It is generally accepted that herding behavior and overconfidence behavior are unrelated or even mutually exclusive.However,these behaviors can both lead to some similar market anomalies,such as excessive trading volu...It is generally accepted that herding behavior and overconfidence behavior are unrelated or even mutually exclusive.However,these behaviors can both lead to some similar market anomalies,such as excessive trading volume and volatility in the stock market.Due to the limitation of traditional time series analysis,we try to study whether there exists network relevance between the investor’s herding behavior and overconfidence behavior based on the complex network method.Since the investor’s herding behavior is based on market trends and overconfidence behavior is based on past performance,we convert the time series data of market trends into a market network and the time series data of the investor’s past judgments into an investor network.Then,we update these networks as new information arrives at the market and show the weighted in-degrees of the nodes in the market network and the investor network can represent the herding degree and the confidence degree of the investor,respectively.Using stock transaction data of Microsoft,US S&P 500 stock index,and China Hushen 300 stock index,we update the two networks and find that there exists a high similarity of network topological properties and a significant correlation of node parameter sequences between the market network and the investor network.Finally,we theoretically derive and conclude that the investor’s herding degree and confidence degree are highly related to each other when there is a clear market trend.展开更多
This study examines herding behavior in the Pakistani Stock Market under different market conditions,focusing on the Ramadan effect and Crisis period by using data from 2004 to 2014.Two regression models of Christie a...This study examines herding behavior in the Pakistani Stock Market under different market conditions,focusing on the Ramadan effect and Crisis period by using data from 2004 to 2014.Two regression models of Christie and Huang(Financ Analysts J 51:31-37,1995)and Chang et al.,(J Bank Finance 24:1651-1679,2000)are used for herding estimations.Results based on daily stock data reveal that there is an absence of herding behavior during rising(up)and falling(down)market as well as during high and low volatility in market.While herding behavior is detected during low trading volume days.Yearly analysis shows that herding existed during 2005,2006 and 2007,while it is not evident during rest of the period.However,herding behavior is not detected during Ramadan.Furthermore,during financial crisis of 2007-08,Pakistani Stock Market exhibits herding behavior due to higher uncertainty and information asymmetry.展开更多
This study investigates speculative bubbles in the cryptocurrency market and factors affecting bubbles during the COVID-19 pandemic.Our results indicate that each cryptocurrency covered in the study presented bubbles....This study investigates speculative bubbles in the cryptocurrency market and factors affecting bubbles during the COVID-19 pandemic.Our results indicate that each cryptocurrency covered in the study presented bubbles.Moreover,we found that explosive behavior in one currency leads to explosivity in other cryptocurrencies.During the pandemic,herd behavior was evident among investors;however,this diminishes during bubbles,indicating that bubbles are not explained by herd behavior.Regarding cryptocurrency and market-specific factors,we found that Google Trends and volume are positively associated with predicting speculative bubbles in time-series and panel probit regressions.Hence,investors should exercise caution when investing in cryptocurrencies and follow both crypto currency and market-related factors to estimate bubbles.Alternative liquidity,volatility,and Google Trends measures are used for robustness analysis and yield similar results.Overall,our results suggest that bubble behavior is common in the cryptocurrency market,contradicting the efficient market hypothesis.展开更多
This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange(CME).The database extends from December 2017 to October 2020,taking as a ref...This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange(CME).The database extends from December 2017 to October 2020,taking as a reference the main exchanges that trade bitcoin(Binance,Bitfinex,Bitstamp,Coinbase,itBit,Kraken,and Gemini)and using hourly closing prices and trading volumes in bitcoin and US dollars.Adapting the proposal of Chang,Cheng and Khorana(2000)(CCK)to test conditional herding,we obtain results that indicate that the herding effect is significant during the week before expiration.After expiration,the herding effect lasts for a few hours and disappears.Information overload originating,among other causes,from sophisticated investors’strategies may generate this mimetic behaviour.The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows,in general,anti-herding behaviour throughout the period of study.展开更多
