Investor sentiment and return predictability of disagreement

This study examines the influence of investor sentiment on the relationship between disagreement among investors and future stock market returns. We find that the relationship between disagreement and future stock market returns time-varies with the degree of investor sentiment. Higher disagreement among investors’ opinions predicts significantly lower future stock market returns during high-sentiment periods, but it has no significant effect on future stock market returns during low-sentiment periods. Our findings imply that investor sentiment is related to several causes of short-sale impediments suggested in the previous literature on investor sentiment, and that the stock return predictability of disagreement is driven by investor sentiment. We demonstrate that investor sentiment has a significant impact on the stock market return predictability of disagreement through in-sample and out-of-sample analyses. In addition, the profitability of our suggested trading strategy exploiting disagreement and investor sentiment level confirms the economic significance of incorporating investor sentiment into the relationship between disagreement among investors and future stock market returns.     

Sentiment and stock market connectedness: Evidence from the U.S. – China trade war

We assess the impact of monthly and daily investor sentiment on stock market return and volatility connectedness during the U.S.-China trade war period. Our analyses focus on the connectedness between the two economies and their major trading partners. We also investigate the asymmetric impact of sentiment on volatility connectedness by exploring the upside and downside markets separately. We consistently document a negative relationship between investor sentiment and stock market connectedness for both return and volatility. We further confirm that investor sentiment exerts a larger impact on volatility connectedness in the downside market compared to the upside market.     

我国投资者情绪与股票收益实证研究

根据投资者情绪是股票价格形成重要影响因素这一研究观点,围绕投资者情绪是否构成系统性风险及其对不同类型股票的差异化影响,运用我国股市交易数据进行的实证研究结果表明,投资者情绪不构成股市的系统性风险,但对不同市值的股票有着差异化的影响,随着股票的"投机性"增加,投资者情绪对其影响也增大.此外,投资者情绪会削弱股票收益与其波动的正相关性,且对于"投机性"越高的股票,这一影响也越大.     

Investor Sentiment and the Closed‐end Fund Puzzle: Out‐of‐sample Evidence

In this paper we examine the proposition that small investor sentiment, measured by the change in the discount/premium on closed‐end funds, is an important factor in stock returns. We conduct an out‐of‐sample test of the investor sentiment hypothesis in a market environment that is more likely to be prone to investor sentiment than the USA. We fail to provide supporting evidence for the claim of Lee et al. (1991) that investor sentiment affects the risk of common stocks. Consistent with Elton et al. (1998) , who show that investor sentiment does not enter the return generating process, our tests do not detect investor sentiment in a capital market that is more susceptible to small investor sentiment. Our results provide additional support against the claim that investor sentiment represents an independent and systematic asset pricing risk.     

Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19

This paper studies the pandemic-driven financial contagion during the COVID-19 period and the impact of investor behavior on it by constructing three types of direct behavior measurements based on Google search volumes. More specifically, using a sample of 26 major stock markets around the world during the COVID-19 pandemic, we construct a non-linear financial contagion network via a dynamic mixture copula-EVT (extreme value theory) model to quantitatively detect and measure the complex nature of pandemic-driven financial contagion. Furthermore, through constructing direct investor behavior measurements including investor attention, sentiment, and fear, we find investor behavior plays an important role in explaining pandemic-driven financial contagion. We also find that the impacts of investor behavior on the pandemic-driven financial contagion are heterogeneous under several different settings, including market conditions, market development levels, regional subsets, and contagion directions.     

Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments

This study examines how speculative and hedging sentiments influence the returns and volatilities of energy futures markets. We construct speculative and hedging sentiment indices based on the weekly data of fund and commercial positions of four energy futures: crude oil, heating oil, gasoline, and natural gas, traded on the New York Mercantile Exchange (NYMEX) from 15 January 2013 to 5 February 2019. Our study demonstrates that speculative sentiment generates greater market fluctuations in the energy futures markets than hedging sentiment; and, further, speculative sentiment stimulates a reversal effect on the returns of crude oil futures. Moreover, speculative sentiment exerts positive systemic risk compensation on the four futures' returns, whereas hedging sentiment alleviates volatilities in the energy futures markets. Most notably, distinguishing it from the leverage effect in stock markets, the speculative sentiment in the energy futures markets is influenced more by good than by bad news; while hedging sentiment exhibits emotional neutrality, as opposed to its impact on stock markets as reported in the literature. Additionally, the positive hedging sentiment in crude oil futures demonstrates significant systemic risk compensation, whereas the three other futures do not have an influence, confirming the prevalence of speculation in hedging transactions in crude oil futures. Our further analysis shows cross-market volatility spillover effects, among which speculative sentiment inherent in crude oil futures causes volatility spillovers to the three other futures, while hedging sentiment has no such effect. Our study has implications for overseeing international energy futures markets, providing regulators with evidence that will facilitate the development of effective strategies to strengthen market supervision.     

