Individual Investor Sentiment Research Articles

Sentiment and Stock Characteristics: Comprehensive Study of Individual Investor Influence on Returns, Volatility, and Trading Volumes

Abstract Background Traditional asset pricing models face challenges from financial anomalies, prompting exploration through behavioural finance theory. This study analyses the nuanced relationship between individual investor sentiment and key stock market variables. Objectives To assess the impact of individual investor sentiment on stock returns, volatilities, and trading volumes using the American Association of Individual Investors (AAII) sentiment index. Methods/Approach Using regression models, we examine the relationship between individual investor sentiment and various stock characteristics across 480 components of the Standard & Poor's 500 index. Results We find a positive relationship between the AAII sentiment index and stock returns and a negative relationship with volatility and trading volume. Conclusions Our study contributes to understanding the intricate role of individual investor sentiment in financial markets.

Higher order expectations, learning, and sentiment pricing dynamics

We present a dynamic asset pricing model combining individual investor sentiment, higher order expectations with learning. In the basic model, the forward-looking expectation of individual investors is distorted by individual sentiment and higher order expectations, so prices react more sluggishly to changes in fundamentals of the asset. We find that investor sentiment plays a significant role in the effect of higher order expectations on asset pricing. Investor sentiment not only makes the price tightly anchor to the initial price, but also increases the sentiment drift of the price. Higher order expectations exhibit inertia, therefore aggravating the anchor to the initial price. With the increase of the order, more and more investor sentiment is integrated into the prices, amplifying the bias of pubic signal relative to fundamentals. When individual sentiment investors learn valuable public information through price system in the long term, the information component of the equilibrium price increases, thus drawing the asset price back toward the rational expected value. The model could offer a partial explanation to the inertia and drift in the price path

Coal price shocks, investor sentiment, and stock market returns

The development of energy finance and the financialization of bulk commodities has deepened the financial attributes of coal, resulting in coal price shocks not only affecting the macroeconomy through the production sector, but also further affecting the financial market. This study investigates the dynamic impacts of coal price shocks on stock market returns accounting for the macroeconomic path by using a time-varying parameter vector autoregressive with stochastic volatility (TVP-SV-VAR) model, as well as examines the role of investor sentiment in the transmission of coal price shocks to the stock market. The results show that coal price shocks have a significant negative impact on Chinese stock market returns, but the impact degree is time-varying, particularly larger during economic downturns. Moreover, individual investor sentiment provides an important channel in the transmission of coal price shocks to the stock market. Insights gleaned from the findings in this study are useful for coal industry regulation policy formulation, market investment decision-making and energy market risk management.

What drives closed‐end fund discounts? Evidence from COVID‐19

AbstractThis paper investigates the impact of the onset of the COVID‐19 pandemic in the United States on closed‐end fund (CEF) discounts. I show that CEF discounts increased after the onset of the COVID‐19 pandemic in the United States, while individual investor sentiment declined. Furthermore, CEFs with higher retail ownership had a larger discount increase, which suggests that individual investor sentiment is a potential contributor to CEF discounts. This finding seems less likely to be driven by rational channels or income‐driven fire sales, as shown by further analysis. Overall, the results shed light on the CEF discount puzzle using a new setting.

The Influence of Capital Market Openness on the Sentiment of Chinese Investors

In recent years, China has been gradually and progressively promoting the opening of its capital markets to the outside world. In this study, a questionnaire survey and SEM (Structural Equation Modeling) model analysis were used to investigate the mechanisms and outcomes of capital market openness on Chinese investor sentiment based on the Land-Hong Kong Link Policy.The study reveals that following the opening of the capital markets, individual investor sentiment tends to become more rational due to factors such as changes in investor structure and shifts in value investment concepts. In the future, it is recommended that China's capital markets promote basic investment education and enhance the development of financial regulations to progress towards a deeper level of openness.