This paper explores some behavioral factors that may explain the formation of speculative bubbles in financial markets. The study adopts an experimental approach focused on the agents’ behavior when facing a “true...This paper explores some behavioral factors that may explain the formation of speculative bubbles in financial markets. The study adopts an experimental approach focused on the agents’ behavior when facing a “true” bubble and is incentivized to herd and/or receive information about the market sentiment. For this purpose, a straightforward laboratory experiment that reproduces the dotcom market bubble and asks subjects to forecast asset prices in a true dynamic information scenario. The experiment was conducted in the laboratory of the Faculty of Economics at the University of Salamanca and involved 137 undergraduate students in the degree of economics. The results show that incentives to the herding behavior increase the forecasted volatility and thus contribute to the bubble inflation. Nevertheless, this effect may be offset by giving information to the agents about the expected market trend. Therefore, under herding effects, it is the absence of clear signals about market sentiments what inflates the bubble.展开更多
Herding behavior is an important part of behavioral finance study. In this paper, I focus on the literature reviews of herding behavior along the timeline and explore how it affects our lives. Herding is a double-edge...Herding behavior is an important part of behavioral finance study. In this paper, I focus on the literature reviews of herding behavior along the timeline and explore how it affects our lives. Herding is a double-edged sword with various impacts. I conclude three possible explanations for herding actions based on regret aversion bias, group mind theory and Emergent Norms Theory. The historical evidence on social and economic impact including asset price bubbles, subprime crisis is presented. Although these negative impacts are serious, herding can improve decision-making for people who are less likely to be biased by regret. Herding may also accelerate society's development if we choose the right leader. Finally I would discuss several measures to ease the negative effect of herding behavior.展开更多
This study examines a novel relationship between volatility and dynamic herding behavior during COVID-19 by examining the relationship of oil market volatility,Global volatility and Infectious disease equity market vo...This study examines a novel relationship between volatility and dynamic herding behavior during COVID-19 by examining the relationship of oil market volatility,Global volatility and Infectious disease equity market volatility with time-varying herding behavior in energy stock of Developed markets.Using country level data,this study observes that market switch between anti-herding to herding state during pandemic and all three volatility measures have significant impact on dynamic herding state under high dispersion regime.However,in low dispersion regime only global volatility has significant impact on time-varying herding behavior.This study suggests that the level of speculation in energy sector affect investor behavior;therefore,policy makers should monitor and model possible signals related to health crisis that can be transformed in to financial market crisis.展开更多
Tradable green certificate(TGC)scheme promotes the development of renewable energy industry which currently has a dual effect on economy and environment.TGC market efficiency is reflected in stimulating renewable ener...Tradable green certificate(TGC)scheme promotes the development of renewable energy industry which currently has a dual effect on economy and environment.TGC market efficiency is reflected in stimulating renewable energy investment,but may be reduced by the herding behavior of market players.This paper proposes and simulates an artificial TGC market model which contains heterogeneous agents,communication structure,and regulatory rules to explore the characteristics of herding behavior and its effects on market efficiency.The results show that the evolution of herding behavior reduces information asymmetry and improves market efficiency,especially when the borrowing is allowed.In addition,the fundamental strategy is diffused by herding evolution,but TGC market efficiency may be remarkably reduced by herding with borrowing mechanism.Moreover,the herding behavior may evolve to an equilibrium where the revenue of market players is comparable,thus the fairness in TGC market is improved.展开更多
