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 enthusia...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.展开更多
This study explains the role of economic uncertainty as a bridge between business cycles and investors’herding behavior.Starting with a conventional stochastic differential equation representing the evolution of stoc...This study explains the role of economic uncertainty as a bridge between business cycles and investors’herding behavior.Starting with a conventional stochastic differential equation representing the evolution of stock returns,we provide a simple theoretical model and empirically demonstrate it.Specifically,the growth rate of gross domestic product and the power law exponent are used as proxies for business cycles and herding behavior,respectively.We find stronger herding behavior during recessions than during booms.We attribute this to economic uncertainty,which leads to strong behavioral bias in the stock market.These findings are consistent with the predictions of the quantum model.展开更多
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
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
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 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
Activity 1 Think about the following questions and write down your answers before reading the text.1.What are some possible ways animals can survive without access to fresh water sources?2.What other factors besides w...Activity 1 Think about the following questions and write down your answers before reading the text.1.What are some possible ways animals can survive without access to fresh water sources?2.What other factors besides water could contribute to the thriving(茁壮成长)of a herd of goats on an isolated island?展开更多
Peste des petits ruminants virus (PPRV) antibodies were studied in Sudanese sheep and goats (n = 855) before and after vaccination with a locally produced Nigeria 75/1 vaccine using a commercial competitive ELISA (cEL...Peste des petits ruminants virus (PPRV) antibodies were studied in Sudanese sheep and goats (n = 855) before and after vaccination with a locally produced Nigeria 75/1 vaccine using a commercial competitive ELISA (cELISA) kit. Animals were kept healthy under field conditions, in four states: Blue Nile (n = 250), North Kordofan (n = 189), South Darfur (n = 225) and the Northern State (n = 191). Before vaccination, the overall sero-prevalence of PPRV antibodies was 54.6% (53.2% - 56%, 95% CI);high (64.8% - 76.4%, 95% CI) in Blue Nile State, medium (50.5% - 61.9%, 95% CI) in North Kordofan State and South Darfur State and low (28.6% - 35.2% 95%, CI) in Northern State. In high-risk areas (high sero-prevalence), Blue Nile (70.4%) and North Kordofan (57.7%), middle age groups (7 - 12 and 13 - 18 months) were identified as high-risk age. Middle age groups showed lower sero-prevalence than preceding (3 - 6 months) and subsequent (>18 months) age groups while the risk of exposure increased with age. Current and previous findings suggested a transmission pathway of PPRV involving the South Eastern border (Blue Nile) and neighbouring Central Sudan to North Kordofan. One month after vaccination 88.4% (343/388) of sero-negative animals were sero-converted suggesting the efficacy of the locally produced Nigeria 75/1 vaccine. Even if only individuals in the high-risk age group (7 - 18 months) were vaccinated, the overall population immunity (OPI) in high-risk areas (the Blue Nile and North Kordofan) would have surpassed the threshold of 70%, which is indicated for blocking PPRV transmission. However, lower vaccination coverage is expected in wider vaccination programmes. These findings primarily justified the targeting of PPR control in Sudan through the vaccination of high-risk age groups in high-risk areas.展开更多
The high-energy cosmic radiation detector(HERD)is a planned experimental instrument at the Chinese Space Station.The silicon charge detector(SCD),a subdetector in HERD,is used to detect cosmic-ray nuclei with a high c...The high-energy cosmic radiation detector(HERD)is a planned experimental instrument at the Chinese Space Station.The silicon charge detector(SCD),a subdetector in HERD,is used to detect cosmic-ray nuclei with a high charge resolution.In this study,we present a compact readout electronic system for the SCD that is designed for the HERD heavy-ion beam test.It comprises front-end readout electronics with 200 input channels as well as data acquisition and data management electronics.The test results showed that the SCD readout system had low noise with a silicon-strip detector connected.The dynamic range could be extended from 200 to 1200 fC,and the cosmic-ray test was performed as expected.展开更多
文摘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.
基金supported by the National Research Foundation of Korea grant funded by the Korean government(No.2022R1A2C100425811,Kwangwon Ahn).
文摘This study explains the role of economic uncertainty as a bridge between business cycles and investors’herding behavior.Starting with a conventional stochastic differential equation representing the evolution of stock returns,we provide a simple theoretical model and empirically demonstrate it.Specifically,the growth rate of gross domestic product and the power law exponent are used as proxies for business cycles and herding behavior,respectively.We find stronger herding behavior during recessions than during booms.We attribute this to economic uncertainty,which leads to strong behavioral bias in the stock market.These findings are consistent with the predictions of the quantum model.
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.
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.
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.
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.
文摘Activity 1 Think about the following questions and write down your answers before reading the text.1.What are some possible ways animals can survive without access to fresh water sources?2.What other factors besides water could contribute to the thriving(茁壮成长)of a herd of goats on an isolated island?
文摘Peste des petits ruminants virus (PPRV) antibodies were studied in Sudanese sheep and goats (n = 855) before and after vaccination with a locally produced Nigeria 75/1 vaccine using a commercial competitive ELISA (cELISA) kit. Animals were kept healthy under field conditions, in four states: Blue Nile (n = 250), North Kordofan (n = 189), South Darfur (n = 225) and the Northern State (n = 191). Before vaccination, the overall sero-prevalence of PPRV antibodies was 54.6% (53.2% - 56%, 95% CI);high (64.8% - 76.4%, 95% CI) in Blue Nile State, medium (50.5% - 61.9%, 95% CI) in North Kordofan State and South Darfur State and low (28.6% - 35.2% 95%, CI) in Northern State. In high-risk areas (high sero-prevalence), Blue Nile (70.4%) and North Kordofan (57.7%), middle age groups (7 - 12 and 13 - 18 months) were identified as high-risk age. Middle age groups showed lower sero-prevalence than preceding (3 - 6 months) and subsequent (>18 months) age groups while the risk of exposure increased with age. Current and previous findings suggested a transmission pathway of PPRV involving the South Eastern border (Blue Nile) and neighbouring Central Sudan to North Kordofan. One month after vaccination 88.4% (343/388) of sero-negative animals were sero-converted suggesting the efficacy of the locally produced Nigeria 75/1 vaccine. Even if only individuals in the high-risk age group (7 - 18 months) were vaccinated, the overall population immunity (OPI) in high-risk areas (the Blue Nile and North Kordofan) would have surpassed the threshold of 70%, which is indicated for blocking PPRV transmission. However, lower vaccination coverage is expected in wider vaccination programmes. These findings primarily justified the targeting of PPR control in Sudan through the vaccination of high-risk age groups in high-risk areas.
基金supported by the CNSA program(D050102)National Natural Science Foundation of China(Nos.12061131007,12003038,42365006)Young Scientists Fund of the National Natural Science Foundation of China(No.11903037).
文摘The high-energy cosmic radiation detector(HERD)is a planned experimental instrument at the Chinese Space Station.The silicon charge detector(SCD),a subdetector in HERD,is used to detect cosmic-ray nuclei with a high charge resolution.In this study,we present a compact readout electronic system for the SCD that is designed for the HERD heavy-ion beam test.It comprises front-end readout electronics with 200 input channels as well as data acquisition and data management electronics.The test results showed that the SCD readout system had low noise with a silicon-strip detector connected.The dynamic range could be extended from 200 to 1200 fC,and the cosmic-ray test was performed as expected.
