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If all analysts have access to the same public information, why would some analysts deviate from the "herd" and issue "bold" recommendations? Is boldness in recommendation a signal of overconfidence or higher ability? We find that it is more profitable to trade based on bold recommendations for firms with low analyst coverage, compared with firms with medium and high coverage. Herding recommendations are less profitable than bold recommendations for firms with low analyst coverage. It appears that some analysts strategically bias their earnings forecast (resulting in less accuracy) so that their recommendations are more profitable. [ABSTRACT FROM AUTHOR]

"Herding games" are mimicry games played by children in several East African pastoralist societies. This article presents an ethnographic account of the herding game among the Hamar agro-pastoralist people of Southwest Ethiopia, and reveals the dynamics by which children learn pastoral ecological knowledge from each other and socialise one another into pastoralist linguacultural practices. During the herding game, male children of various ages learn from each other the indigenous categorisation system for livestock individuation, and internalise important semantic distinctions in the domain of coat colours and patterns, by mapping the categories for livestock appearance on pebbles and shells. The game also allows children to learn and practise the communicative style used in human–animal interactions: this includes the Hamar system of address for cattle, animal directives and "bell-ideophones", which are crucial in a pastoral soundscape. The study demonstrates the importance of child agency in linguacultural socialisation. Herding games and children's play are an important context for horizontal learning in small-scale pastoralist societies and should be given more attention in cross-cultural studies on child socialisation. [ABSTRACT FROM AUTHOR]

In this article, we aim to design a general framework for the pursuit‐evasion (PE) game of multiple UAVs. Based on the distance between the pursuers and the evader, the whole pursuit‐evasion process is decoupled into a seeking stage and a herding stage. A formation control method is proposed to make sure that the pursuers can find and drive the noncooperative evaders along a desired trajectory towards the designated target while maintaining a preset formation. In the meantime, an adaptive potential function is designed to achieve collision avoidance to both obstacles and other agents in the formation. The main contribution is that it combines formation control and collision avoidance in the problem of indirect herding, which is rarely addressed before. Also, the convergence and effectiveness of the designed controller for trajectory tracking and formation maintenance are proven and verified in the article. Simulation results in two and three dimensional space show that the proposed framework achieves the goal of coordinated herding and collision avoidance in a pursuit‐evasion scenario under uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

In today's fast-paced digital landscape, the attention span of users consuming video content is alarmingly brief, often as short as 15 seconds for music or entertainment videos and 6 minutes for lecture videos. This presents a significant challenge for video producers and platform providers as they seek to engage users with longer content. One promising solution involves recommending specific fragments within longer videos that align with individual user profiles. In this article, we address this challenge by introducing a novel framework for video fragment recommendations, guided by three key insights. First, we implement a Self-Attention Block that captures the inter-fragment contextual effect, enhancing the relevance of recommendations. Second, we incorporate video-level preferences to ensure that the fragment recommendations are consistent with users' overall interests. Third, we propose a Self-Attentive Herding Effect (SAHE) module to model the intra-fragment contextual effect, specifically the herding effect of time-sync comments within a fragment. To evaluate the effectiveness of our proposed method, we conduct extensive experiments comparing our model against the state-of-the-art approaches in terms of NDCG@K and Recall@K. Our results demonstrate that the model effectively leverages inter-fragment and intra-fragment contextual effects along with video-level preferences, outperforming existing methods. Additionally, we carry out empirical experiments to analyze the key components and parameters of the proposed model, providing further insights into its performance.1 [ABSTRACT FROM AUTHOR]

Drawing inspiration from natural herding behaviours, shepherding provides a method for swarm guidance that utilizes steering agents and can be applied in biological and robotics systems at various scales. However, while most shepherding research has relied on the precise sensing capabilities of steering agents, these assumptions do not necessarily hold in real-world tasks. To fill in the gap between practice and literature, in this study, we demonstrate that swarm shepherding can be achieved via bearing-only measurements, and explore the minimum amount of information required. We initially formulate our algorithm for a single agent and subsequently expand its application to accommodate multiple agents, incorporating strategies tailored for herding multiple swarms. Numerical simulations show the effectiveness of the algorithm under various initial placements and configurations. The minimum amount of information required by the proposed algorithm for successful shepherding, i.e. a moderate angular accuracy for the steering agents and limited communication between them, is also determined. Our proposed bearing-only algorithm offers crucial insights into swarm dynamics, which may have applications across a variety of domains, such as agriculture and search and rescue. This article is part of the theme issue 'The road forward with swarm systems'. [ABSTRACT FROM AUTHOR]