The high energy cosmic-radiation detection(HERD)facility is planned to launch in 2027 and scheduled to be installed on the China Space Station.It serves as a dark matter particle detector,a cosmic ray instrument,and a...The high energy cosmic-radiation detection(HERD)facility is planned to launch in 2027 and scheduled to be installed on the China Space Station.It serves as a dark matter particle detector,a cosmic ray instrument,and an observatory for high-energy gamma rays.A transition radiation detector placed on one of its lateral sides serves dual purpose,(ⅰ)calibrating HERD's electromagnetic calorimeter in the TeV energy range,and(ⅱ)serving as an independent detector for high-energy gamma rays.In this paper,the prototype readout electronics design of the transition radiation detector is demonstrated,which aims to accurately measure the charge of the anodes using the SAMPA application specific integrated circuit chip.The electronic performance of the prototype system is evaluated in terms of noise,linearity,and resolution.Through the presented design,each electronic channel can achieve a dynamic range of 0–100 fC,the RMS noise level not exceeding 0.15 fC,and the integral nonlinearity was<0.2%.To further verify the readout electronic performance,a joint test with the detector was carried out,and the results show that the prototype system can satisfy the requirements of the detector's scientific goals.展开更多
In recent years,the usage of social networking sites has considerably increased in the Arab world.It has empowered individuals to express their opinions,especially in politics.Furthermore,various organizations that op...In recent years,the usage of social networking sites has considerably increased in the Arab world.It has empowered individuals to express their opinions,especially in politics.Furthermore,various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different scales.This is attributed to business owners’understanding of social media’s importance for business development.However,the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and nouns.Hate speech over online social networking sites turns out to be a worldwide issue that reduces the cohesion of civil societies.In this background,the current study develops a Chaotic Elephant Herd Optimization with Machine Learning for Hate Speech Detection(CEHOML-HSD)model in the context of the Arabic language.The presented CEHOML-HSD model majorly concentrates on identifying and categorising the Arabic text into hate speech and normal.To attain this,the CEHOML-HSD model follows different sub-processes as discussed herewith.At the initial stage,the CEHOML-HSD model undergoes data pre-processing with the help of the TF-IDF vectorizer.Secondly,the Support Vector Machine(SVM)model is utilized to detect and classify the hate speech texts made in the Arabic language.Lastly,the CEHO approach is employed for fine-tuning the parameters involved in SVM.This CEHO approach is developed by combining the chaotic functions with the classical EHO algorithm.The design of the CEHO algorithm for parameter tuning shows the novelty of the work.A widespread experimental analysis was executed to validate the enhanced performance of the proposed CEHOML-HSD approach.The comparative study outcomes established the supremacy of the proposed CEHOML-HSD model over other approaches.展开更多
Herd immunity is often considered a measure to protect a whole community or population from disease if the vaccination threshold is met. Using the demographic and COVID-19 infection data from the state of Pennsylvania...Herd immunity is often considered a measure to protect a whole community or population from disease if the vaccination threshold is met. Using the demographic and COVID-19 infection data from the state of Pennsylvania, United States, the study aimed to determine if herd immunity by vaccination is an effective way to reduce the spread of the COVID-19 virus. The Pennsylvania counties were split into two groups based on qualification of herd immunity: counties that met the COVID-19 herd immunization rate of 70% and counties that did not. The ANOVA test was used to analyze the difference between the groups with and without herd immunity by the COVID-19 vaccine. The results demonstrated that there was no significant statistical difference between counties that did achieve and those that did not achieve the herd immunity threshold for the COVID-19 vaccine. On the other hand, it was observed that there had been a significant decrease in positive cases between 2020 and 2023. This decline can be attributed to the overall protection by the vaccination and adaptability to the disease, not specifically due to herd immunity alone. Ultimately, these outcomes suggest that herd immunity cannot reduce the risk of contracting COVID-19. Increased efforts to get vaccinated should be implemented to protect the general community and a wider scope of age.展开更多