Sensitivity of Chinese stock markets to individual investor sentiment: An analysis of Sina Weibo mood related to COVID-19

This research explores the impact of individual investor sentiment derived from social networks on stock market returns. Using keyword-based techniques, we collect and analyze Sina Weibo posts related to COVID-19, extracting daily influential weighted sentiment indexes from a dataset of over 2.4 million posts in 2020. Empirical tests utilizing a sentiment-augmented three-factor model reveal that individual investor sentiment exerts an independent influence on Chinese financial markets, after controlling for market risk, size, and value effects. We further find that negative sentiment carries a stronger impact on stock returns, which is in line with the loss-averse behavior commonly observed among individual investors. We also find an asymmetric pattern in the sentiment-return relation across different industry types. While positive sentiment affects both types of industries that suffer or benefit from COVID-19, negative sentiment affects only the industries that suffer from the pandemic. Overall, our empirical results provide robust support for the significance of individual investor sentiment in explaining the behavior of the Chinese financial markets.

Differences between NZ and U.S. individual investor sentiment: more noise or more information?

In this study, we introduce a newly created sentiment index of individual investors in NZ constructed similar to the well-known sentiment index provided by the American Association of Individual Investors (AAII) in the U.S. This unique setup allows us to compare different aspects of investors’ behaviour in both countries. We show that NZ market participants are less confident about the directional movement of the stock market, their expectations are more volatile and their distributions have fatter tails. By contrast, both bullish and bearish sentiment is more persistent among U.S. investors. Furthermore, our analysis of return predictability reveals that both groups of investors behave as noise traders. However, the results for NZ investors are stronger. Overall, our findings call for better financial education, particularly in the area of equity investing.

The impact of the COVID-19 pandemic on motivating factors affecting individual investors’ socially responsible investment decision: a comparative analysis of the USA, Germany and Japan

PurposeIndividual investors are experiencing serious sentiment shifts that influence their financial activities due to the COVID-19 pandemic while socially responsible investment (SRI) has garnered attention worldwide. This study aims to explore how individual investors’ sentiments and investment choices altered in reaction to the COVID-19 pandemic.Design/methodology/approachWe surveyed 1,219 individual investors in Japan, the USA and Germany using an online questionnaire and performed a cross-sectional analysis using logit and ordered logit regressions.FindingsThis study found that individual investor sentiment affects SRI after COVID-19, but not necessarily in the same manner. Return-focused aspects negatively affect their SRI, while relationship-oriented social issues positively affect it. In addition, the relationship differs by nation. Japanese investors anticipate shorter term SRI returns than the US and German investors. Only Japanese investors’ SRI decisions were impacted by the relationship-oriented social factors including the environment, diversity and employee rights and welfare.Research limitations/implicationsThis study emphasizes the need for precise motivation characterization when evaluating the same issue. The author also identified the variance and characteristics among countries, which differ from previous research.Practical implicationsAn academically credible image of the relationship will enable business managers to find appealing strategies. This study also suggests country-specific investor relations strategies.Originality/valueThis study differentiates return- and relationship-oriented social motivations for SRI into 14 components, thus clarifying the relationship mechanism between the COVID-19 pandemic and individual investors’ SRI behavior. Moreover, no study has compared individual investor sentiment and investment behavior affected by the pandemic in the three countries.

Sensitivity of Chinese Stock Markets to Individual Investor Sentiment: An Analysis of Sina Weibo Mood Related to COVID-19

Sensitivity of Chinese Stock Markets to Individual Investor Sentiment: An Analysis of Sina Weibo Mood Related to COVID-19

BEHAVIOR OF FINANCIAL MARKETS AROUND NEWS ANNOUNCEMENTS: A REVIEW BASED ON BIBLIOMETRIC ANALYSIS OF SCIENTIFIC FIELDS

This study analyses existing literature about investor behavior around news an- nouncements. We use bibliometric analysis to explore the evolution and development in this theme. We analyze 815 research articles collected from Scopus database from 1992 to 2021 through bibliometric measurements and social networks using Vosviewer. We Önd that the number of studies examining investor behavior in response to news announcements has been steadily increasing over time, particularly since 2008. Further, the study highlighted ináuential authors, countries, institutions, impactful journals, and top articles in this theme. To identify the research gap to propose agenda for future research, the study conducted clustering and factor analysis of main studies and themes in this literature. Majority of the studies has focused on the impact of news announcements on stock market and individual investor sentiment, particularly herd behavior of investors. Even though many researchers tried to investigate di§erent aspects of investor behavior around corporate and macroeco- nomic news announcements, to the best of our knowledge, no studies have been conducted to evaluate the performance and trends in this theme. This study signiÖcantly contributes to the Önancial literature dedicated to news announcements by analyzing the trend and pattern of publication in this theme and helping researchers and other participants in the Önancial market to get insight in this theme and to conduct future studies