The paper aims to examine the relationships between behavioural biases (such as overconfidence and herding) and the rational behaviour of Australian female consumers when making financial decisions. In doing so, the paper showcases the financial illiteracy of Australian female consumers when confronted with irregularities within the Australian financial markets. From a theoretical standpoint, the study adopts the notions of the adaptive market hypothesis (AMH) to understand the reasoning behind the relationships between behavioural biases (such as overconfidence and herding) and the rational behaviour of Australian female consumers when making decisions rationally. Using a quantitative approach, a structural equation modelling (SEM) was conducted on the proposed theoretical framework with a cleaned dataset of 357 Australian female consumers, which revealed that behavioural biases significantly influence each stage of rational decision-making when making financial decisions. More precisely, the structural equation modelling (SEM) showcases that herding behaviour has a significant positive relationship with the information search and evaluation of alternative stages when making financial decisions. However, overconfidence behaviour has a significant negative relationship with demand identification and evaluation of alternative stages when making financial decisions. Moreover, the findings also showcase that the proposed theoretical model closely fits with the data utilised, indicating that Australian female consumers do follow rational decision-making when making financial decisions. Additionally, the findings revealed that the education and income levels of Australian female consumers positively influence the stages of rational decision-making. The findings also contend that Australian female consumers have a risk-averse attitude (i.e., within three key hypothetical scenarios) towards financial decisions due to the presence of financial illiteracy. Hence, it is strongly suggested that financial institutions highlight the calculative benefits and returns from financial product purchases in advertising and promotions in a way that appeals to female consumer segments. [ABSTRACT FROM AUTHOR]

The study investigates the impact of sector and market-wide illiquidity shocks on herding within US Real Estate Investment Trusts (REITs), on a sub-sector level, including health, hotel, mortgage, residential, retail and Warehouse REITs. Using daily data from January 2014 to February 2022, and consistent with noise trader risk theory, the research confirms the existence of herding behavior within US REITs on a sub-sector level, along with identifying that herding effects are intense on days with negative market returns as compared to days with positive market returns. Assessing the impact of investor sentiments via the VIX index, we find that herding behavior rises with a hike in investor uncertainty and fear. Motivated by the presence of a structural break within our data set corresponding to the Covid-19 outbreak, we use a Markov Switching approach and find significant evidence of sub-sector herding being more intense during the crash regime/covid-19 phase, relative to the expansionary phase. When assessing illiquidity, our results confirm that i) during the expansionary phase only expected illiquidity (market and sector-wide) enhances sub-sector herding within US REITs while ii) during the crash phase only unexpected illiquidity (market and sector-wide) enhances sub-sector herding within US REITs. [ABSTRACT FROM AUTHOR]

Abstract This study investigates the impact of information communication technology (ICT), economic freedom, and economic sustainability on herding behavior, and examines whether the link between economic freedom and economic sustainability depends on ICT. Using quantile regression on a sample of seven Gulf Cooperation Council stock markets from 2004 to 2020, we find that ICT and economic freedom reduce herding in lower quantiles while promoting it in higher quantiles. Conversely, open market freedom and economic sustainability appear to correct herding in all quantiles. The results show that ICT reinforces the move away from herding seen with economic freedom for the transmission channel of ICT on herding. However, ICT plays a dual role in open market freedom and economic sustainability, weakening (strengthening) the curative effect of economic sustainability (open market freedom) in the lower quantiles and strengthening (weakening) it in higher quantiles. Thus, the highest impact in reducing herding exits through the combination of ICT and economic freedom is skewed to the lower quantiles with ICT-open market freedom and skewed to the upper quantiles with ICT-economic sustainability. These results offer substantial implications for policymakers.