投资者情绪对市场风险价格影响

本文利用我国证券市场统计数据研究了个体和机构投资者情绪对风险市场价格（MPR）的影响,实证结果证明了市场对波动的反应是异质性的,并且受投资者情绪变化的影响。具体来看,将投资者情绪分解成理性和非理性成分后,非理性乐观情绪的增加将导致MPR明显的下降,但理性情绪的变动不会对MPR有明显的影响。这意味着当市场投资者情绪是由基础价值变化来决定的时候,市场风险价格不会发生变化。进一步的VAR脉冲响应函数分析结果显示,非理性的乐观或悲观情绪并不受理性情绪波动的影响,这意味着非理性情绪不是由基础风险因素决定的。     

Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events

To investigate the complex interactions between market events and investor sentiment, we employ a multivariate Hawkes process to evaluate dynamic effects among four types of distinct events: positive returns, negative returns, positive sentiment, and negative sentiment. Using both intraday S&P 500 return data and Thomson Reuters News sentiment data from 2008 to 2014, we find: (a) self-excitation is strong for all four types of events at 15 min time scale; (b) there is a significant mutual-excitation between positive returns and positive sentiment and negative returns and negative sentiment; (c) decay of return events is almost twice as fast as sentiment events, which means market prices move faster than investor sentiment changes; (d) positive sentiment shocks tend to generate negative price jumps; and (e) the cross-excitation between positive and negative sentiments is stronger than their self-excitation. These findings provide further understanding of investor sentiment and its intricate interactions with market returns.     

无权处分场合买卖合同的效力与权利瑕疵担保

《民法典》第597条第1款的主要规范目的是,无权处分不影响买卖合同的效力。只要承认权利人的追认会产生所有权变动的效果,就适宜承认存在效力未定的处分行为。区分负担行为和处分行为,在解释论上具有可取之处。在传统债法上,无权处分致使给付不能的,存在适用债务不履行责任抑或权利瑕疵担保责任的争论,两方面规定在构成要件上有实质区别。我国《民法典》合同编实行救济进路,第三人享有所有权、抵押权等权利致使所有权不能转移的,当事人可以选择适用《民法典》第597条第1款或第612条,两者在违约责任的构成要件和效果上并无实质区别。《民法典》第612条中规定的第三人“享有权利”文义范围较窄,应当对其进行目的论扩张,将第三人“过去享有权利”且主张权利的一些情形纳入其中;即使买受人构成善意取得,仍可认定出卖人违反权利瑕疵担保义务。     

Are stock market crises contagious? The role of crisis definitions

Financial contagion studies generally examine whether co-movement between markets increases during a crisis. We use a flexible co-movement measure to examine how conclusions of such analyses depend on the sample chosen as the ‘crisis’. To this end, we analyse stock market co-movement during the 1997 Asian crisis and the 2007 global financial crisis for all possible source countries and for all possible time periods or extreme return quantiles. This way we account for the main crisis dating approaches adopted in the literature. Our results suggest there is no clear relationship between excess co-movement and commonly used crisis samples.     

Does Investor Sentiment Affect Earnings Management?

