Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.     

Terrorism activities and long-term annual management forecasts

We study the effects of terrorist attacks on firms’ long-term annual management earnings forecasts bias. We find that the managers of firms located closer to the epicenters of attacks are more likely to issue optimistic long-term annual earnings forecasts relative to the managers of a control group of unaffected firms. The exposure effect is stronger for more severe terrorist events, and firms with more uncertain fundamentals and less geographic diversification. In addition, we document that managers’ forecast optimism intensifies for firms with stronger negative stock market reaction to the terrorist event, for CEOs with higher ability and for companies that are more likely to issue equity or engage in acquisitions following the terrorist event. Overall, our results are consistent with the idea that long-term annual earnings forecasts are used by managers to counterbalance the short-term pessimistic response to terrorist attacks.     

我国股改中权证的价格泡沫及影响因素

本文针对我国股改中的百慕大权证提出了新的“模拟树-市场情绪”定价模型。该模型的实证研究结果表明中国权证市场价格存在严重高估;加入市场情绪指标后,通过建立多元回归模型得到了对于实际价格的显著的拟合结果,有力地解释了超出权证理论价格的实际价格所包含的情绪因素。本文最后对权证价格高估的原因及权证未来的走势进行了分析。     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

"上证"A股市场情绪的关键影响因素

文章从投资者认知偏误视角,研究提出了"上证"A股市场情绪的四维量表,系统整合了18个关键影响因素,形成中国证券市场情绪的关键影响因素概念模型.采用"上证"A股市场中152家企业的调研数据,进行验证性因子分析和拟合优度检验.结果表明,12个理论因素按预期模式加载,形成了认知偏误、有限套利、交互传染和本土特性等四个维度,对认识中国证券投资者的决策行为具有一定指导意义.     

Individual stock sentiment beta and stock returns

Using the data in Chinese stock market, we measure the individual stock sentiment beta, which is defined as the sensitivity of individual stock returns to the individual stock sentiment changes. We demonstrate that stocks in the highest individual stock sentiment beta portfolio have significantly higher excess returns, CAPM alpha, Fama-French three-factor alpha and Fama-French five-factor alpha. Besides, we find that the high individual stock sentiment beta stocks are smaller, younger, more volatile stocks with higher price and higher market beta. After controlling for firm characteristic, the returns of High-Low individual stock sentiment beta portfolios are still significantly positive. Moreover, we show the effect of the individual stock sentiment beta on stock returns is positive and significant in different stock markets, in different sample periods, and in bull and bear market. Besides, the results of the Bayes-Stein individual stock sentiment beta are still stable.     

Risk sentiment and firms’ liquidity in the French market

This paper investigates the impact of risk sentiment on market liquidity by using panel data. We use six risk word lists; uncertain, weak model, negative, legal, opportunity, and environmental & social responsibility word lists to measure the risk sentiment. Concerning the liquidity proxies, we use three measures, quoted spread, effective spread, and adverse selection component. The results indicate that an intensive risk tone and uncertain information in annual reports lead to decreased liquidity. In addition we find that risk sentiment variable impacts the liquidity but not vice versa.     

Wealth effect and investor sentiment

This paper investigated the relationship between the U.S. stock and housing markets as well as their influence on the wealth effect of consumption and found that the stock market sentiment index can explain changes in the wealth effect. The empirical results indicate that these two markets exert a wealth effect on consumption. The estimation results of the Markov-switching model indicate two states: a state in which the stock market influences its coexistence with the housing market and a state in which the housing and stock markets are unrelated. Public optimism regarding stock market investments affects the probability of transitioning between these states.     

Assessing the reversal of investor sentiment

Assessing the reversal of sentiment in stock markets is needed because, according to the social mood cycle, the change of social mood over time is an antecedent of price movements. The purpose of this study is to empirically assess reversal of investor sentiment, to show the phases of social mood cycle from increasing mood to decreasing mood, and to explain the dynamic change in market inefficiency from increasing to decreasing. Growth modeling, developed particularly for dealing with the change over time, is used in this study for assessing the reversal of investor sentiment. The autocovariance structure of errors and the variances/covariances of the random coefficients are all taken into account in the model. The results have indicated that the change in investor sentiment over time is inverted U-shaped for the entire market. Moreover, arbitrage constraint and stock characteristics exert a joint moderating effect on sentiment reversal. Less arbitrage constraint can strengthen sentiment reversal only when the market for individual stocks is dominated by noise traders. Based on the results obtained, we discuss asset pricing, liquidity management, and market intervention.     

Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis

This paper investigates the portfolio optimization under investor’s sentiment states of Hidden Markov model and over a different time horizon during the period 2004–2016. To compare the efficient portfolios of the Islamic and the conventional stock indexes, we have employed two approaches: the Bayesian and Markowitz mean-variance. Our findings reveal that the Bayesian efficient frontier of Islamic and conventional stock portfolios is affected by the investor’s sentiment state and the time horizon. Our findings also indicate that the investor’s sentiment regimes change the Islamic and the conventional optimal diversified portfolios.Moreover, the results show that the potential diversification benefits seem to be more important when using the Bayesian approach than when applying the Markowitz approach. This finding is valid for the bearish, depressed, bullish and calm states in Islamic stock markets. However, the diversification of potential portfolios is significant only for the bullish and the bubble states in the conventional financial markets.The findings of the study provided additional evidence for investors to exploit googling investor sentiment states to evaluate the portfolio performance and make an optimal portfolio allocation.