Investor behavioral factors determine the investment decisions of individual investors in the stock market. The study investigated behavioral factors driving investment decisions in Nepal’s stock market, contributing to existing literature. The behavioral factors comprise heuristics, prospects, and herding as predictors and investment decisions as a response variable. Thus, the study adopted a descriptive and analytical research design to test the research hypotheses and resolve the research questions and issues. A survey was conducted among individual investors registered with Nepal’s trading management system (TMS). A total of 526 structured questionnaires were distributed to targeted respondents, and only 350 useful questionnaires (66.54 percent) were received. The survey data of cross-sectional type were encompassed with a random clustering sampling method for this study. Further, the study employed descriptive statistics to depict the characteristics of respondents’ profiles, correlation analysis to assess the association between predictors and response variables, and linear regression analysis to investigate the impact of predictors on response variables. Similarly, Cronbach’s alpha was tested to observe reliability in the study. The survey findings showed a positive and significant association between heuristics and investment decisions (β = 0.088, p < 0.05). The prospect is positively linked with the individual’s investment decision but found insignificant (β = 0.011, p > 0.05). Finally, herding found a positive and significant association with investment decisions (β = 0.235, p < 0.05). The findings of this study contribute to existing theory and can be a benchmark for decision-makers and policymakers, investors, and others.

Purpose – The study examines the herd behaviour in Association of Southeast Asian Nations (ASEAN)-5 foreign exchange markets: Indonesia, Malaysia, Philippines, Singapore and Thailand. Design/methodology/approach – We use the daily data as a sample. Cross-sectional absolute deviation (CSAD) and quantile regression are employed to identify the herding behaviour in these markets. Findings – The findings report that all the foreign exchange markets in ASEAN-5 do not exhibit herding behaviour. Diversity of the fundamental economic, such as economic growth rate, rate of inflation and economy structure, produce monetary and exchange rate policies, is among the reasons for the absence of herd behaviour. Practical implications – Maintaining macroeconomic stability and promoting market resilience to outside shocks should remain a priority for policymakers. As for investors, diversification is still a vital risk-management strategy. Originality/value – This study provides a novel investigation into herd behaviour in ASEAN-5 foreign exchange market.

This paper analyzes the herding behavior that characterizes lenders' lending decisions on a microloan platform and explains how rational herding behavior can resolve the information-asymmetry problem, which is a well-known reason for the failure of online microloan platforms. Using a set of panel data on individual lending decisions acquired from Paipaidai.com (PPDai), an online microloan platform, we examine the influence of the lending decisions of prominent, experienced lenders on novice lenders to identify rational herding behavior. Our empirical analysis demonstrates that rational herding behavior can in fact efficiently reduce lender loss from borrower defaults caused by limited information. Although it is typically assumed that herding behavior is irrational, we find that it can be rational in this context and can thus shed light on why PPDai has succeeded while most other microloan platforms have failed. Accordingly, we make three key contributions: 1) we use heterogeneous herding effects to empirically determine whether lenders' herding behavior on PPDai is rational based on observational learning; 2) we investigate the moderating effect of borrower credit and novice-lender experience on herding, and we leverage this heterogeneity in lender experience to better explain loan results; and 3) because PPDai publicly provides potential lenders with a transparent credit score—in contrast to platforms like Prosper.com, which leverage hidden proprietary credit information from Experian—we further analyze the credit composition of prominent lenders to better understand the crucial determinants of rational herding. In fact, our follow-up survival simulations indicate that without rational herding, the total number of successful PPDai loans would have decreased by around 46 percent during the study period—a finding that further underlines the crucial influence of rational herding and the unique contextual factors of PPDai that have fostered it. [ABSTRACT FROM AUTHOR]

