金融寡头J.P.摩根

约翰·皮尔庞特·摩根(John Pierpont Morgan,Sr.,简称J.P.摩根)(1837年-1913年)是19世纪末20世纪上半叶美国最重要的银行家,现在他的名字永远写在了一个公司的名字上面,这就是J.P.摩根公司,现在它又与大通曼哈顿公司合并为J.P.摩根大通公司(J.P.Morgan Chase Co.).     

.NET和J2EE的崛起与抗衡

一、.NET诞生的背景在当今最为流行的IT词汇里,.NET(读作dotnet)无疑是最风光的一个。尽管很多人对.NET都似曾耳闻,但是真正理解其内涵的却并不多。1.微软面临来自Java阵营的威胁Sun公司推出的Java方案号召程序员们都转到Ja-va语言的旗下,因为使用Java语言开发的应用系统,可以在任意操作系统平台上运行。这种跨平台特性吸引了很多企业和开发人员转向Java。Sun公司的意图触动了微软公司的利益。微软的Windows开发用户群是微软通过Windows操作系统获得的最大财富,微软自然希望大家都使用Windows操作系统,并且使用Windows下的非Java…     

Professor R. J. Chambers: A biographical note

The paper attempts to assess the potential value of generic standards of competence to the future education and training of accountants and the implications for education, training and assessment practices. It identifies some problems in applying the technique of functional analysis to the definition of professional standards in general before looking at the specific problems of setting standards for accountants. Eraut's classification of types of knowledge which underpin professional performance is applied to the case of accounting. These comments are related to the draft accounting standards which have been produced under the Occupational Standards Programme with particular reference to the Management Accounting Standards.     

E. J. Moorhead (1910 – 2004)

Abstract

As is well known in actuarial practice, excess claims (outliers) have a disturbing effect on the ratemaking process. To obtain better estimators of premiums, which are based on credibility theory, Künsch and Gisler and Reinhard suggested using robust methods. The estimators proposed by these authors are indeed resistant to outliers and serve as an excellent example of how useful robust models can be for insurance pricing. In this article we further refine these procedures by reducing the degree of heuristic arguments they involve. Specifically we develop a class of robust estimators for the credibility premium when claims are approximately gamma-distributed and thoroughly study their robustness-efficiency trade-offs in large and small samples. Under specific datagenerating scenarios, this approach yields quantitative indices of estimators’ strength and weakness, and it allows the actuary (who is typically equipped with information beyond the statistical model) to choose a procedure from a full menu of possibilities. Practical performance of our methods is illustrated under several simulated scenarios and by employing expert judgment.