Abstract: This paper explores whether stock characteristics influence the herding formation among investors in the US equity market. To extend the research scope of the existing literature, this paper further examines the role that stock risk characteristics play in the US equity market, and the way they influence investors’ decision-making. First, empirical results show that whether general stocks or high-risk stocks, there are no herding behaviors among the investors in the US equity market during the whole research period or during four great events. Moreover, stock characteristics have great influence on investors’ trading decisions. Finally, there is a bidirectional lead-lag relationship of the herding formation between high-risk stocks and low-risk stocks, but the influence of high-risk stocks on the low-risk stocks is stronger than that of low-risk stocks on the high-risk stocks.
Abstract: Web service composition combines available services
to provide new functionality. Given the number of available
services with similar functionalities and different non functional
aspects (QoS), the problem of finding a QoS-optimal web service
composition is considered as an optimization problem belonging to
NP-hard class. Thus, an optimal solution cannot be found by exact
algorithms within a reasonable time. In this paper, a meta-heuristic
bio-inspired is presented to address the QoS aware web service
composition; it is based on Elephant Herding Optimization (EHO)
algorithm, which is inspired by the herding behavior of elephant
group. EHO is characterized by a process of dividing and combining
the population to sub populations (clan); this process allows the
exchange of information between local searches to move toward
a global optimum. However, with Applying others evolutionary
algorithms the problem of early stagnancy in a local optimum
cannot be avoided. Compared with PSO, the results of experimental
evaluation show that our proposition significantly outperforms the
existing algorithm with better performance of the fitness value and a
fast convergence.
Abstract: This study provides insight into the effects of investor sentiment, excess optimism, overconfidence, the disposition effect, and herding formation on momentum profits. This study contributes to the field by providing a further examination of the relationship between psychological factors and momentum profits. The empirical results show that there is no evidence of significant momentum profits in Taiwan’s stock market. Additionally, investor sentiment in Taiwan’s stock market significantly influences its momentum profits.
Abstract: This study explored the relationship between
psychological traits, demographics and financial behavioral biases for
individual investors in Taiwan stock market. By using questionnaire
survey method conducted in 2010, there are 554 valid convenient
samples collected to examine the determinants of three types of
behavioral biases. Based on literature review, two hypothesized
models are constructed and further used to evaluate the effects of big
five personality traits and demographic variables on investment biases
through Structural Equation Model (SEM) analysis. The results
showed that investment biases of individual investors are significantly
related to four personality traits as well as some demographics.
Abstract: This paper is to clarify the relationship of individual investor types, risk tolerance and herding bias. The questionnaire survey investigation is conducted to collect 389 valid and voluntary individual investors and to examine how the risk tolerance plays as a mediator between four types of personality and herding bias. Based on featuring BB&K model and reviewing the prior literature of psychology, a linear structural model are constructed and further used to evaluate the path of herding formation through the analysis of Structural Equation Modeling (SEM). The results showed that more impetuous investors would be prone to herding bias directly, but rather exhibit higher risk tolerance. However, risk tolerance would fully mediate between the level of confidence (i.e., confident or anxious) and herding bias, but not mediate between the method of action (careful or impetuous) for individual investors.
Abstract: This study aims to explore the relationship between the
disposition effect and herding behavior of investors trading Taiwanese
information technology stocks. This study differs from previous
literature in two aspects. First, in contrast with the earlier studies that
focused on investigating investors’ herding behavior, this study
explores the possibility that the disposition effect drives investors’
herding behavior. Additionally, it takes an in-depth look at the
interdependence between the disposition effect and herding behavior
of investors, including lead-lag relationship and volatility transmission
effect. Empirical results show that investors trading Taiwan’s
information technology stocks exhibit pronounced herding behavior
and that the disposition effect has a great impact on their herding
behavior.
Abstract: Planning capacities when regenerating complex investment goods involves particular challenges in that the planning is subject to a large degree of uncertainty regarding load information. Using information fusion – by applying Bayesian Networks – a method is being developed for forecasting the anticipated expenditures (human labor, tool and machinery utilization, time etc.) for regenerating a good. The generated forecasts then later serve as a tool for planning capacities and ensure a greater stability in the planning processes.
Abstract: If price and quantity are the fundamental building
blocks of any theory of market interactions, the importance of trading
volume in understanding the behavior of financial markets is clear.
However, while many economic models of financial markets have
been developed to explain the behavior of prices -predictability,
variability, and information content- far less attention has been
devoted to explaining the behavior of trading volume. In this article,
we hope to expand our understanding of trading volume by
developing a new measure of herding behavior based on a cross
sectional dispersion of volumes betas. We apply our measure to the
Toronto stock exchange using monthly data from January 2000 to
December 2002. Our findings show that the herd phenomenon
consists of three essential components: stationary herding, intentional
herding and the feedback herding.
Abstract: In this paper, we focus on the problem of driving and
herding a collection of autonomous actors to a given area. Then, a
new method based on multi-agent coordination is proposed for
solving the problem.
In our proposed method, we assume that the environment is
covered by sensors. When an event is occurred, sensors forward
information to a sink node. Based on received information, the sink
node will estimate the direction and the speed of movement of actors
and announce the obtained value to the actors. The actors coordinate
to reach the target location.