Impact of investor sentiment on mutual fund risk taking and performance: evidence from China

ABSTRACT

This study provides empirical rationale and guidance for incorporating investor sentiment into mutual fund enterprise information systems. It investigates the effect of fund-specific investor sentiment on fund risk taking and performance. Working on a sample of equity funds in China, our panel regressions reveal that fund risk-taking is negatively related to lagged fund-specific investor sentiment. Investor sentiment is negatively linked to subsequent fund performance, which conforms with the dumb money effect. Encouragingly, there is evidence that mutual fund managers in China possess investing expertise. Fund-specific investor sentiment shows asymmetric impacts. The dumb money effect is primarily driven by positive sentiment.     

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.     

Diversification discount and investor sentiment

While previous research has linked the diversification discount to suboptimal managerial decisions, recent empirical work and methods have shown these relationships are not as strong. A rational learning framework indicates the diversification discount is related to economic activity. Building on this framework, we test and find support for the hypothesis that investor sentiment explains the diversification discount. Investor sentiment favors riskier firms when sentiment is high, thereby increasing returns and relative valuations. As a result, diversified firms imputed value based on these multiples leads to a larger diversification discount and reverses when sentiment falls.     

Geopolitical risks and investor sentiment: Causality and TVP-VAR analysis

This paper aims to explore the relationship between geopolitical risks (GPR) and investor sentiment in the US stock market based on Granger causality test and time-varying parameter vector autoregression (TVP-VAR) analysis. Empirical results indicate that changes in geopolitical risks can affect investor sentiment, whereas investor sentiment cannot affect geopolitical risks. More importantly, geopolitical risks have significant negative effects on investor sentiment, suggesting that higher (lower) geopolitical risks dampen (promote) investor sentiment directly or indirectly. Specifically, the negative effects of geopolitical risks show substantial time variation and generally decrease over time. The response of investor sentiment appears to be more pronounced in the short and medium term than in the long term, and is more sensitive to domestic geopolitical events. There is no significant difference in the impacts of geopolitical risks (GPR), geopolitical threats (GPT), and geopolitical acts (GPA). The results obtained are robust for alternative investor sentiment and geopolitical risk indicators.     

Overnight stock returns,intraday returns,and firm-specific investor sentiment

In this study, we propose a new index for measuring firm-specific investor sentiment using overnight and intraday stock returns. We use actual equity data to construct the firm-level investor sentiment index and find that the new index has characteristics expected of a sentiment measure. In addition, we propose a novel sentiment-weighted trading strategy and apply it to momentum and short-term reversal strategies. We find that the sentiment-weighted trading strategy generates better performance in momentum and short-term reversal strategies. The sentiment-weighted trading strategy’s superior performance is evidence that our firm-level investor sentiment index possesses predictive powers with regard to future returns.     

Business portfolio restructuring,prior diversification posture and investor reactions

This study examined firm performance in market reaction to two types of business portfolio restructuring announcements: refocusing and repositioning. We predicted that market performance effects for these two types of strategic restructurers would be moderated by prior diversification posture. The theory behind these expectations was built on a general premise that restructuring strategy would be more favorably viewed by the market as performance enhancing when it offered greater potential for organizational transformation. Results showed strong support for our conclusion that prior diversification posture poses a significant contingency factor in restructuring firms' strategic choices. Further, the market tended to respond more favorably with this sample to repositioning restructuring choices. Copyright © 2003 John Wiley & Sons, Ltd.     

Individual stock crowded trades,individual stock investor sentiment and excess returns

Recent behavioral asset pricing models and the popular press suggest that investors may follow similar strategies resulting in crowded equity positions to push prices further away from fundamentals. This paper develops a new approach to measure individual stock crowded trades, and further investigates the joint effects of individual stock crowded trades and individual stock investor sentiment on excess returns. Specifically, our results show that the combined effect of individual stock crowded trades and individual stock investor sentiment on excess returns is positive and significant, which reveals the importance of “anomaly factors” in asset pricing. Furthermore, our results suggest that increasing individual stock buyer-initiated crowded trades will increase excess returns simultaneously; however, increasing individual stock seller-initiated crowded trades will decrease excess returns simultaneously. Collectively, our results highlight the importance of individual stock crowded trades and individual stock investor sentiment on the formation of stock prices.     

Impact of network investor sentiment and news arrival on jumps

This paper studied the influence of news announcements and network investor sentiment on Chinese stock index and index futures market jumps. A machine learning text analysis algorithm was employed to measure investor forum sentiment. It was found that news arrivals were an important reason for jump occurrences, jumps were significantly associated with network investor sentiment, and while occasionally the news and network investor sentiment resulted in simultaneous market jumps, they appeared to be relatively independent. The network investor sentiment time-lag and asymmetric effects were also tested, from which it was found that network investor sentiment had a significant asymmetric effect on the jumps, but time-lag effects had little influence. News announcements and the top 25% of the extreme network sentiments were found to explain more than 50% of the jumps, with extreme sentiments tending to increase the volatility of the news-related jumps and persistently influencing returns after the news-related jumps.     

