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
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
Grassland is most important in China due to its multi-functions. However, about 90% of total usable grassland in China has been degraded and the degradation expands at a rate of 2 million ha per year. Western China co...Grassland is most important in China due to its multi-functions. However, about 90% of total usable grassland in China has been degraded and the degradation expands at a rate of 2 million ha per year. Western China covers 6.12 million square kilometers and 63.8% of the total national area with a distribution of 50 minority nationalities and 75% of the minority national population. Ecological environment there is very vulnerable with more than 90% areas of the annually increased degradation taking place. Under the current tenure arrangement, the individual herder households become the main and direct users of grassland, their decision-making on grassland management may have crucial impact on ecological environment as well as their livelihoods. Thus, it is necessary to examine the determinants of their grassland management behaviors. This study applies 231 household field data from 6 provinces of western China and uses econometric models to explore the major constraints for restricting the herd households' grassland management behaviors. Main results show that under the current tenure and other governance measures, institutional factors, market price and herder's farm and household's characteristics affect the grassland management behaviors.展开更多
Smallholder dairy farming in Africa is classified into rural, peri-urban and urban systems. The major classification criterion is demographic. Dairy systems are extensively characterized, but not based on rigorous sta...Smallholder dairy farming in Africa is classified into rural, peri-urban and urban systems. The major classification criterion is demographic. Dairy systems are extensively characterized, but not based on rigorous statistical analyses. We validated this classification based on herd genetic structure and identify determinants of within-system variations, taking Ethiopia as a case study. Discriminant function analysis correctly classified 38% - 50.6% of the 360 sampled farms into the three systems. Multinomial logistic regression analysis showed that rural and peri-urban farmers were 1.26 (P < 0.1) to 1.45 (P < 0.001) times more likely to keep local and low grade crossbreds and fewer high grade crosses (P < 0.05;odds ratio = 2.35) than the urban farmers. In the rural system, proportion of high grade crosses declined and low grades increased over generations, whereas in urban system the reverse was observed. Access to breeding services and land resources significantly determined the adoption of crossbred dairy herd within systems. In conclusion, considering farms within systems as a uniform unit to target development interventions may not be appropriate and thus farm topologies and system specific determinants of farmers’ breeding strategies need to be considered to design and introduce appropriate breeding interventions.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
Beginning in the fall of 2014 there has been a general and widespread increase in the incidence of prolapse in the U.S. swine herd. The purpose of this manuscript is to review the incidence, causative factors and trea...Beginning in the fall of 2014 there has been a general and widespread increase in the incidence of prolapse in the U.S. swine herd. The purpose of this manuscript is to review the incidence, causative factors and treatment of rectal, vaginal, uterine and preputial prolapses. Rectal and vaginal prolapses are most common in swine when compared to other prolapse types. The cause of prolapses supports a fixation mechanism failure overcome by pressure on or weakening of support tissue. The fundamental factors affecting the incidence for prolapses are many and include factors related to nutrition, physiology, hormones, genetics, environment and other disease factors such as chronic diarrhea, cough, and dystocia. Treatment of prolapsed swine includes surgical and therapeutic management that can lead to complete recovery. However, in most cases, euthanasia is the final result. Economic loss was calculated at approximately $5220 dollars/year/1000 sows.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
The development of buffalo milk industry in China encounters the problems of small high yield populations and insufficient excellent provenance. Therefore,it is necessary to carry out dairy herd improvement( DHI) to i...The development of buffalo milk industry in China encounters the problems of small high yield populations and insufficient excellent provenance. Therefore,it is necessary to carry out dairy herd improvement( DHI) to increase dairy buffalo herd productivity. This paper reviewed the situation and problems of DHI in dairy buffalo,and the corresponding opinions and suggestions were put forward.展开更多
A model to explain the dynamic characters of earnings management was developed based on the interactionamong several firms’ disclosure policies. Under the condition of incomplete information, each firm’s earnings ma...A model to explain the dynamic characters of earnings management was developed based on the interactionamong several firms’ disclosure policies. Under the condition of incomplete information, each firm’s earnings man-agement will be influenced by the earnings disclosure policies of other firms. It can lead to "herd behavior" of earningsmanagement. This paper studies the relationship between earnings manipulation and rights issue policy based on thedistribution of earnings after management. The results indicate that Chinese listed companies trend towards controllingROE in the narrow ranges just above 6% and 10% .Therefore, "herd behavior" exists in the earnings management.展开更多