Purpose – Determining the impact of behavioral influences on the stock market has significant implications for investment analysis and portfolio management. Behavioral biases are parameters that need to be considered in investment decision-making. The purpose of this study is to inform Bangladeshi investors about behavioral biases that they may encounter when making investment decisions in the prevailing frontier environment. Design/methodology/approach – Through the chi-square test, one-way ANOVA, paired-samples t-test and descriptive analysis based on the facts collected from 281 respondents of the Dhaka Stock Exchange (DSE), the study has found that individual investors of Bangladesh often make investment decisions emotionally rather than based on theories. Findings – The result shows that risk aversion and risk perception are the two most influential emotional dimensions that impact investors' decisions. The findings are consistent with the other researchers and highlight the fact that investors hardly act according to the norms recommended in the financial theories. Research limitations/implications – The findings are grounded on a small portion of investors at DSE on some particular days, which is not sufficient to study individual investors' entire complex decision-making behavior from various angles. Many respondents were reluctant and even confused to disclose their behavioral aspects. These, along with biased and careless answers, may impede the identification of the actual scenario of the behavioral responses in decision-making that demand further study. Originality/value – The novelty of this study is unique in that it examined investors of the DSE, who are considered to be a representative in a frontier market like Bangladesh. Since this market is not very resilient, small investors need to be aware of the biases of behavioral factors to survive.

Bitcoin remains a popular investment choice despite the regulatory obstacles and failures of many crypto firms. This intriguing behavior of investors necessitates calls for more in-depth research. This study explores the underlying motivations behind the intention to invest in Bitcoin by considering inaction regret aversion, overconfidence bias, herding, risk affinity, profit expectancy, perceived ease of investing, and social media influence in shaping the investors’ attitude towards investing in Bitcoin and consequently on behavioral intention to invest in Bitcoin. The study employs PLS-SEM and mediation analysis on a sample of 439 individuals from India with no history of cryptocurrency trading or investment. Path analysis demonstrates that inaction regret aversion, risk affinity, profit expectancy of Bitcoin, perceived ease of investing in Bitcoin, and social media influence are significant positive predictors of attitude toward investing in Bitcoin. Notably, profit expectancy remains the most relevant variable in the stated context. Attitude toward investing in Bitcoin positively and significantly influences the behavioral intention to invest in Bitcoin. The current study also indicates the significance of attitude as a mediator in the mentioned context.

The article discusses the potential for political bias in forensic mental evaluations and publications, particularly when interpreting social media. It highlights the importance of addressing bias in peer-reviewed publications in forensic psychology and psychiatry, as well as the need to control political biases in scholarly work. The text also explores the risk of political bias in forensic practice and the impact of herding bias on perceptions and decisions in the field. The authors emphasize the necessity of addressing political bias in forensic work, especially with the increasing influence of Artificial Intelligence on forensic interpretation of social media. [Extracted from the article]

This study used survey data to measure the benefits of paid herding for small stockholders on the communal rangelands of the eastern Free State. Extensionists can recommend herding to their clients because it mitigated the worst of a recent drought by controlling intermediate consumption and facilitating better recruitment. However, the practice did not impact the size or composition of livestock losses. In drought, livestock holders prioritised off-take over accumulation and selectively shed male animals. Off-take was directed to sales rather than to home consumption. Herding affected the cost of production, with herders saving more than their wages on purchased feed and remedies but not enough to make their herds profitable. [ABSTRACT FROM AUTHOR]

Taking the practices of reindeer ear- and fur-marking in northern European Russia and Western Siberia as its primary focus, this article analyses modifications of informal "traditional" practices as a part of their appropriation by state institutions and highly bureaucratized state-owned enterprises. The practice of making and reading ear- and fur-marks is highly situated and workable only when embedded in a wider web of social communication. Analyzing three cases of the practice in formal institutions, we show that the modifications represent attempts to eliminate the situatedness and embeddedness of the practice. Some modifications can be explained by the attempt to extend the scope of the practice to the level of individuals, but this has made the practice unworkable without reference to special databases and is useless for reindeer herders. [ABSTRACT FROM AUTHOR]