An Analysis of the U.S. Individual Investor Sentiment Influence on Cryptocurrency Returns and Volatility

In this research, the U.S. investor sentiment effect on cryptocurrency returns and volatility is examined by separating it into irrational and rational parts. According to the data, an unforeseen rise in the rational part of U.S. individual investor attitude influences cryptocurrency returns statistically and positively. In other words, rational sentiment can result in rising cryptocurrency returns. Additionally, a positive significant association exists between cryptocurrency volatility and the rational part of the individual U.S. investor sentiment. The findings confirm the hypothesis that the behavior of rational investors who utilize and study the impact of economic factors on asset prices reduces cryptocurrency volatility.

Stock index direction forecasting using an explainable eXtreme Gradient Boosting and investor sentiments

In this article, an explainable eXtreme Gradient Boosting (XGBoost) method is proposed for stock index prediction and trading simulation in the Chinese security market. Sentiment features of three types of investors, including institutional, individual, and foreign investors, are utilized as explanatory variables, and a binary classification model based on XGBoost is constructed to predict the direction of the Shanghai composite index and Shenzhen composite index movements. Additionally, the Gain function of XGBoost and SHapley Additive exPlanations (SHAP) are employed to estimate the importance of sentimental factors affecting index direction forecasting. Experimental results demonstrate that the XGBoost-based approach using multiple investor sentiments achieved the best forecasting accuracy, and sentiment features of the institutional investor were relatively more essential than the individual investor and foreign investor sentiments for index direction prediction in most out-of-sample periods. It demonstrates that the method proposed in this research can provide useful references for market participants to support their investment in the Chinese security market.

Oil sentiment and the U.S. inflation premium

In this paper, we employ a new dataset to measure the impact of investor sentiment regarding oil prices on the U.S. inflation premium. Our empirical analysis relies on Structural Vector Autoregression (SVAR) and out-of-sample forecasts. The results indicate that a one standard deviation positive shock to overall investor sentiment regarding oil prices results in a significant increase in the U.S. inflation premium by approximately 1.2% over the subsequent 10 weeks. Compared to individual investor sentiment, institutional investor sentiment regarding oil prices has a larger impact on the U.S. inflation premium. Finally, we find an out-of-sample evidence that the overall investor sentiment regarding oil prices has predictive power on the U.S. inflation premium.

Asymmetric impacts of individual investor sentiment on the time-varying risk-return relation in stock market

This study investigates the impacts of investor sentiments, including individual sentiment and market-wide sentiments, on time-varying risk-return tradeoffs in the U.S. stock market using quantile regressions. Empirical results show that the individual sentiment has a significant negative effect on the time-varying risk-return tradeoff across all quantiles, indicating the heterogeneity of the individual sentiment effect. Specifically, the positive individual sentiment weakens the time-varying risk-return tradeoff while the negative individual sentiment enhances it. Besides, there are asymmetric effects of the individual sentiment at quantiles (0.25, 0.75), that is, a negative individual sentiment associated with bad news has a stronger impact than a positive individual sentiment associated with good news. These findings are robust for alternative estimate methods and individual sentiments. However, the study finds that the time-varying risk-return tradeoff is less sensitive to the market-wide sentiment than to the individual sentiment, indicating that the individual sentiment is more useful and important in determining the stock price and variation.