Excess co-movement of agricultural futures prices: Perspective from contagious investor sentiment

This study investigates the excess co-movement of agricultural futures prices from a new perspective of contagious investor sentiment. This study shows that contagious investor sentiment is a key determinant of excess co-movement of agricultural futures prices, by using contagious investor sentiment among different agricultural futures. Further, this study decomposes contagious investor sentiment into expected and unexpected contagious investor sentiment. Results show that both of them can positively affect excess co-movement of agricultural futures prices. More interestingly, expected contagious investor sentiment outperforms unexpected contagious investor sentiment in soybean 1 future, soymeal future, and strong wheat future. In general, the results of this study can provide strong support for the significant roles of contagious investor sentiment in asset pricing applications.     

The momentum and reversal effects of investor sentiment on stock prices

In this paper, we illustrate the real function relationship between the stock returns and change of investor sentiment based on the nonparametric regression model. The empirical results show that when the change of investor sentiment is moderate, the stock return is positively correlated with the change of investor sentiment, presenting an obvious momentum effect. However, the stock return is negatively correlated with the change of investor sentiment if the change of investor sentiment is dramatic, presenting significant reversal effects. Moreover, the degree of reversal effect caused by extremely optimistic sentiment is greater than that driven by extremely pessimistic sentiment, which shows a significant asymmetry. Our findings offer a partial explanation for financial anomalies such as the mean reversion of stock returns, the characteristic of slow rise and steep fall in China's stock market and so on.     

The COVID-19 pandemic uncertainty,investor sentiment,and global equity markets: Evidence from the time-frequency co-movements

We use daily data of the Google search engine volume index (GSVI) to capture the pandemic uncertainty and examine its effect on stock market activity (return, volatility, and illiquidity) of major world economies while controlling the effect of the Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index. We use a time–frequency based wavelet approach comprising wavelet coherence and phase difference for our empirical assessment. During the early spread of the COVID-19, our results suggest that pandemic uncertainty, and FEARS sentiment strongly co-move, and increased pandemic uncertainty leads to pessimistic investor sentiment. Furthermore, our partial wavelet analysis results indicate a synchronization relationship between pandemic uncertainty and stock market activities across G7 countries and the world market. Our results are robust to the inclusion of alternative pandemic fear measure in the form of equity market volatility infectious disease tracker. The pandemic uncertainty and associated sentiment implications could be one plausible reason for increased volatility and illiquidity in the market, and hence, policymakers should look upon this issue for the financial market stability perspective.     

Time-frequency transmission mechanism of EPU,investor sentiment and financial assets: A multiscale TVP-VAR connectedness analysis

This article examines the transmission mechanism of economic policy uncertainty (EPU), investor sentiment and Chinese financial assets from time-frequency and static-dynamic perspectives. The multiscale connectedness method based on time-varying parameter vector autoregression (TVP-VAR) is introduced to explore the time–frequency and static-dynamic spillovers. The empirical results are as follows: First, there is an interdependence between EPU and high-risk assets. Additionally, EPU and high-risk assets spillover risk to investor sentiment individually or in chains, ultimately affecting low-risk assets. Second, high-risk assets spill to low-risk assets in the short term but reverse in the long term. Third, EPU spills over to the system the most around 2008, especially in the long term. In addition, high-risk assets are the largest risk spillover and recipient at each frequency over the last decade. Overall, investors and regulators should consider real-time financial monitoring solutions in China based on economic policy uncertainty and investor sentiment factors.     

Market mispricings and portfolio allocation to mutual fund classes

Major factors affecting Greek household budget flows to mutual fund classes with different risk-return profiles are studied, applying the flexible functional form of the Almost Ideal Demand System to analyse allocation to equity, bond, balanced, and money market funds. An increase in household expenditure can have a positive impact; an adverse price change may erode budget benefits for a class. Volatility in possible “mispricings” in the underlying market valuation, with risk aversion attitudes, can result in asset reallocation. Cross-price effects provide insight on complementarity and substitutability between classes. Conclusions have useful policy implications for asset management and portfolio allocation strategies.     

Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search

We examine the ability of online ticker searches (e.g. XOM for Exxon Mobil) to forecast abnormal stock returns and trading volumes. Specifically, we argue that online ticker searches serve as a valid proxy for investor sentiment — a set of beliefs about cash flows and investment risks that are not necessarily justified by the facts at hand — which is generally associated with less sophisticated, retail investors. Based on prior research on investor sentiment, we expect online search intensity to forecast stock returns and trading volume, and also expect that highly volatile stocks, which are more difficult to arbitrage, will be more sensitive to search intensity than less volatile stocks. In a sample of S&P 500 firms over the period 2005-2008, we find that, over a weekly horizon, online search intensity reliably predicts abnormal stock returns and trading volumes, and that the sensitivity of returns to search intensity is positively related to the difficulty of a stock being arbitraged. More broadly, our study highlights the potential of employing online search data for other forecasting applications.     