In the context of vigorously developing China's securities market institutional investors in the period of economic transition,this paper does the empirical research on the herd behavior from the view of the inter...In the context of vigorously developing China's securities market institutional investors in the period of economic transition,this paper does the empirical research on the herd behavior from the view of the interaction between individual and institutional investors. This paper adopts the standard deviation of trading volume the cross-section to measure herd behavior. The results show that no matter what the market is in bull status and bear status,institutional investors perform herd behavior and with the expansion of the shareholding scale in a bull market,the herd behavior is higher,which suggests that the vigorous development of institutional investors has not eliminated herd behavior. This paper further confirms that there is the endogenous volatility in the market based on an artificial stock market. Finally it is demonstrated the herd behavior of institutional investors cause abnormal fluctuations in the market.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
As fossil fuel stocks are being depleted,alternative sources of energy must be explored.Consequently,traditional thermal power plants must coexist with renewable resources,such as wind,solar,and hydro units,and all-da...As fossil fuel stocks are being depleted,alternative sources of energy must be explored.Consequently,traditional thermal power plants must coexist with renewable resources,such as wind,solar,and hydro units,and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand.The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity(ATC)of current systems.Thermal units are linked to sources of renewable energy such as hydro,wind,and solar power,and are set up to run for 24 h.By contrast,new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos.Chaos seems to increase the performance and convergence properties of existing optimization approaches.In this study,selfish animal tendencies,mathematically represented as selfish herd optimizers,were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs,creating a multi-objective optimization problem.To evaluate the performance of the proposed hybridized optimization technique,an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions,that is,the renewable energy source-thermal scheduling concept,on IEEE 9-bus,IEEE 39-bus,and Indian Northern Region Power Grid 246-bus test systems.The findings show that the proposed technique outperforms existing well-established optimization strategies.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
Purpose To derive the temperature response of the basic unit of the electromagnetic calorimeter of the high energy cosmic-radiation detection(HERD)facility.Method Tested a method to measure HERD calorimeter cell(HCC)l...Purpose To derive the temperature response of the basic unit of the electromagnetic calorimeter of the high energy cosmic-radiation detection(HERD)facility.Method Tested a method to measure HERD calorimeter cell(HCC)light yield using an ultraviolet Light-Emitting Diode with a wavelength of 300 nm,and established an experimental setup and tested the light yield of the HCC at different temperatures in a thermal chamber.Results and conclusions The result showed that the signal amplitudes variation of the HCC reached up to 10.2% with temperature ranging from 0 to 60℃,if we narrow the temperature range to 0-35℃,the variation was about 3.7% and it showed much better linearity.This result provides a good instruction on the thermal control of the HERD calorimeter(CALO)to improve its performance.展开更多
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.
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.
基金Ford Foundation (1105-1408)Natural Science Foundation of China (71273268) for providing funding supports
文摘Grassland is most important in China due to its multi-functions. However, about 90% of total usable grassland in China has been degraded and the degradation expands at a rate of 2 million ha per year. Western China covers 6.12 million square kilometers and 63.8% of the total national area with a distribution of 50 minority nationalities and 75% of the minority national population. Ecological environment there is very vulnerable with more than 90% areas of the annually increased degradation taking place. Under the current tenure arrangement, the individual herder households become the main and direct users of grassland, their decision-making on grassland management may have crucial impact on ecological environment as well as their livelihoods. Thus, it is necessary to examine the determinants of their grassland management behaviors. This study applies 231 household field data from 6 provinces of western China and uses econometric models to explore the major constraints for restricting the herd households' grassland management behaviors. Main results show that under the current tenure and other governance measures, institutional factors, market price and herder's farm and household's characteristics affect the grassland management behaviors.
文摘Smallholder dairy farming in Africa is classified into rural, peri-urban and urban systems. The major classification criterion is demographic. Dairy systems are extensively characterized, but not based on rigorous statistical analyses. We validated this classification based on herd genetic structure and identify determinants of within-system variations, taking Ethiopia as a case study. Discriminant function analysis correctly classified 38% - 50.6% of the 360 sampled farms into the three systems. Multinomial logistic regression analysis showed that rural and peri-urban farmers were 1.26 (P < 0.1) to 1.45 (P < 0.001) times more likely to keep local and low grade crossbreds and fewer high grade crosses (P < 0.05;odds ratio = 2.35) than the urban farmers. In the rural system, proportion of high grade crosses declined and low grades increased over generations, whereas in urban system the reverse was observed. Access to breeding services and land resources significantly determined the adoption of crossbred dairy herd within systems. In conclusion, considering farms within systems as a uniform unit to target development interventions may not be appropriate and thus farm topologies and system specific determinants of farmers’ breeding strategies need to be considered to design and introduce appropriate breeding interventions.
