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This paper establishes a direct link between (anti) herding behavior in currency markets and investor sentiment, proxied by a social media based investor happiness index built on Twitter feed data. Our analysis of daily data for nine developed market currencies suggests that the foreign exchange market is generally characterized by strong anti-herding behavior. Utilizing the quantile-on-quantile (QQ) approach, developed by Sim and Zhou (2015), we show that the relationship between investor sentiment and anti-herding is in fact regime specific, with anti-herding behavior particularly prominent during states of extreme investor sentiment. The effect of sentiment on anti-herding is generally stronger in extreme bullish sentiment states, while average sentiment is associated with less severe anti-herding. The findings lend support to the behavioral factors for asset pricing models and suggest that real time investor sentiment signals can be utilized to monitor potential speculative activities in the currency market. [ABSTRACT FROM AUTHOR]

In this paper, we link Joseph de la Vega's work Confusion de Confusiones, written in 1688, with current behavioral finance and propose that Vega be considered the first precursor of modern behavioral finance. In addition to describing excessive trading, overreaction and underreaction, and the disposition effect, Vega vividly portrays how investors behaved 300 years ago and includes interesting documentation on investor biases, such as herding, overconfidence, and regret aversion. [ABSTRACT FROM AUTHOR]

The cycle of boom and crash is a “natural” element in financial market history, and numerous research works have provided evidence that market prices spend far more time deviating from postulated theoretical equilibrium than actually tending towards it. In particular, nonmean-reverting dynamism in financial markets may be produced by mass psychological dynamics in the patterns of human aggregate behavior, which result from nonrational herding impulses sensed by market participants in complex and uncertain situations. Based on a literature review and the analysis of several case studies, this paper elucidates postulated mechanisms behind, and characteristics of, herding in financial markets. The main goal is to raise awareness of the often little-understood point that collective behavior does not simply sum up preexisting individual motives and preferences. Thus, the paper focuses on the mechanism of how individually unintended aggregate outcomes such as financial market booms and panics are shaped by collective dynamics and social interactions between traders and their social environment. [ABSTRACT FROM AUTHOR]

Relying on over 300 million news sentiment scores from a global news source covering a battery of different news topics and their sentiment, we construct a novel measure called top news sentiment based on rolling correlations with equity returns. We find an effect of top news sentiment on stock returns with robust timeframes. These findings add to the sentiment literature with the first dynamically created sentiment variable. We are able to construct profitable trading strategies based on top news sentiment. It therefore pays off for investors to be inattentive to most news topics and their sentiment. [ABSTRACT FROM AUTHOR]

In this paper, I provide empirical evidence that an analyst working in Germany is more likely to publish a high (low) price target regarding a DAX30 stock when other Germany based analysts are also optimistic (pessimistic) about the same stock. This effect of geographical proximity is not biased by the fact that DAX30 companies are headquartered in Germany. Shedding light on how influence takes place, I show that influence through communication and the exchange of opinion within small groups of analysts plays a vital role. This mainly applies during a bullish market environment. When markets are bearish, analysts' incentives induce them not to deviate too much from the overall average, such that then observational learning has a greater impact. [ABSTRACT FROM AUTHOR]

We present seminal empirical evidence on market-wide herding from historical markets for the St. Petersburg stock exchange between 1865 and 1914. Our findings indicate the presence of herding in Imperial Russia's largest equity market, which tends to vary among industries and grow stronger during months of negative performance and declining volatility. Controlling for the 1893-reform that prompted wider social participation in equity trading, we find that herding surfaces exclusively in the post-reform years, with no evidence of herding arising pre-reform. Our results showcase that the behavior of investors in historical stock exchanges exhibits patterns similar to those of modern-day ones. [ABSTRACT FROM AUTHOR]

Herding is a feature of investor behavior in financial markets, particularly in market stress. We apply an approach based on the cross-sectional dispersion of individual stocks' betas, which allows us to extract herding patterns, using two dynamic methodologies to measure the herding phenomenon over time with a state-space model for the Cryptocurrency Market. The results reveal that herding toward the market shows significant movement, and persistence regardless of the market condition, expressed through the market index, market volatility, and the volatility index. When analyzing path herding is possible to observe that herding was intense during the investigated period. We also identify a positive relationship between herding and market stress. [ABSTRACT FROM AUTHOR]

This study is aimed at testing the relationship between investors' uncertainty reflected by market sentiment and herding behavior phenomenon. Using data for 1990–2019 for size-ranked portfolios, the evidence documented here indicates that herding is strongly related to market sentiment as captured by the CBOE's Volatility Index, the VIX. The results indicate that the VIX, which is also recognized as the fear index, has a substantial impact on herding across all groups and subgroups of size-ranked portfolios. Overall, the effect of VIX exists in most of the quantiles of the cross-sectional absolute deviation distribution. In this context, the scale and magnitude of the fear index impact rises toward the highest parts of the herding distribution. We also show that herding behavior is more pronounced when the market is overwhelmed by sentiment. The findings have several practical implications for investment professionals such as portfolio managers, investment officers, analysts, and other market participants. They also provide academic insights for researchers dealing with market efficiency and investors' behavior. [ABSTRACT FROM AUTHOR]