Group-living organisms commonly exhibit collective escape responses, yet how information flows among group members in these events remains an open question. Here, we study the collective responses of a sheep flock (Ovis aries) to a shepherd dog (border collie) in a driving task between two well-defined target points. We collected high-resolution spatiotemporal data from 14 sheep and the dog, using Ultra-Wide-Band tags attached to each individual. We find that the spatial positions of sheep along the front-back axis of the group's velocity strongly correlate with their impact on the collective movement. Our analyses reveal that, even though the dog chases the sheep flock from behind, directional information on shorter time scales propagates from the front of the group towards the rear; further, the dog adjusts its movement in response to the flock's dynamics. We introduce an agent-based model that captures key data features. Specifically, in response to chasing, the sheep change their spatial relative positions less frequently and exhibit a transfer of directional information flow from front to back; this pattern disappears in the absence of chasing. Our study reveals some general insights into how directional information propagates in escaping animal groups. Experimental analysis and computational modeling of collective responses of flocking sheep to a herding dog reveal how directional information spreads in escaping animal groups. [ABSTRACT FROM AUTHOR]

Evolutionary graph theory has considerably advanced the process of modelling the evolution of structured populations, which models the interactions between individuals as pairwise contests. In recent years, these classical evolution models have been extended to incorporate more realistic features, e.g. multiplayer games. A recent series of papers have developed a new evolutionary framework including structure, multiplayer interactions, evolutionary dynamics, and movement. However, so far, the developed models have mainly considered independent movement without coordinated behaviour. Although the theory underlying the framework has been developed and explored in various directions, several movement mechanisms have been produced which characterise coordinated movement, for example, herding. By embedding these newly constructed movement distributions, within the evolutionary setting of the framework, we demonstrate that certain levels of aggregation and dispersal benefit specific types of individuals. Moreover, by extending existing parameters within the framework, we are not only able to develop a general process of embedding any of the considered movement distributions into the evolutionary setting on complete graphs but also analytically produce the probability of fixation of a mutant on a complete N-sized network, for the multiplayer Public Goods and Hawk–Dove games. Also, by applying weak selection methods, we extended existing previous analyses on the pairwise Hawk–Dove Game to encompass the multiplayer version considered in this paper. By producing neutrality and equilibrium conditions, we show that hawks generally do worse in our models due to the multiplayer nature of the interactions. [ABSTRACT FROM AUTHOR]

It is well-believed that most trading activities tend to herd. Herding is an important topic in finance. It implies a violation of efficient markets and hence, suggests possibly predictable trading profits. However, it is hard to test such a hypothesis using aggregated data (as in the literature). In this paper, we obtain a proprietary data set that contains detailed trading information, and as a result, for the first time it allows us to validate this hypothesis. The data set contains all trades transacted in 2019 by all the brokers/dealers across all locations in Taiwan of all the equities (stocks, warrants, and ETFs). Given such data, in this paper, we use swarm intelligence to identify such herding behavior. In particular, we use two versions of swarm intelligence—Boids and PSO (particle swarm optimization)—to study the herding behavior. Our results indicate weak swarm among brokers/dealers. [ABSTRACT FROM AUTHOR]

This study is the first to examine herding and reverse herding in US metropolitan housing markets based on Zillow ZIP-level house price indices. Reverse herding is found to be more prevalent than herding, which differs markedly from equity markets and outcomes derived from less granular house price indices. The results suggest that the interaction between price appreciation and overconfidence may drive reverse herding. Also, herding and reverse herding show strong dependency on market conditions. Wide spatial and temporal variation in herding and reverse herding suggests the importance of local characteristics as determinants of the rationality of market responses. [ABSTRACT FROM AUTHOR]

In this paper, a coherent detection optical OFDM (CO-OFDM) communication system is designed to provide 40 Gbps downstream signaling using Optisystem and MATLAB software. First, the classical Partial Transmission Sequence (PTS) technique is applied to the CO-OFDM system to reduce the Peak-to-Average Power Ratio (PAPR). Then, to further reduce the PAPR of the CO-OFDM signal, the PTS system is integrated with Discrete Invasive Weed Optimization (DIWO) to obtain optimized phase weighting factors, resulting in DIWO-PTS. The performance of DIWO-PTS is compared with that of Discrete Elephant Herding Optimization-PTS (DEHO-PTS) and Discrete Crow Search Algorithm-PTS (DCSA-PTS). Simulation results show that DIWO-PTS is the best technique in terms of BER performance and achieves minimum PAPR compared to DEHO-PTS and DCSA-PTS using the same number of searches. According to the simulation results, after applying DIWO-PTS to the CO-OFDM system, the PAPR at CCDF = 10–3 is reduced from 10.42 dB to 5.85 dB, a reduction of 4.57 dB, whereas DCSA-PTS has a PAPR of 5.94 dB, a reduction of 4.48 dB, and DEHO-PTS has a PAPR of 6.03 dB, a reduction of 4.39 dB. [ABSTRACT FROM AUTHOR]