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Beginning in the fall of 2014 there has been a general and widespread increase in the incidence of prolapse in the U.S. swine herd. The purpose of this manuscript is to review the incidence, causative factors and treatment of rectal, vaginal, uterine and preputial prolapses. Rectal and vaginal prolapses are most common in swine when compared to other prolapse types. The cause of prolapses supports a fixation mechanism failure overcome by pressure on or weakening of support tissue. The fundamental factors affecting the incidence for prolapses are many and include factors related to nutrition, physiology, hormones, genetics, environment and other disease factors such as chronic diarrhea, cough, and dystocia. Treatment of prolapsed swine includes surgical and therapeutic management that can lead to complete recovery. However, in most cases, euthanasia is the final result. Economic loss was calculated at approximately $5220 dollars/year/1000 sows.
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.
基金Supported by Scientific Innovation Program of Guangxi Aquatic,Animal Husbandry and Veterinary Bureau(1304519)
文摘The development of buffalo milk industry in China encounters the problems of small high yield populations and insufficient excellent provenance. Therefore,it is necessary to carry out dairy herd improvement( DHI) to increase dairy buffalo herd productivity. This paper reviewed the situation and problems of DHI in dairy buffalo,and the corresponding opinions and suggestions were put forward.
文摘A model to explain the dynamic characters of earnings management was developed based on the interactionamong several firms’ disclosure policies. Under the condition of incomplete information, each firm’s earnings man-agement will be influenced by the earnings disclosure policies of other firms. It can lead to "herd behavior" of earningsmanagement. This paper studies the relationship between earnings manipulation and rights issue policy based on thedistribution of earnings after management. The results indicate that Chinese listed companies trend towards controllingROE in the narrow ranges just above 6% and 10% .Therefore, "herd behavior" exists in the earnings management.
基金supported by the National Nature Science Foundation under Grant No.71201124
文摘In the context of vigorously developing China's securities market institutional investors in the period of economic transition,this paper does the empirical research on the herd behavior from the view of the interaction between individual and institutional investors. This paper adopts the standard deviation of trading volume the cross-section to measure herd behavior. The results show that no matter what the market is in bull status and bear status,institutional investors perform herd behavior and with the expansion of the shareholding scale in a bull market,the herd behavior is higher,which suggests that the vigorous development of institutional investors has not eliminated herd behavior. This paper further confirms that there is the endogenous volatility in the market based on an artificial stock market. Finally it is demonstrated the herd behavior of institutional investors cause abnormal fluctuations in the market.
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As fossil fuel stocks are being depleted,alternative sources of energy must be explored.Consequently,traditional thermal power plants must coexist with renewable resources,such as wind,solar,and hydro units,and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand.The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity(ATC)of current systems.Thermal units are linked to sources of renewable energy such as hydro,wind,and solar power,and are set up to run for 24 h.By contrast,new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos.Chaos seems to increase the performance and convergence properties of existing optimization approaches.In this study,selfish animal tendencies,mathematically represented as selfish herd optimizers,were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs,creating a multi-objective optimization problem.To evaluate the performance of the proposed hybridized optimization technique,an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions,that is,the renewable energy source-thermal scheduling concept,on IEEE 9-bus,IEEE 39-bus,and Indian Northern Region Power Grid 246-bus test systems.The findings show that the proposed technique outperforms existing well-established optimization strategies.
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the National Natural Science Foundation of China(Grant Nos.12027803,11875097,11975257)the support from the International Partnership Program of Chinese Academy of Sciences(Grant No.113111KYSB20190020).
文摘Purpose To derive the temperature response of the basic unit of the electromagnetic calorimeter of the high energy cosmic-radiation detection(HERD)facility.Method Tested a method to measure HERD calorimeter cell(HCC)light yield using an ultraviolet Light-Emitting Diode with a wavelength of 300 nm,and established an experimental setup and tested the light yield of the HCC at different temperatures in a thermal chamber.Results and conclusions The result showed that the signal amplitudes variation of the HCC reached up to 10.2% with temperature ranging from 0 to 60℃,if we narrow the temperature range to 0-35℃,the variation was about 3.7% and it showed much better linearity.This result provides a good instruction on the thermal control of the HERD calorimeter(CALO)to improve its performance.
