Investor behaviour and reaching for yield: Evidence from the sterling corporate bond market

We provide evidence on how corporate bond investors react to a change in yields, and how this behaviour differs in times of market‐wide stress. We also investigate ‘reaching for yield’ across investor types, as well as providing insights into the structure of the corporate bond market. Using proprietary sterling corporate bond transaction data, we show that insurance companies, hedge funds and asset managers are typically net buyers when corporate bond yields rise. Dealer banks clear the market by being net sellers. However, we find evidence for this behaviour reversing in times of stress for some investors. During the 2013 ‘taper tantrum’, asset managers were net sellers of corporate bonds in response to a sharp rise in yields, potentially amplifying price changes. At the same time, dealer banks were net buyers. Finally, we provide evidence that insurers, hedge funds and asset managers tilt their portfolios towards higher risk bonds, consistent with ‘reaching for yield’ behaviour.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Virtual reality and mixed reality for second chance tourism

The deterioration of attractions, landmarks, artefacts and destinations is a critical issue facing tourism across the world. The closure of tourism sites and attractions is increasingly more common due to the difficulty and expense of managing preservation with onsite tourism engagement. However, the closure or destruction of tourism sites presents challenges for tourism development. The inability to foster meaningful visitor engagement at sites has implications for the local communities. This paper aims to explore the efficacy of creating tourism experiences in destinations and sites that have succumbed to over-tourism, resultant deterioration and even, destruction. To achieve this objective, the paper introduces the concept of second chance tourism and the role of innovative preservation methods such as virtual and mixed reality. Based on the proposed framework, the collation of data will provide indications on site preservation and impact mitigation via a second chance to reduce pressure on inherently fragile destinations.     

Economic interpretations of DEA

Research on productive efficiency at the firm level has developed as an important and active strand of research the last decades, both within operations research, management science and economics. Two apparently different definitions of efficiency are examined, but it is shown that when both estimation methods are based on solving linear programming problems the definitions of efficiency are identical. The purpose of the paper is to give the basic ideas of efficiency analyses using DEA as a tool for researchers not so familiar with efficiency analysis and DEA. The concept of shadow prices is given special attention.     

简析加强非国有企业档案管理的重要性

阐述了中国“入世”后，档案工作在非国有企业的生存发展中所起的基础性作用和保护企业知识产权的重要性，提出了非国有企业档案工作改革的新思路。     

刍议馆长的非权力影响力

馆长对图书馆的事业发展至关重要.探讨了图书馆馆长治理图书馆的非权力影响力,即指依靠馆长自身的素养,即德、才、仁、情等因素,使馆长更具向心力、凝聚力,从而推动图书馆工作的有效地运作,促进图书馆事业的蓬勃发展.     

Estimation of the mean in ranked set sampling with non responses

The estimation of the population mean when ranked set sampling [rss] is used for selecting the sample and non responses [nr] are present, is studied. The nr stratum is sub sampled using simple random sampling with replacement. Two strategies are analyzed. One of them is based on the selection of a sub sample from the nr in each cycle. The other uses sub samples selected among the nr in each rank.  The accuracy of the proposed estimators is characterized by the corresponding expected variances. Simulations and real life data are used for analyzing the behavior of them. Acknowledgements: This paper was developed partially during the visit of the author to Université des Antilles et Gouyane. The author gratefully acknowledges the helpful suggestions of the referees and thanks the support of DAAD for visiting Humboldt University where a version of the paper version was made.     

Inferential Causal Models: Integrating Quality & Quantity

In-depth data analysis plus statistical modeling can produce inferentialcausal models. Their creation thus combines aspects of analysis by close inspection,that is, reason analysis and cross-tabular analysis, with statistical analysis procedures,especially those that are special cases of the generalized linear model (McCullaghand Nelder, 1989; Agresti, 1996; Lindsey, 1997). This paper explores some of the roots of this combined method and suggests some new directions. An exercise clarifies some limitations of classic reason analysis by showing how the cross tabulation of variables with controls for test factors may produce better inferences. Then, given the cross tabulation of several variables, by explicating Coleman effect parameters, logistic regressions, and Poisson log-linear models, it shows how generalized linear models provide appropriate measures of effects and tests of statistical significance. Finally, to address a weakness of reason analysis, a case-control design is proposed and an example is developed.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.     

面向对象程序设计教学改革与实践

指出了面向对象程序设计教学中存在的问题,针对问题提出了改革措施：采用案例式教学,加强实践教学管理,结合BB教学平台辅助教学。不断提高学生学习的自觉性和主动性,成为教学改革的重要研究内容。