Assessing alternative technologies for the cost-effective computation of derivatives

被引:0
|
作者
Freedman, RS [1 ]
Digiorgio, R [1 ]
机构
[1] SUN MICROSYST INC,NEW YORK,NY
关键词
D O I
10.1080/088395196118399
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One should not separate the method of computing the expected present value of a derivative from its ultimate computing topology. In the following sections, we discuss the cost-benefit issues involved with implementing several methods for computing derivative statistics on alternate computing topologies. We show how the choice of topology impacts the computing time for a particular example of a time-consuming derivative valuation. We conclude by showing how all these factors can be represented as a case-based expert system, which can be used to help an organization assess its computing alternatives.
引用
收藏
页码:491 / 503
页数:13
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