This study uses high-frequency intraday data to investigate country-level intraday herding behavior among global market investors and finds strong evidence of significant herding at the country level. Specifically, we find that traders tend to follow each other from one country to another. Moreover, we find that country-level herding is a combination of informed and uninformed herding, and that the contribution of uninformed herding is approximately five times greater than that of its informed counterpart. Informed country-level herding is primarily motivated by correlated signals, whereas uninformed country-level herding is influenced by momentum trading, style investing, and market pressure. [ABSTRACT FROM AUTHOR]

The author examines whether the trading behavior of exchange-traded funds (ETFs) is biased by any herding effect. Return data of a sample of 66 and 34 large-cap and small-cap ETFs, respectively, are used over the period 2012-2016 to assess whether these funds herd and whether herding is more pronounced during extreme markets, during down markets, and during days with extreme trading activity and volatility. The results show that herding is not the case for ETFs. However, some evidence is obtained on a decreasing return dispersion among ETFs on days with negative market returns. Trading activity seems not to induce herding. On the contrary, the author obtains evidence that shows that the higher the trading volumes are, the higher the return dispersion among ETFs is. When it comes to herding during highly volatile markets, the author finds that return dispersion among ETFs decreases on days with extremely high intraday volatility. However, when assessing the relationship between return dispersion and volatility without focusing on days with extremely high risk, the author obtains strong evidence of a linear relation between the 2 variables. This contradicting finding suggests that the stronger the intraday volatility in the ETF market is, the wider the dispersion in returns among ETFs is. [ABSTRACT FROM AUTHOR]

The primary objective of the study is to explore the predictability of herding patterns of foreign institutional investors in the Indian market using high frequency data over a period from January 2003 to June 2014. Herding of an individual stock was measured estimating a simple volume based ratio and persistence of trends was detected using theruns test(Wald and Wolfowitz [1940]) on that ratio. Predictability of herding behavior has been successfully modeled by applying 7 data mining models using various measures of performance. Market regulators may consider our findings to regulate the foreign institutional investors trading to make the financial system more transparent and robust. [ABSTRACT FROM AUTHOR]

The purpose for this article is to explore the existence of herding behavior in the context of Shariah-based ethical investments. To this end the authors have employed the highly liquid constituent stocks of the U.S. Dow Jones Islamic Index for the period January 2007 to December 2014. The methodology encompasses both static and dynamic models that capture potential time-varying patterns or asymmetric behavior of herding. Summarizing the results, the authors document significant antiherding behavior that is robust across different formulations and testing procedures. Most interestingly, they observe an asymmetric behavior of the antiherding phenomenon. Results from the dynamic analysis reveal that antiherding tends to be more intense during turbulent periods. The findings may entail useful implications for investors who wish to diversify their portfolios using faith-based investments. [ABSTRACT FROM AUTHOR]

We study reputational herding in financial markets in a laboratory experiment. In the spirit of Dasgupta and Prat [2008], career concerns are introduced in a sequential asset market where wages for investors are set by subjects in the role of employers. Employers can observe investment behavior, but not investors' ability types. Thereby, reputational incentives may arise endogenously. We find that a sizable fraction of investors follows an established trend even in a setting where there are no reputational incentives. In a setting where there are reputational concerns, they do not seem to create substantial herd behavior. [ABSTRACT FROM AUTHOR]

In this article, we study the herding phenomenon in Spanish equity pension funds with European investment locations from 2002 to 2012, considering whether the development of different investment strategies by the managers results in herding. In addition, we analyze the performance-herding relationship, observing whether pension fund performance decreases or increases when pension funds herd. Using the herding measure of Lakonishok et al. [1992], we do not find strong imitation behavior, although herding in the market and book-to-market styles are higher. Those pension funds that do not herd or that follow distinctive strategies do not present significant differences in performance with respect to herding funds. [ABSTRACT FROM PUBLISHER]

Mathematical descriptions of financial markets with respect to the efficient market hypothesis (EMH) and fractal finance are now equally robust but EMH still dominates. EMH and other current paradigms are extended to accommodate situations having higher information complexity and interactions coupled with positive feedback. The “herding behavior” literature in finance marks a significant recognition that interdependent trader behavior may result in deviation from normal distribution of returns, as does “chartist” trading. Further legitimization of the separate-but-equal status of EMH and fractal finance is pursued. Research on the nonlinear models giving theoretical underpinning to equations representing mirror markets as complex dynamical systems is encouraged. Why some herding- and chartist-behaviors scale up and then die off whereas others result in significant crashes is explained. The buildup to the 2007 liquidity crisis offers an example of nonlinear scale-free dynamics. Concepts from complexity science, econophysics, and scale-free theory are used to offer further explanation to physicists’ mathematical treatments. [ABSTRACT FROM AUTHOR]

The article focuses on the conclusive evidence of herding among most types of financial institutions. It has been suggested that most institutional investors herd. The tendency to herd is the greatest among bank trust departments and independent advisors and the least among mutual funds. Most herding appears to be based on informational cascades and is not momentum based. Institutions that herd tend to follow other like institutions. No evidence has been found that herding appears to drive prices away from fundamental values although it has been proved that herding tends to decline over time and be less significant in the stocks of large firms.

This article studies the herding effect in the capital markets. Using data from the Italian Stock Exchange, the authors test for the presence of herding as described in Christie and Huang [1995], Chang, Cheng, and Khorana [2000], and Hwang and Salmon [2001]. The tests support Christie and Huang's conclusions that herding is present in extreme market conditions. [ABSTRACT FROM AUTHOR]