This study uses a dynamic herding model that considers intertemporal and crosssectional correlation to confirm that loan herding occurs among joint-stock commercial banks (JSCBs) and city commercial banks (CCBs). We c...This study uses a dynamic herding model that considers intertemporal and crosssectional correlation to confirm that loan herding occurs among joint-stock commercial banks (JSCBs) and city commercial banks (CCBs). We clarify the motivations for bank loan herding. We find that loan herding by both JSCBs and CCBs results more from following the behavior of other same-type banks than different-type banks because of characteristic herding or reputational concerns. Loan herding by JSCBs is motivated by investigative herding, whereas loan herding by CCBs results from informational cascades. Moreover, loan herding has a significantly harmful impact on the operating performance of CCBs but not JSCBs, which may be explained by the irrational behavior of CCBs. Our results will help Chinese bank supervisors develop appropriate policies for handling loan herding.展开更多
The main intent of this paper is to implement the stability-aware energy-efficient clustering protocol in WSN.This paper plans to derive a multi-objective function with the constraints like energy,distance,delay,stabi...The main intent of this paper is to implement the stability-aware energy-efficient clustering protocol in WSN.This paper plans to derive a multi-objective function with the constraints like energy,distance,delay,stability period,and intents to attain the objective by developing a new well-performing meta-heuristic algorithm called Opposition-based Elephant Herding Optimisa-tion(O-EHO).The objective function diminishes the energy consumption of sensor nodes by optimum selection of cluster heads that leads to maintain the energy balance between the nor-mal nodes.In this way,there is a remarkable enhancement in the performance parameters such as throughput,stability period,and network lifetime.It is proved that the network lifetime is enhanced by the stability period and thus it is considered as the most significant parameter.The experimental analysis proves the competitive performance of the proposed model over other heuristic methods.展开更多
Using the unique scheduled disclosure system for annual reports in China’s stock market,we examine within-industry herding behavior in annual report timing.The results reveal the waiting and following behavior strate...Using the unique scheduled disclosure system for annual reports in China’s stock market,we examine within-industry herding behavior in annual report timing.The results reveal the waiting and following behavior strategies used in the annual reporting process within industry.Firms that originally schedule an early(late)disclosure date within their industry are more likely to reschedule to a later(earlier)date.Informational pressure is the dominant mechanism underlying herding in annual reporting,and capital market reputation incentives mainly induce the herding of bad news.Further analysis shows that delaying disclosure via the waiting strategy reduces the future occurrence of restatements,whereas bringing forward disclosure does not change the propensity of future restatements.Overall,we enrich the limited empirical studies on sequential mandatory disclosure decisions within industry.展开更多
This paper studies the connection between the irrational behavior of traders and the herding equilibrium of informed traders in security market. At first, we set up the trading system on the condition of market maker,...This paper studies the connection between the irrational behavior of traders and the herding equilibrium of informed traders in security market. At first, we set up the trading system on the condition of market maker, establish a trading model of perfectly rational traders, and then define herding equilibrium. Second, we extend the model using two parameters, and find the critical points of irrational traders when they reach the herding equilibrium. The result indicates that herding never occurs in market if all the traders are perfectly rational. If consider their irrational factor, it maybe arouse herding. Besides, along with the number of traders who make the same trading strategies increasing, the two critical points show some rules.展开更多
How does stablecoin design affect market behavior during turbulent periods?Stable-coins attempt to maintain a“stable”peg to the US dollar,but do so with widely varying structural designs.The spectacular collapse of ...How does stablecoin design affect market behavior during turbulent periods?Stable-coins attempt to maintain a“stable”peg to the US dollar,but do so with widely varying structural designs.The spectacular collapse of the TerraUSD(UST)stablecoin and the linked Terra(LUNA)token in May 2022 precipitated a series of reactions across major stablecoins,with some experiencing a fall in value and others gaining value.Using a Baba,Engle,Kraft and Kroner(1990)(BEKK)model,we examine the reaction to this exogenous shock and find significant contagion effects from the UST collapse,likely partially due to herding behavior among traders.We test the varying reactions among stablecoins and find that stablecoin design differences affect the direction,magnitude,and duration of the response to shocks.We discuss the implications for stablecoin developers,exchanges,traders,and regulators.展开更多
Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-wor...Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-work lifetime considerably.Securing WSN is a challenging issue faced by researchers.Trust systems are very helpful in detecting interfering nodes in WSN.Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem.The metaheuristic Elephant Herding Optimizations(EHO)algorithm is formulated based on ele-phant herding in their clans.EHO considers two herding behaviors to solve and enhance optimization problem.Based on Elephant Herd Optimization,a trust-based security method is built in this work.The proposed routing selects routes to destination based on the trust values,thus,finding optimal secure routes for transmitting data.Experimental results have demonstrated the effectiveness of the proposed EHO based routing.The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%,by 1.45%,and by 31.94%than LEACH,Elephant Herd Optimization,and Trust LEACH,respec-tively at Number of Nodes 3000.As the proposed routing is efficient in selecting secure routes,the average packet loss rate is significantly reduced,improving the network’s performance.It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.展开更多
基金Project supported by the Youth Program of the National Social Science Foundation of China(Grant No.18CJY057)。
文摘It is generally accepted that herding behavior and overconfidence behavior are unrelated or even mutually exclusive.However,these behaviors can both lead to some similar market anomalies,such as excessive trading volume and volatility in the stock market.Due to the limitation of traditional time series analysis,we try to study whether there exists network relevance between the investor’s herding behavior and overconfidence behavior based on the complex network method.Since the investor’s herding behavior is based on market trends and overconfidence behavior is based on past performance,we convert the time series data of market trends into a market network and the time series data of the investor’s past judgments into an investor network.Then,we update these networks as new information arrives at the market and show the weighted in-degrees of the nodes in the market network and the investor network can represent the herding degree and the confidence degree of the investor,respectively.Using stock transaction data of Microsoft,US S&P 500 stock index,and China Hushen 300 stock index,we update the two networks and find that there exists a high similarity of network topological properties and a significant correlation of node parameter sequences between the market network and the investor network.Finally,we theoretically derive and conclude that the investor’s herding degree and confidence degree are highly related to each other when there is a clear market trend.
文摘This study examines herding behavior in the Pakistani Stock Market under different market conditions,focusing on the Ramadan effect and Crisis period by using data from 2004 to 2014.Two regression models of Christie and Huang(Financ Analysts J 51:31-37,1995)and Chang et al.,(J Bank Finance 24:1651-1679,2000)are used for herding estimations.Results based on daily stock data reveal that there is an absence of herding behavior during rising(up)and falling(down)market as well as during high and low volatility in market.While herding behavior is detected during low trading volume days.Yearly analysis shows that herding existed during 2005,2006 and 2007,while it is not evident during rest of the period.However,herding behavior is not detected during Ramadan.Furthermore,during financial crisis of 2007-08,Pakistani Stock Market exhibits herding behavior due to higher uncertainty and information asymmetry.
文摘This study investigates speculative bubbles in the cryptocurrency market and factors affecting bubbles during the COVID-19 pandemic.Our results indicate that each cryptocurrency covered in the study presented bubbles.Moreover,we found that explosive behavior in one currency leads to explosivity in other cryptocurrencies.During the pandemic,herd behavior was evident among investors;however,this diminishes during bubbles,indicating that bubbles are not explained by herd behavior.Regarding cryptocurrency and market-specific factors,we found that Google Trends and volume are positively associated with predicting speculative bubbles in time-series and panel probit regressions.Hence,investors should exercise caution when investing in cryptocurrencies and follow both crypto currency and market-related factors to estimate bubbles.Alternative liquidity,volatility,and Google Trends measures are used for robustness analysis and yield similar results.Overall,our results suggest that bubble behavior is common in the cryptocurrency market,contradicting the efficient market hypothesis.