Attention to environmental, social, and governance (ESG) investing has grown in recent years. Even after the SARS-CoV-2 (COVID-19) global pandemic, there has been a rise in financial instruments that are structured according to certain prescribed "sustainable finance" objectives. From a risk management perspective, and as we continue to see a rise in inflows into such instruments, it is important to appreciate that ESG markets will have a growing influence on our financial system and its development. In light of this, and using a sample of some of the most common and popular US-based ESG index funds, this study explores the extent to which herding behaviors are present in such markets. From a regulatory point of view, such behaviors are important to identify, given that they can lead to excess price volatility, bubbles, and other such market-destabilizing phenomena. In addition, this study builds a framework for exploring whether Twitter-based economic uncertainty, which is arguably a forward-looking indicator of investors' expectations, can exacerbate herding behaviors in ESG markets. Overall, this study shows the following: (i) herding behaviors are present in ESG markets; (ii) rises in Twitter economic uncertainty can potentially exacerbate such herding; (iii) although ESG funds, like traditional asset classes, generally show a negative risk–return tradeoff, this can be driven by changes in Twitter economic uncertainty. [ABSTRACT FROM AUTHOR]

We consider social learning in a changing world. With changing states, societies can be responsive only if agents regularly act upon fresh information, which significantly limits the value of observational learning. When the state is close to persistent, a consensus whereby most agents choose the same action typically emerges. However, the consensus action is not perfectly correlated with the state, because societies exhibit inertia following state changes. When signals are precise enough, learning is incomplete, even if agents draw large samples of past actions, as actions then become too correlated within samples, thereby reducing informativeness and welfare. [ABSTRACT FROM AUTHOR]

This study investigates the industry herding of mutual funds traded in Turkey and the effects of industry herding on industry valuations. Using a sample of monthly portfolio holdings of 37 equity-intensive mutual funds traded in Borsa Istanbul (BIST), we employ the LSV and Sias herding measures. We find significant industry herding with the LSV measure and no overall industry herding with the Sias measure. We show that fund flows of underlying investors, individual stock herding, and the investing style of the mutual funds are not relevant drivers of industry herding. Furthermore, we document that industry herding is not a factor that destabilizes industry returns. These findings are especially crucial for investors who trade in concentrated markets since they raise questions regarding aspects such as the lower number of investors and stocks, as well as the information content of industry components, which have been claimed to have an impact on herding behavior in such a setting. [ABSTRACT FROM AUTHOR]

In the past two decades, there has been a decline in the use of uniform-price auctions in favor of fixed prices in markets of peer-to-peer lending, equity crowdfunding, and initial public offerings. This article aims to analytically study why this trend might be occurring. The analysis reveals that, relative to a fixed price, a uniform-price auction leads to more herding and strategic delay of bid submission and, consequently, a smaller transaction completion probability and lower expected revenue. These predictions are consistent with the empirical regularities observed for the bidding behavior and funding outcomes on Prosper, one of the leading peer-to-peer online lending platforms, and those documented in the literature for markets of equity crowdfunding and initial public offerings. [ABSTRACT FROM AUTHOR]

Abstract Although the 2022 cryptocurrency market crash prompted despair among investors, the rallying cry, “wagmi” (We’re all gonna make it.) emerged among cryptocurrency enthusiasts in the aftermath. Did cryptocurrency enthusiasts respond to this crash differently compared to traditional investors? Using natural language processing techniques applied to Twitter data, this study employed a difference-in-differences method to determine whether the cryptocurrency market crash had a differential effect on investor sentiment toward cryptocurrency enthusiasts relative to more traditional investors. The results indicate that the crash affected investor sentiment among cryptocurrency enthusiastic investors differently from traditional investors. In particular, cryptocurrency enthusiasts’ tweets became more neutral and, surprisingly, less negative. This result appears to be primarily driven by a deliberate, collectivist effort to promote positivity within the cryptocurrency community (“wagmi”). Considering the more nuanced emotional content of tweets, it appears that cryptocurrency enthusiasts expressed less joy and surprise in the aftermath of the cryptocurrency crash than traditional investors. Moreover, cryptocurrency enthusiasts tweeted more frequently after the cryptocurrency crash, with a relative increase in tweet frequency of approximately one tweet per day. An analysis of the specific textual content of tweets provides evidence of herding behavior among cryptocurrency enthusiasts.

