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.     

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.     

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.     

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.     

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.     

Scheduled macroeconomic news announcements and intraday market sentiment

We analyze the effects of scheduled macroeconomic news on intraday and daily market sentiment by comparing sentiment on news announcement dates with that on non-announcement dates. Announcements of macroeconomic indicators change neither intraday nor daily market sentiment. However, the directions of the announced values have asymmetric effects on intraday market sentiment, although they do not affect daily market sentiment. For example, an announcement of an increase in the gross domestic product (GDP) reduces short-term intraday market sentiment, whereas an announcement of a decrease in GDP does not significantly affect intraday market sentiment. We also find that the effect of intraday market sentiment on short-term market returns is greater following announcements of macroeconomic indicators that significantly affect intraday market sentiment.     

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.     

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 impact of sentiment and attention measures on stock market volatility

We analyze the impact of sentiment and attention variables on the stock market volatility by using a novel and extensive dataset that combines social media, news articles, information consumption, and search engine data. We apply a state-of-the-art sentiment classification technique in order to investigate the question of whether sentiment and attention measures contain additional predictive power for realized volatility when controlling for a wide range of economic and financial predictors. Using a penalized regression framework, we identify the most relevant variables to be investors’ attention, as measured by the number of Google searches on financial keywords (e.g. “financial market” and “stock market”), and the daily volume of company-specific short messages posted on StockTwits. In addition, our study shows that attention and sentiment variables are able to improve volatility forecasts significantly, although the magnitudes of the improvements are relatively small from an economic point of view.     

The effect of market sentiment and information asymmetry on option pricing

This work addresses the impact of imperfections, such as information asymmetry and market sentiment, on the performance of option pricing models. More precisely, this work compares the option pricing model of Black and Scholes and the same model in the presence of imperfections. This study is based on S&P 500 options that cover the period between 17/03/2000 and 14/06/2013. The achieved results show that, in general, in the presence of imperfections, the model is more effective than the Black and Scholes model. This research appears to be promising for the incorporation of imperfections into the assessment of options.     

Time-varying impact of monetary policy shocks on US stock returns: The role of investor sentiment

This paper investigates how monetary policy shock affects the stock market of the United States (US) conditional on states of investor sentiment. In this regard, we use a recently developed estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks, which in turn is achieved by integrating the current short-term rate surprises, which are least affected by an information effect, into a vector autoregressive (VAR) model as an exogenous variable. When allowing for time-varying model parameters, we find that, compared to the low investor sentiment regime, the negative reaction of stock returns to contractionary monetary policy shocks is stronger in the state associated with relatively higher investor sentiment. Our results are robust to alternative sample period (which excludes the zero lower bound) and model specification and also have important implications for academicians, investors, and policymakers.     

The influence and predictive powers of mixed-frequency individual stock sentiment on stock returns

In this article, we construct mixed-frequency individual stock sentiment using MIDAS model. We first investigate the influence power of mixed-frequency individual stock sentiment on excess returns. The results indicate that the higher the frequency of individual stock sentiment is, the better it explains the variation of excess returns, that mixed-frequency individual stock sentiment, especially mixed high-frequency sentiment, exerts greater influence on excess returns than the same frequency one and that the mixed-frequency sentiment has a stronger explanatory power to the variation of excess returns than size factor, book-to-market factor, profitability factor and investment factor do. Then, we study the predictive content of mixed-frequency individual stock sentiment. The results show that the higher the frequency of individual stock sentiment is, the better the forecast performs. Moreover, by comparing the corresponding statistics in influence and predictive power models, we find that the influence power of mixed-frequency individual stock sentiment is more significant than its predictive power.     

投资者情绪对封闭式基金折价的影响研究述评

封闭式基金折价问题由来已久,本文对国内外文献进行梳理,从基本面因素、情绪因素等角度分别对封闭式基金折价问题进行剖析,本文的亮点在于追根溯源从心理学角度寻找投资者情绪的特征,从心理学文献中寻找折价的原因,并根据国内外文献,提出封闭式基金折价问题研究的切入点。     

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.     