文摘This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange(CME).The database extends from December 2017 to October 2020,taking as a reference the main exchanges that trade bitcoin(Binance,Bitfinex,Bitstamp,Coinbase,itBit,Kraken,and Gemini)and using hourly closing prices and trading volumes in bitcoin and US dollars.Adapting the proposal of Chang,Cheng and Khorana(2000)(CCK)to test conditional herding,we obtain results that indicate that the herding effect is significant during the week before expiration.After expiration,the herding effect lasts for a few hours and disappears.Information overload originating,among other causes,from sophisticated investors’strategies may generate this mimetic behaviour.The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows,in general,anti-herding behaviour throughout the period of study.
文摘This paper explores some behavioral factors that may explain the formation of speculative bubbles in financial markets. The study adopts an experimental approach focused on the agents’ behavior when facing a “true” bubble and is incentivized to herd and/or receive information about the market sentiment. For this purpose, a straightforward laboratory experiment that reproduces the dotcom market bubble and asks subjects to forecast asset prices in a true dynamic information scenario. The experiment was conducted in the laboratory of the Faculty of Economics at the University of Salamanca and involved 137 undergraduate students in the degree of economics. The results show that incentives to the herding behavior increase the forecasted volatility and thus contribute to the bubble inflation. Nevertheless, this effect may be offset by giving information to the agents about the expected market trend. Therefore, under herding effects, it is the absence of clear signals about market sentiments what inflates the bubble.
文摘Herding behavior is an important part of behavioral finance study. In this paper, I focus on the literature reviews of herding behavior along the timeline and explore how it affects our lives. Herding is a double-edged sword with various impacts. I conclude three possible explanations for herding actions based on regret aversion bias, group mind theory and Emergent Norms Theory. The historical evidence on social and economic impact including asset price bubbles, subprime crisis is presented. Although these negative impacts are serious, herding can improve decision-making for people who are less likely to be biased by regret. Herding may also accelerate society's development if we choose the right leader. Finally I would discuss several measures to ease the negative effect of herding behavior.
文摘This study examines a novel relationship between volatility and dynamic herding behavior during COVID-19 by examining the relationship of oil market volatility,Global volatility and Infectious disease equity market volatility with time-varying herding behavior in energy stock of Developed markets.Using country level data,this study observes that market switch between anti-herding to herding state during pandemic and all three volatility measures have significant impact on dynamic herding state under high dispersion regime.However,in low dispersion regime only global volatility has significant impact on time-varying herding behavior.This study suggests that the level of speculation in energy sector affect investor behavior;therefore,policy makers should monitor and model possible signals related to health crisis that can be transformed in to financial market crisis.
基金supported by the Beijing Municipal Social Science Foundation(No.16JDYJB031)the Fundamental Research Funds for the Central Universities(No.2020YJ008).
文摘Tradable green certificate(TGC)scheme promotes the development of renewable energy industry which currently has a dual effect on economy and environment.TGC market efficiency is reflected in stimulating renewable energy investment,but may be reduced by the herding behavior of market players.This paper proposes and simulates an artificial TGC market model which contains heterogeneous agents,communication structure,and regulatory rules to explore the characteristics of herding behavior and its effects on market efficiency.The results show that the evolution of herding behavior reduces information asymmetry and improves market efficiency,especially when the borrowing is allowed.In addition,the fundamental strategy is diffused by herding evolution,but TGC market efficiency may be remarkably reduced by herding with borrowing mechanism.Moreover,the herding behavior may evolve to an equilibrium where the revenue of market players is comparable,thus the fairness in TGC market is improved.
