使用粒子群算法解决期权定价模型参数校准问题——以heston模型为例

期权定价模型的参数校准问题是一个常见的难题,以heston 模型为例,定价时需要估计6 个参数,参数估计问题实质上是高维非线性规划问题,由于估参函数的性质不好,一般的估参方法常常失效。使用粒子群（PSO）智能算法可以改善该模型的参数校准问题,因为粒子群算法具有内在随机性,因此参数估计中的局部极小值问题可以被较好地解决。使用2017 年12 月20 日的香港恒生指数期权作为估计样本,并对2017 年12 月25 日的期权进行样本外预测,数值结果表明使用heston 模型对期权进行定价并配合粒子群算法估计参数具有良好的定价效果。     

CRM动态能力维度对顾客资产的作用机制研究

顾客资产是企业的一项关键资产,对其进行有效的评估及管理将有利于企业绩效的提高,因此,建立和维持CRM动态能力将使企业具有持续的竞争优势.文章从上述这一个新的视角构建了顾客资产的效果机制模型.同时,分别从市场导向、社会网络能力、资源重构三个维度的重要性验证了对营销效果和顾客资产的影响存在差异性,并发现了营销情报与顾客响应的内在统一性.     

Employee performance outcomes and burnout following the presentation-of-self in customer-service contexts

This study examines how emotional intelligence and occupational commitment have a moderating effect on the relationship between emotional labour and its potential outcomes. Two acting strategies reflect emotional labour, namely surface and deep acting, with burnout and performance as the prospective outcomes. Burnout is operationalized into emotional exhaustion, depersonalization and diminished personal achievement; whereas performance is operationalized into task performance and organizational citizenship behaviour (OCB). The study investigates employee responses from several tourism and hospitality organizations in Florida, USA. The results show that emotional labour relates most positively to task performance and to burnout in the case of surface acting. Tests of moderation show that occupational commitment enhances performance outcomes by facilitating emotional labour strategies, and the prevalence of higher emotional intelligence amongst employees reduces burnout. These findings contribute to the literature on emotional labour by incorporating emotional intelligence and occupational commitment as moderators and by incorporating OCBs within performance analyses.     

Does hospitality diversity education make a difference in undergraduate students’ emotional intelligence

Soft skills are typically referred to as the attributes exhibited or contained by an individual that display his/her ability to interact with others. Two types of soft skills that are often discussed within the hospitality industry are diversity awareness and emotional intelligence. Diversity may be explained or defined as a state of unlikeness, the conditions of being different, and all things that make us different. Areas where differences may exist include race, ethnicity, gender, sexual orientation, socio-economic status, age, physical abilities, religious beliefs, political affiliation and emotional reaction. Emotional intelligence (EI) has been defined as the ability to perceive, understand, regulate, and harness emotions in the self and others. How one deals with emotion is one characteristic that varies from culture to culture. Research has shown that EI may be a contributing factor in a moment of truth being considered a failure or success. The purpose of this study was to examine if undergraduate student EI scores change after completing a diversity issues course. Students completed the Assessing Emotions Scale on the first class day. At the conclusion of the 15-week course covering approximately 20 diversity issues concepts students completed the same EI assessment. Paired sampled t-testing was conducted to determine whether mean differences existed when comparing post and pre-course scores. Results of this study suggest that certain components of EI are significantly changed after taking the diversity issues course.     

Employee satisfaction with schedule flexibility: Psychological antecedents and consequences within the workplace

Although balancing work-related and non-work-related time demands is an ongoing concern for many hotel workers, there is a dearth of research examining workers’ satisfaction with their work schedule flexibility. Using a sample drawn from nine different hotel properties in South Korea, this study finds that workers’ levels of emotional intelligence and overall job satisfaction serve as antecedents of their schedule flexibility satisfaction. Moreover, the study also finds that decreased turnover intent is a consequence of schedule flexibility satisfaction. Based upon these findings, both managerial and research implications are presented.     

专家系统在网络管理中应用的分析与研究

本文将介绍人工智能网络管理中的专家系统在网络管理的应用,它能够模拟人的智能对网络进行自动收集数据、自动进行诊断、进行性能分析、趋势分析、故障分析,控制流量,在各种管理功能域中一定程度上实行自动管理提高了网络管理的质量和效率。     

Machine learning methods in finance: Recent applications and prospects

We study how researchers can apply machine learning (ML) methods in finance. We first establish that the two major categories of ML (supervised and unsupervised learning) address fundamentally different problems than traditional econometric approaches. Then, we review the current state of research on ML in finance and identify three archetypes of applications: (i) the construction of superior and novel measures, (ii) the reduction of prediction error, and (iii) the extension of the standard econometric toolset. With this taxonomy, we give an outlook on potential future directions for both researchers and practitioners. Our results suggest many benefits of ML methods compared to traditional approaches and indicate that ML holds great potential for future research in finance.     

Emotional Intelligence in Undergraduate Accounting Students: Preliminary Assessment

Abstract

There is a growing recognition among researchers and practitioners that the workplace is not the strictly cognitively-managed environment it was once assumed to be. Emotions play a large role in organizational life, and emotional intelligence (the ability to recognize, use and manage emotions) has become a skill that may allow accountants to perform better in a variety of areas such as leadership, client relations, and perhaps even decision-making. In addition, it is a skill that employers seem to value and that may be important to personal development as well. Thus, accounting education must attempt to inculcate emotional intelligence in its graduates in addition to technical knowledge. This paper investigates the level of emotional intelligence of accounting students using the MSCEIT, an instrument that measures ability rather than acquired competencies. The results show that the level of emotional intelligence of the students in the sample could be a concern. There is no evidence that one term of traditional accounting education can be expected to provide an opportunity for improvement. Thus, attempts to increase the emotional intelligence of the students may require targeted educational interventions.     

A multiple objective particle swarm optimization approach for inventory classification

This paper presents a particle swarm optimization approach for inventory classification problems where inventory items are classified based on a specific objective or multiple objectives, such as minimizing costs, maximizing inventory turnover ratios, and maximizing inventory correlation. In addition, this approach determines the best number of inventory classes and how items should be categorized for the desired objectives at the same time. Experiments are employed to determine the best combination of algorithm parameter values. Extensive numerical studies are conducted and results are compared to other known classification methods. The performance of the algorithm on a practical case is also presented.     

BUILDING AND EVOLVING DATA WAREHOUSING AND BUSINESS INTELLIGENCE ARTEFACTS: THE CASE OF SYSCO

This paper investigates use of data warehouse and business intelligence capabilities to integrate with customers in the supply chain and improve insights into customer sales. By making internal data warehouse sales information available to customers, additional value to those customers is created, eliminating asymmetries of information in the supply chain. In addition, the evolution of data warehousing into business intelligence is investigated, expanding sales information to include marketing associate performance analysis generated for internal use. Further, a methodology that was used for building a business intelligence system is also examined. Finally, what appears to be a business‐intelligence‐driven focus on enterprise resource planning systems is analyzed. These issues are illustrated using real‐world data warehousing and business intelligence artefacts developed at SYSCO. Copyright © 2012 John Wiley & Sons, Ltd.