The study aims to determine the influence of behavioural biases on financial risk propensity. It also attempts to examine the influence of financial risk propensity on investment decisions and the mediational role of financial risk propensity on the relationship between behavioural biases and investment decisions. A survey by questionnaire method is adopted to collect data from 203 respondents using the purposive sampling technique among the investors. The study has found that prospect, herding, and heuristics dimensions of behavioural bias have a significant impact on financial risk propensity, and in turn, financial risk propensity has a significant impact on investment decisions. The results of the study can help to develop more realistic investment valuation models in light of the revised risk-return expectations of investors who act contrary to the traditional concept of rational utility maximisers.

The options trader’s decisions are expected to be rational decisions but an element of irrationality is observed in decision making. The Disposition effect is the behavioral aspect of an investor which explains his irrational decision-making. The disposition effect is the tendency to keep losing positions too long and selling winning positions too early. The present research work studies the disposition effect in options trading. Options are derivatives of underlying assets which give the holder the right to exercise them at a given date and price. In this research work, elements of disposition effect namely,Herding (HE), Mental accounting (MA), Risk Aversion (RA) are studied along with Trade enablers (TE) and Cost consciousness (CC). The data was collected from 250 respondents’ trading options on the National Stock Exchange, India. The collected data was analyzed using Structured Equation Modeling (SEM). The results reflected that the disposition effect existed in decision-making by options traders. Trade Enabler consisting of Time decay and Open Interest, and Herding emerged as significant elements of disposition effect for options trading. Mental accounting, risk aversion, and cost-consciousness emerged as less significant elements affecting the disposition effect in options trading.

Although the 2022 cryptocurrency market crash prompted despair among investors, the rallying cry, "wagmi" (We're all gonna make it.) emerged among cryptocurrency enthusiasts in the aftermath. Did cryptocurrency enthusiasts respond to this crash differently compared to traditional investors? Using natural language processing techniques applied to Twitter data, this study employed a difference-in-differences method to determine whether the cryptocurrency market crash had a differential effect on investor sentiment toward cryptocurrency enthusiasts relative to more traditional investors. The results indicate that the crash affected investor sentiment among cryptocurrency enthusiastic investors differently from traditional investors. In particular, cryptocurrency enthusiasts' tweets became more neutral and, surprisingly, less negative. This result appears to be primarily driven by a deliberate, collectivist effort to promote positivity within the cryptocurrency community ("wagmi"). Considering the more nuanced emotional content of tweets, it appears that cryptocurrency enthusiasts expressed less joy and surprise in the aftermath of the cryptocurrency crash than traditional investors. Moreover, cryptocurrency enthusiasts tweeted more frequently after the cryptocurrency crash, with a relative increase in tweet frequency of approximately one tweet per day. An analysis of the specific textual content of tweets provides evidence of herding behavior among cryptocurrency enthusiasts. [ABSTRACT FROM AUTHOR]

We build a model of equity crowdfunding that incorporates the two major funding models: all‐or‐nothing (AoN) and keep‐it‐all (KIA). Both informed and uninformed investors arrive sequentially and rationally choose whether and how much to invest. The KIA solution turns out to be a reduced version of AoN without signalling. We test predictions using data from a leading European equity crowdfunding platform and find support. Results are consistent with rational information aggregation. However, negative information cascades may still appear. The AoN crowdfunding mechanism might therefore fail to finance a nonnegligible percentage of positive NPV projects. [ABSTRACT FROM AUTHOR]