基金supported by the National Natural Science Foundation of China(Nos.12375193,11975292,11875304)the CAS“Light of West China”Program+1 种基金the Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.GJJSTD20210009)the CAS Pioneer Hundred Talent Program。
文摘The high energy cosmic-radiation detection(HERD)facility is planned to launch in 2027 and scheduled to be installed on the China Space Station.It serves as a dark matter particle detector,a cosmic ray instrument,and an observatory for high-energy gamma rays.A transition radiation detector placed on one of its lateral sides serves dual purpose,(ⅰ)calibrating HERD's electromagnetic calorimeter in the TeV energy range,and(ⅱ)serving as an independent detector for high-energy gamma rays.In this paper,the prototype readout electronics design of the transition radiation detector is demonstrated,which aims to accurately measure the charge of the anodes using the SAMPA application specific integrated circuit chip.The electronic performance of the prototype system is evaluated in terms of noise,linearity,and resolution.Through the presented design,each electronic channel can achieve a dynamic range of 0–100 fC,the RMS noise level not exceeding 0.15 fC,and the integral nonlinearity was<0.2%.To further verify the readout electronic performance,a joint test with the detector was carried out,and the results show that the prototype system can satisfy the requirements of the detector's scientific goals.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R263)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.This study is supported via funding from Prince Sattam bin Abdulaziz University Project Number(PSAU/2024/R/1445).
文摘In recent years,the usage of social networking sites has considerably increased in the Arab world.It has empowered individuals to express their opinions,especially in politics.Furthermore,various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different scales.This is attributed to business owners’understanding of social media’s importance for business development.However,the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and nouns.Hate speech over online social networking sites turns out to be a worldwide issue that reduces the cohesion of civil societies.In this background,the current study develops a Chaotic Elephant Herd Optimization with Machine Learning for Hate Speech Detection(CEHOML-HSD)model in the context of the Arabic language.The presented CEHOML-HSD model majorly concentrates on identifying and categorising the Arabic text into hate speech and normal.To attain this,the CEHOML-HSD model follows different sub-processes as discussed herewith.At the initial stage,the CEHOML-HSD model undergoes data pre-processing with the help of the TF-IDF vectorizer.Secondly,the Support Vector Machine(SVM)model is utilized to detect and classify the hate speech texts made in the Arabic language.Lastly,the CEHO approach is employed for fine-tuning the parameters involved in SVM.This CEHO approach is developed by combining the chaotic functions with the classical EHO algorithm.The design of the CEHO algorithm for parameter tuning shows the novelty of the work.A widespread experimental analysis was executed to validate the enhanced performance of the proposed CEHOML-HSD approach.The comparative study outcomes established the supremacy of the proposed CEHOML-HSD model over other approaches.
文摘Herd immunity is often considered a measure to protect a whole community or population from disease if the vaccination threshold is met. Using the demographic and COVID-19 infection data from the state of Pennsylvania, United States, the study aimed to determine if herd immunity by vaccination is an effective way to reduce the spread of the COVID-19 virus. The Pennsylvania counties were split into two groups based on qualification of herd immunity: counties that met the COVID-19 herd immunization rate of 70% and counties that did not. The ANOVA test was used to analyze the difference between the groups with and without herd immunity by the COVID-19 vaccine. The results demonstrated that there was no significant statistical difference between counties that did achieve and those that did not achieve the herd immunity threshold for the COVID-19 vaccine. On the other hand, it was observed that there had been a significant decrease in positive cases between 2020 and 2023. This decline can be attributed to the overall protection by the vaccination and adaptability to the disease, not specifically due to herd immunity alone. Ultimately, these outcomes suggest that herd immunity cannot reduce the risk of contracting COVID-19. Increased efforts to get vaccinated should be implemented to protect the general community and a wider scope of age.
文摘This study uses a dynamic herding model that considers intertemporal and crosssectional correlation to confirm that loan herding occurs among joint-stock commercial banks (JSCBs) and city commercial banks (CCBs). We clarify the motivations for bank loan herding. We find that loan herding by both JSCBs and CCBs results more from following the behavior of other same-type banks than different-type banks because of characteristic herding or reputational concerns. Loan herding by JSCBs is motivated by investigative herding, whereas loan herding by CCBs results from informational cascades. Moreover, loan herding has a significantly harmful impact on the operating performance of CCBs but not JSCBs, which may be explained by the irrational behavior of CCBs. Our results will help Chinese bank supervisors develop appropriate policies for handling loan herding.