I hypothesize and find that earnings management via accruals is driven partially by the prevailing market‐wide investor sentiment. Managers inflate earnings in periods of higher sentiment, but report more conservatively during periods of low sentiment. Moreover, the likelihood of income‐increasing earnings management to avoid negative earnings surprises is also positively associated with investor sentiment. These results are robust to: (i) controls for time‐varying firm characteristics such as growth, investment opportunity sets, future profitability, leverage and size; (ii) macroeconomic variables such as future inflation, GDP growth, and growth in industrial production; (iii) multiple proxies for investor sentiment; and (iv) discretionary revenues as alternative measure of earnings management. Cross‐sectional analyses reveal that firms whose stock returns co‐move more with investor sentiment are more (less) likely to manage earnings upward via abnormal accruals in quarters of higher (lower) sentiment. The findings of managers’ strategic use of abnormal accruals show the need for increased attention from boards of directors, auditors and regulators to heightened managerial incentives to overstate earnings and to report optimistic earnings numbers during periods of high investor sentiment.     

Time-variation in the impact of news sentiment

Utilizing firm-specific news sentiment data provided by Thomson Reuters News Analytics, I construct aggregate measures to examine the relationship between news sentiment and stock market returns over the period 2004–2010. I find a highly significant relationship between aggregated measures of news sentiment and stock returns that fluctuates over time and by industry. I identify a link between the time-variation of news sentiment impact and industry beta, and determine that levels of investor sentiment (proxied by VIX) play an important role in explaining this variation.     

Asymmetric impacts of disaggregated oil price shocks on uncertainties and investor sentiment

This paper aims to examine short- and long-run asymmetries in the impacts of disaggregated oil price shocks on economic policy uncertainty, stock market uncertainty, treasury rates, and investor (bullish and bearish) sentiment in the US. To this end, we use a nonlinear auto-regressive distributed lag cointegration approach, which allows us to capture both positive and negative disaggregated oil shocks. We find that oil demand shocks are the main drivers of both measures of uncertainty, while oil supply shocks affect treasury rates. However, both oil demand shocks and oil supply shocks affect investor sentiment, with certain differences in the effects of positive and negative shocks. The overall effects of both oil demand and supply shocks—whether positive or negative—are stronger in the long-run than in the short-run. Additionally, we apply rolling causality and reveal evidence of a rather homogenous causal flow from disaggregated oil shocks to the variables studied, particularly around global stress periods. Our findings have implications for asset pricing and portfolio risk management and suggest policy formulations that differentiate between disaggregated positive and negative oil price shocks.

     

DAYLIGHT AND INVESTOR SENTIMENT: A SECOND LOOK AT TWO STOCK MARKET BEHAVIORAL ANOMALIES

Kamstra, Kramer, and Levi (2000, 2003) describe two stock market behavioral anomalies associated with changes in investor sentiment caused by daylight saving time (DST) changes and seasonal affective disorder (SAD). According to the hypothesized effects, DST changes and SAD affect asset prices by changing investors’ risk aversion. Although changes in the timing or amount of daylight are correlated with unusual stock market returns, I present evidence they do not cause those unusual returns. Instead, seasonal patterns in market‐related information during the sample period are the likely cause of the correlation between stock market returns and DST changes or SAD.     

The Dynamic Extreme Co-Movement between Chinese Stock Market and Global Stock Markets

ABSTRACT

We use time-varying Symmetrized Joe-Clayton Copula model to study the extreme co-movement (boom or crash together) between the Chinese stock market and major stock markets in the world from 2007 to 2017, including developed markets and stock markets on “Belt and Road Initiative” (hereafter B.R.I.). We find that the extreme co-movement probability between Chinese market and “Belt and Road Initiative” markets is higher than developed markets at both tails. Then we study important “real” and “non-fundamental” factors affecting the excess co-movement probability, including bilateral trade openness, financial integration, and economic policy uncertainty. The results of panel regression analysis show that: the bilateral financial integration has significant effects over the lower tail dependence between Chinese and developed markets, but does not affect the extreme co-movement between Chinese and B.R.I. markets. And the bilateral trade openness is an important factor for the extreme co-movement at both tail between Chinese and global markets. The economic policy uncertainty index, especially China’s economic policy uncertainty, plays a key role in the extreme co-movement between Chinese and developed markets at both tails. However, it has sizable effects only at the upper tail co-movement between Chinese and B.R.I. markets.     

Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network

In the post-epidemic period, the international economic structure has been readjusted, with risks contagious across financial and economic systems. This paper primarily uses the high-frequency TENET network and the Granger-causality network to describe the interconnectedness between the tail risk of stock volatility and investor sentiment, then the two-layer network is constructed by the generalized variance decomposition method to examine the inter-layer connectedness. Based on the two-layer network, the heterogeneity frequency response of network connectedness and dynamic network structure are further analyzed from the perspective of frequency domain. The study found that the tail risk of high-frequency stock volatility displays industry heterogeneity and time-varying property, and investor sentiment contagion network provides information transmission medium for stock risk. The double-layer network study found that stock volatility in consumer goods industry exhibits higher risk spillover to investor sentiment. The diversified financial industry, real estate industry and energy industry in the two-layer network are systemically important industries. In addition, the study of the frequency domain dynamic network found that the connectedness volatility in the short-term risk network of stock volatility was significantly higher than that of the investor sentiment network, and the short-term risk spillover effect of the network played a leading role in the total risk spillover. The research conclusions provide reference for preventing systemic risks from the perspective of systemically important industries and cyclical fluctuations.     

Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets

This paper first investigates the relationship between investor sentiment, captured by internet search behaviour, and the unexpected component of stock market volatility during the COVID-19 pandemic. According to data on 12 major stock markets, our research indicates a positive correlation between the Google search volume index on COVID-19 and the unexpected volatility of stock markets. The result suggests that greater COVID-19-related investor sentiment during this pandemic is associated with higher stock market uncertainty.Our study further examines whether country-level governance plays a role in protecting stock markets during this pandemic and reveals that the unexpected conditional volatility is lower when a country's governance is more effective. The impact of investor sentiment and country governance on unexpected volatility after the initial shock of COVID-19 is also investigated. The findings demonstrate the importance of establishing good country-level governance that can effectively reduce stock market uncertainty in the context of this pandemic, and support continual policy development related to investor protection.     

投资者关注与股价崩盘风险:抑制还是加剧?

本文以2010—2017年中国A股上市公司为样本,考察了投资者关注影响股价崩盘风险的客观表现和传导路径。研究发现,投资者关注度的提高会显著加剧下一期的股价崩盘风险,存在“关注度的崩盘效应”;分组检验发现,关注度的崩盘效应仅在机构持股比例低的公司和市场处于牛市状态下存在;路径检验发现,投资者关注不存在信息路径,没有改善公司信息透明度,但存在部分的情绪路径,提高了股价同步性和投资者情绪,从而加剧了股价崩盘风险。建议监管部门重视投资者关注对股价带来的冲击,通过进一步提高机构者持股比例,缓解情绪过热导致的定价错误程度,降低股价崩盘风险。     

Chinese institutional investors’ sentiment

We use daily survey data on Chinese institutional investors’ forecasts to measure investors’ sentiment. Our empirical model uncovers that share prices and investor sentiment do not have a long-run relation; however, in the short-run, the mood of investors follows a positive-feedback process. Hence, institutional investors are optimistic when previous market returns were positive. Contrarily, negative returns trigger a decline in sentiment, which reacts more sensitively to negative than positive returns. Investor sentiment does not predict future market movements—but a drop in confidence increases market volatility and destabilizes exchanges. EGARCH models reveal asymmetric responses in the volatility of investor sentiment; however, Granger causality tests reject volatility-spillovers between returns and sentiment.     

Intraday online investor sentiment and return patterns in the U.S. stock market

We implement a novel approach to derive investor sentiment from messages posted on social media before we explore the relation between online investor sentiment and intraday stock returns. Using an extensive dataset of messages posted on the microblogging platform StockTwits, we construct a lexicon of words used by online investors when they share opinions and ideas about the bullishness or the bearishness of the stock market. We demonstrate that a transparent and replicable approach significantly outperforms standard dictionary-based methods used in the literature while remaining competitive with more complex machine learning algorithms. Aggregating individual message sentiment at half-hour intervals, we provide empirical evidence that online investor sentiment helps forecast intraday stock index returns. After controlling for past market returns, we find that the first half-hour change in investor sentiment predicts the last half-hour S&P 500 index ETF return. Examining users’ self-reported investment approach, holding period and experience level, we find that the intraday sentiment effect is driven by the shift in the sentiment of novice traders. Overall, our results provide direct empirical evidence of sentiment-driven noise trading at the intraday level.