Spillover and connectedness among G7 real estate investment trusts: The effects of investor sentiment and global factors

This paper examines the dynamic spillover interconnectedness of G7 Real Estate Investment Trusts (REITs) markets. We use the spillover index of Diebold and Yilmaz (2012), the time-varying parameters vector-autoregression (TVP-VAR) model, and the quantile regression approach. The result show that REITs network connectedness is dynamic and experiences an abrupt increase in the first wave of COVID-19 outbreak (2020Q1). We also observe a substantial abrupt decrease in connectedness during the success of vaccination programs (end 2021). The connectedness among assets is much stronger during COVID-19 than before. The REITs of Japan and Italy are net receivers of spillover and those of US and UK are net transmitters of spillovers before and during COVID-19. Conversely, the REIT of Canada and Germany (France) switches from net receivers (contributors) of spillovers before the pandemic to net contributors (receivers) during the COVID-19. Finally, we show that News Sentiment index, Geopolitical Risk index, Economic Policy Uncertainty index, US Treasury yield, and Stock Volatility index influence the spillover magnitude across quantiles.     

Spillovers of currency carry trade returns,market risk sentiment,and U.S. market returns

This paper examines the link between spillovers of currency carry trade returns and U.S. market returns. Following Tse and Zhao (2012), this paper hypothesizes that the magnitude of spillovers of currency carry trade returns is positively correlated with market risk sentiment and, therefore, has an impact on market returns. Using the G10 currencies and S&P 500 index futures, the empirical results present a high magnitude of spillover effects of currency carry trade markets. The empirical findings also show a significantly positive relationship between spillovers of currency carry trade returns and subsequent market returns. Furthermore, the results indicate that this relationship is stronger in bear markets than in bull markets. Finally, our findings show that spillovers of currency carry trade returns significantly affect the subsequent transition probabilities of market returns.     

Identifying states of global financial market based on information flow network motifs

Stock markets exhibit different states due to internal and external shocks. It is of great significance to identify the status of global financial markets. Based on 48 global stock indices from 1996 to 2018, we constructed a global stock index transfer entropy network, which represents the information flow between stock markets in different economies. By analyzing the triadic motifs in the transfer entropy network, we divided the global stock market into different market states based on the distribution of motifs. The characteristic structure of information flow was observed in different market states. We found that the information flow in the global stock market increases significantly during major financial events, indicating that the global stock index has a mutual influence and a close relationship with each other. In addition, stock indices in the Asia-Pacific, Middle East, and Africa are the main sinks of information, while stock indices in the Americas and Europe are the primary sources of information.     

Intraday effect of news on emerging European forex markets: An event study analysis

We analyze the impact of euro zone/German and U.S. macroeconomic news announcements and the communication of the monetary policy settings of the ECB and the Fed on the forex markets of new EU members. We employ an event study methodology to analyze intraday data from 2011–2015. Our comprehensive analysis of the wide variety of macroeconomic information during the post-GFC period shows that: (i) macroeconomic announcements affect the value of the new EU country exchange rates, (ii) the origin of the announcement matters, (iii) the type of announcement matters, (iv) different types of news (good, bad or neutral) result in different reactions, (v) markets react not only after the news release but also before, (vi) when the U.S. dollar is the base currency the impact of the news is larger than in the case of the euro, (vii) announcements on ECB monetary policy result in stronger effects than those of the Fed, (viii) temporary inefficiencies are present in new EU country forex markets, (ix) new EU country exchange rates react differently to positive US news during the EU debt crisis compared to the rest of the period.     

流动性衡量及对资产定价的影响研究述评

流动性一般被认为是市场执行交易的能力,这种能力表现为交易的便利性和交易对价格冲击的最小化.对于流动性的衡量有基于买卖价差的方法、流动比率的方法、交易对价格的冲击的方法等等,许多文献在衡量流动性水平的基础上,就流动性对资产定价的影响进行了理论和实证研究,本文系统总结了这些代表性的模型和研究成果.最后本文认为应该在参考国外成熟理论的基础上,深入研究适合我国资本市场的流动性衡量方法、内在规律和对价格的作用机制.     

The impact of macro news and central bank communication on emerging European forex markets

We employ a two-stage empirical strategy to analyze the impact of macroeconomic news and central bank communication on the exchange rates of three Central and Eastern European (CEE) currencies against the euro. First we estimate the nominal equilibrium exchange rate based on a monetary model. Second, we employ a high-frequency GARCH model to estimate the effects of the news and communication along with the estimated exchange rate misalignment on the exchange rate as well as its volatility. The analysis is performed during the pre-crisis (2004–2007) and crisis (2008–2009) periods. CEE currencies react to macroeconomic news during both periods in an intuitive manner that corresponds to exchange rate-related theories. However, the responsiveness of the currencies to central bank verbal interventions becomes important only during the crisis period.