文摘The main intent of this paper is to implement the stability-aware energy-efficient clustering protocol in WSN.This paper plans to derive a multi-objective function with the constraints like energy,distance,delay,stability period,and intents to attain the objective by developing a new well-performing meta-heuristic algorithm called Opposition-based Elephant Herding Optimisa-tion(O-EHO).The objective function diminishes the energy consumption of sensor nodes by optimum selection of cluster heads that leads to maintain the energy balance between the nor-mal nodes.In this way,there is a remarkable enhancement in the performance parameters such as throughput,stability period,and network lifetime.It is proved that the network lifetime is enhanced by the stability period and thus it is considered as the most significant parameter.The experimental analysis proves the competitive performance of the proposed model over other heuristic methods.
基金financial support from the National Social Science Foundation of China(16BGL004)
文摘Using the unique scheduled disclosure system for annual reports in China’s stock market,we examine within-industry herding behavior in annual report timing.The results reveal the waiting and following behavior strategies used in the annual reporting process within industry.Firms that originally schedule an early(late)disclosure date within their industry are more likely to reschedule to a later(earlier)date.Informational pressure is the dominant mechanism underlying herding in annual reporting,and capital market reputation incentives mainly induce the herding of bad news.Further analysis shows that delaying disclosure via the waiting strategy reduces the future occurrence of restatements,whereas bringing forward disclosure does not change the propensity of future restatements.Overall,we enrich the limited empirical studies on sequential mandatory disclosure decisions within industry.
基金This project is supported by National Natural Science Foundation of China(70371063)
文摘This paper studies the connection between the irrational behavior of traders and the herding equilibrium of informed traders in security market. At first, we set up the trading system on the condition of market maker, establish a trading model of perfectly rational traders, and then define herding equilibrium. Second, we extend the model using two parameters, and find the critical points of irrational traders when they reach the herding equilibrium. The result indicates that herding never occurs in market if all the traders are perfectly rational. If consider their irrational factor, it maybe arouse herding. Besides, along with the number of traders who make the same trading strategies increasing, the two critical points show some rules.
基金funding agencies in the public,commercial,or not-for-profit sectors.Luca Galati was founded by the Rozetta Institute(formerly CMCRC-SIRCA),55 Harrington St,The Rocks,Sydney,NSW 2000,Australia.
文摘How does stablecoin design affect market behavior during turbulent periods?Stable-coins attempt to maintain a“stable”peg to the US dollar,but do so with widely varying structural designs.The spectacular collapse of the TerraUSD(UST)stablecoin and the linked Terra(LUNA)token in May 2022 precipitated a series of reactions across major stablecoins,with some experiencing a fall in value and others gaining value.Using a Baba,Engle,Kraft and Kroner(1990)(BEKK)model,we examine the reaction to this exogenous shock and find significant contagion effects from the UST collapse,likely partially due to herding behavior among traders.We test the varying reactions among stablecoins and find that stablecoin design differences affect the direction,magnitude,and duration of the response to shocks.We discuss the implications for stablecoin developers,exchanges,traders,and regulators.
文摘Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-work lifetime considerably.Securing WSN is a challenging issue faced by researchers.Trust systems are very helpful in detecting interfering nodes in WSN.Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem.The metaheuristic Elephant Herding Optimizations(EHO)algorithm is formulated based on ele-phant herding in their clans.EHO considers two herding behaviors to solve and enhance optimization problem.Based on Elephant Herd Optimization,a trust-based security method is built in this work.The proposed routing selects routes to destination based on the trust values,thus,finding optimal secure routes for transmitting data.Experimental results have demonstrated the effectiveness of the proposed EHO based routing.The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%,by 1.45%,and by 31.94%than LEACH,Elephant Herd Optimization,and Trust LEACH,respec-tively at Number of Nodes 3000.As the proposed routing is efficient in selecting secure routes,the average packet loss rate is significantly reduced,improving the network’s performance.It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.