• We assess the impact of herding/anti-herding on stock-bond correlations in the US. • We find that corporate bonds exhibit herding and stocks anti-herding. • Both these patterns dampen the correlation between US stocks and corporate bonds. • This effect is largely noise-driven in nature. • High uncertainty, optimism and economic outperformance strengthen this effect. We examine investors' herding/anti-herding behavior in the US stock and corporate bond markets and their impact on stock-bond return correlation. Corporate bonds exhibit herding, with stocks displaying anti-herding. Bond herding and stock anti-herding are weakly related, with each significantly dampening the stock-bond return correlation. This effect is largely driven by their irrational components, affecting mostly the correlation of noise-driven stock and bond return elements, more so during periods of elevated uncertainty, optimistic sentiment and excessively positive economic performance. As the irrational forces in each asset class (stocks; bonds) countervail each other, this implies greater stability and resilience for the financial system. [ABSTRACT FROM AUTHOR]

The negative herding effect tends to cause the spread of negative emotions among netizens, resulting in significant public opinion crises. Therefore, linking the negative herding effect and online public opinion, we aim to exploring the connection between netizens' emotions, opinions, and the negative herding effect. To better distinguish the emotions in texts, a new BiGADG (Bidirectional Gated recurrent unit based on Attention with Distance‐based dependency syntax Graph convolutional network) model is proposed in this article. This model includes primarily the proposed dependency syntax based on dependency distance, Bidirectional Gated Recurrent Unit (BiGRU), multi‐head self‐attention and Graph Convolutional Network (GCN). Particularly, the dependency syntax based on dependency distances incorporates word‐to‐word dependency distances into the traditional dependency syntax, which enriches the syntactic structural features of the text. After the experiments, the accuracy of BiGADG model is 86.53%, which is 3.11% higher compared to BERT model. It is evident that our model for sentiment classification has been improved. Based on the results of sentiment classification, we investigate the existence of negative herding behaviour and its underlying motivation in online public opinion. We have found that the negative herding effect, if not effectively managed, may trigger large‐scale and uncontrollable public opinion crises. [ABSTRACT FROM AUTHOR]

This paper explores the role of the COVID-19 pandemic on the herding behaviour across market participants in the Croatian market. The analysis uses daily prices of the Croatian stock index, spanning the period January 2016 to December 2022. The hypothesis of the herding behaviour is tested through the quantile regression approach. The findings document no evidence of herding prior to the pandemic crisis. In contrast, herding is discovered during the COVID-19 period. The paper provides policymakers and investors with valuable information to draw significant measures in their investment portfolio management during crises and pandemics. [ABSTRACT FROM AUTHOR]

In the age of Business 4.0, cryptocurrencies have emerged as a popular alternative investment vehicle. Despite significant risks, they offer attractive perks. Poor decision-making can lead to investment losses, prompting this study to explore factors influencing cryptocurrency investment decisions. Using a quantitative methodology, data was collected from 106 respondents through questionnaires on popular bitcoin brokerage forums. The analysis employed structural equation modeling partial least squares with Smart PLS 4 software. Multiple group analysis was conducted based on investment experience (less than two years vs. more than two years). The results show that risk tolerance significantly affects investment decisions in cryptocurrency. For respondents with over two years of experience, heuristic bias impacts both risk tolerance and investment decisions, while herding behavior only affects risk tolerance. For those with less than two years of experience, heuristic bias influences investment decisions but not risk tolerance, and herding behavior has no significant effect on either. [ABSTRACT FROM AUTHOR]

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In the European north, there is a growing trend for Sámi reindeer herding communities to enter negotiated agreements with developers on projects that aim to exploit land and natural resources. This paper offers, for the first time, an evaluation of the content of a selection of these agreements, drawing on a sample of 15 agreements from five communities in Sweden. The evaluation was conducted from a Sámi perspective on how the agreements affect the ability of herding communities to safeguard reindeer wellbeing. The overall conclusion is that the agreements provide some positive contributions to mitigate harm to the reindeer, but also contribute considerable risks. We argue that agreements might have a meaningful role to play in the integration of Sámi rights in land and resource decisions, but herding communities have considerable space to increase the range of clauses – guided by larger goals of Sámi self-determination. [ABSTRACT FROM AUTHOR]