Agency costs and audit quality: evidence from France

The IFRS mandatory adoption in European countries is an excellent context from which to assess the validity of accounting choice theory, which postulates that information asymmetry, contractual efficiency (agency costs) and managerial opportunism reasons could drive the choice. With this aim, we test the impact of these factors to explain the adoption of fair value for investment properties (IAS 40) in the real estate industry, taking into account the ‘revaluation’ option offered by IFRS1 and using historical cost without revaluations as a baseline category for comparison purposes. We select a sample of European real estate companies from Finland, France, Germany, Greece, Italy, Spain and Sweden, all first-time adopters of the IFRS. Using a multinomial logistic model, we show that information asymmetry, contractual efficiency and managerial opportunism could account for the fair value choice. Particularly, the most significant findings are that size as a proxy of political costs reduces the likelihood of using fair value while market-to-book ratio is negatively associated with the fair value choice. On the other hand, leverage, another typical proxy of contracting costs, seems not to influence the choice. This evidence confirms the current validity of traditional accounting choice theory even if it reveals, in such a context, the irrelevance of the usual relations between accounting choice and leverage.     

Predicting stock market crises using daily stock market valuation and investor sentiment indicators

The purpose of this paper is to develop a daily early warning system for stock market crises using daily stock market valuation and investor sentiment indicators. To achieve this goal, we use principal components analysis to propose a comprehensive index of daily market indicators that reflects stock market valuation and investor sentiment. Based on the comprehensive index, we employ a logit model with Ensemble Empirical Mode Decomposition to develop a daily early warning system for stock market crises. Finally, we apply the proposed system to the early warning for stock market crises in China. The in-sample forecasting results show that investor sentiment and the forecast horizon by Ensemble Empirical Mode Decomposition improve the forecasting performance of conventional early warning systems. The out-of-sample forecasting results indicate that the proposed warning system still has a good performance.     

Risk-neutral skewness and market returns: The role of institutional investor sentiment in the futures market

This paper investigates the effect of index risk-neutral skewness on subsequent market returns and explores whether this effect will vary with various types of institutional investor sentiment in the futures market. Using index futures returns as the proxy of market returns, the empirical results show that the index risk-neutral skewness has a significantly negative effect on subsequent index futures returns. Moreover, the effect of institutional investor sentiment on subsequent index futures returns varies with various types of institutional investor sentiment. Finally, the effect of index risk-neutral skewness on subsequent index futures returns relies on various types of institutional investor sentiment.     

The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.     

The fluctuation correlation between investor sentiment and stock index using VMD-LSTM: Evidence from China stock market

The impact of the investor sentiment on China’s capital market price volatility is concerned under the perspective of the behavioral finance. Firstly, in terms of the existing methods of establishing the investor sentiment index, the composite investor sentiment index which include six indicators (five objective indicators and a subjective indicator) are obtained. Secondly, VMD-LSTM (Variational Mode Decomposition and Long Short Term Memory) hybrid neural network model is used to decompose and restructure the investor sentiment index and the Shanghai Security Exchange Composite Index (SSEC) into the short-term, medium-term and long-term trend. Each trend is trained to obtain the forecasting results in three different time scales, and then to achieve the final predicting results by superimposing the output of each trend. Furthermore, compare with other prediction methods, the model can indeed improve the overall predicting accuracy. Finally, GARCH model and the co-integration error regression model are used to discuss the fluctuation correlation and VAR (Vector Auto-regression) models are established to analyze the causality between the stock market indices and the investor sentiment index.     

The impacts of investor sentiment on returns and conditional volatility of international stock markets

One of the main arguments of behavioral finance is that some properties of asset prices are most probably regarded as deviations from fundamental value and they are generated by the participation of traders who are not fully rational, thus called noise traders. Noise trader theory postulates that sentiment traders have greater impact during high-sentiment periods than during low-sentiment periods, and sentiment traders miscalculate the variance of returns undermining the mean-variance relation. The main objective of this research is to construct a model to evaluate the returns and conditional volatility of various stock market indexes considering the changes in the investor sentiment by measuring the effects of noise trader demand shocks on returns and volatility. EGARCH model is used to determine whether earning shocks have more influence on the conditional volatility in high sentiment periods weakening the mean–variance relation. This paper takes an international approach using weekly market index returns of U.S., Japan, Hong Kong, U.K., France, Germany, and Turkey. Weekly trading volumes of these indexes are regressed against a group of macroeconomic variables and the residuals are used as proxies for investor sentiment and significant evidence is found that there is asymmetric volatility in these market indexes and earning shocks have more influence on conditional volatility when the sentiment is high.