity and larger market capitalization for each stock market. The results suggest that there is significant evidence of herding behavior found in Kuala Lumpur and Philippines Stock Exchanges. In addition, there is no evidence of herding behavior in Indonesia, Singapore, and Thailand Stock Exchanges.

This paper aims to examine the Chinese investment anomaly and dissect it from a perspective of rational expectation framework.

Characteristic-based sorting and Fama–MacBeth two-stage cross-sectional regression are adopted to test the relationship between corporate investment and expected returns in both portfolio and individual stock levels. Under the framework of pricing kernels, an investment-based common risk factor is constructed to test the role of risk played in the negative investment-return relationship. Moreover, a Markov regime switching model is adopted to investigate the time-varying risk premium across market regimes.

Empirical results provide ample evidence showing that there is a negative relationship between investment and expected returns in the Chinese stock market. The new investment-based risk factor is found to capture the return differences across characteristic-based portfolios. In addition, risk premium of the new risk factor is not only statistically positive throughout the sample period, but also has an asymmetry that is higher during market downturn but lower under bull market.

This paper merely tests the hypotheses derived from rational school.

Investment strategies based on characteristic-sorted portfolios should be adjusted to different market regimes.

First, this paper provides comprehensive empirical results by adopting different methodologies for investigating the investment anomaly in China. Second, an investment-based factor is constructed specifically for the Chinese stock market for the first time. Finally, this is the first paper to investigate the asymmetric risk premium across the Chinese bear and bull regimes by using a multivariate Markov regime switching model.