Artificial intelligence in financial services: a qualitative research to discover robo-advisory services

PurposeThe purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms.Design/methodology/approachThis is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes.FindingsFactors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors.Research limitations/implicationsDue to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market.Practical implicationsThis study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner.Social implicationsIn the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems.Originality/valueThis study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

Bitcoin Sentiment Index and Stock Market Return

The returns predictions and price movements of financial markets are predicted through online search engines. These search engines claim to trade sentiments of individual investors. This study aims to determine the changes in the American stock market returns due to Bitcoin investors’ sentiments. The Bitcoin sentiment index is constructed and used as a benchmark for Bitcoin investors’ sentiments from the time period of 2013-2018. This index is constructed through searching terms from top business magazines and journals available online. Such index is used as benchmark to determine the bitcoin potential investor sentiments and their impact on S&P returns. By using the ordinary least square method it was found that there is a negative impact of BSI on S&P returns. Further vector autoregressive(VAR) model is used to determine the association between these economic time series. According to VAR results it was found positive significant impact of S&P returns on BSI whereas, BSI itself was unable to predict S&P returns. Therefore, it can be said that S&P returns causes BSI.

What investors say is what the market says: measuring China's real investor sentiment.

This paper describes a novel approach to measure individual investor sentiment using text-based analysis of millions of posts extracted from Chinese financial online forums. We describe how we built a database of more than 200 million stock posts from online financial forums, created GubaLex, a sentiment dictionary consisting of 48,878 words to allow sentiment analysis, and how we developed GubaSenti, an individual investor sentiment index for the stock market in China. This allowed (1) the first systemic measurement of individual investor sentiment in China; (2) an approach to text-based analysis that reflects investor sentiment about millions of posts about stocks listed in Guba; (3) a way to flexibly measure investor sentiment of a single stock, a sector or an industry and the whole market; and (4) made this possible for daily, weekly, monthly, quarterly, and yearly time periods. We also examine the relationship of the sentiment proxy and stock returns and compare it with two typical BW metrics in China. Empirical results show that GubaSenti correlates better with market performance than BW metrics in China and can be used to predict market changes in the short term.

What Drives Closed-End Fund Discounts? Evidence from COVID-19

By exploiting the exogenous COVID-19 shock, this paper attempts to shed light on the closed-end fund (CEF) discount puzzle. CEF discounts increased after COVID-19, and I identify a causal role of sentiment in this effect. I show that COVID-19 reduced individual investor sentiment. Using the difference-in-differences (DiD) approach, I find that CEFs with higher sentiment beta or higher retail ownership experienced a larger increase in discounts after the COVID-19 shock. The DiD results are unlikely to be driven by alternative channels such as the liquidity, expense, payout, and leverage channels. Overall, the results support the sentiment-based explanation of CEF discounts.

The impact of COVID-19 on the Chinese stock market: Sentimental or substantial?

We investigate the impact of COVID-19 on Chinese stock market by an event study and examine the effect of individual investor sentiment on returns. The pandemic has an overall negative effect on stock market during the post-event window, which can't be explained by real losses. Results show a stronger positive correlation between individual investor sentiment and stock returns than usual. The impact on individual investor sentiment on stock returns is more significant for enterprises with high PB, PE and CMV, low net asset, and low institutional shareholding. Only 7 industries related to pharmacy, digitalization, and agriculture are boosted.

Coronavirus (Covid-19) outbreak, investor sentiment, and medical portfolio: Evidence from China, Hong Kong, Korea, Japan, and U.S

This study explores whether investor sentiment, driven by Coronavirus-related news (CRNs) and economic-related announcements (ERAs) associated with the Coronavirus outbreak, is priced in medical stock portfolios in China, Hongkong, Korea, Japan, and U.S. We find that the CNRs and ERAs do not trigger irrational investment behaviours towards medical stocks. CRNs exert significant and positive effects on the five markets' medical portfolios. ERAs also pose positive and significant effects on five markets' medical portfolios. Furthermore, ERAs have stronger effects on the institutional investor sentiment than the individual investor sentiment. Total effects of CRNs and ERAs on five markets' medical stock portfolios are positive and significant, meaning the optimistic investor sentiment on the medical industry, which plays the critical role in preventing this unprecedented infectious disease.