启发式
计算机科学
估价(财务)
嵌入
二项期权定价模型
计量经济学
嵌套集模型
投资(军事)
运筹学
数学优化
经济
数学
数据挖掘
期权估价
财务
人工智能
政治
政治学
关系数据库
法学
作者
Michel Benaroch,Sandeep Shah,Mark Jeffery
标识
DOI:10.2753/mis0742-1222230108
摘要
As real options analysis (ROA) is being applied to increasingly complex information technology (IT) investment problems, a concern arises over the use of heuristic ROA models that are simpler to apply but can produce overvaluations. A good example is the application of a heuristic nested variation of the Black-Scholes (BS) model to the evaluation of interrelated IT investments as nested options. This particular heuristic BS model could overvalue by more than 100 percent. Using a binomial model that is custom-tailored to a generic IT investment embedding nested options as the "baseline," we identify conditions under which the degree of overvaluation of this heuristic BS model is severe and unpredictable. Moreover, upon examining the structure of the custom-tailored binomial model, we identify the reason for overvaluation and derive a more accurate nested variation of the BS model. These findings should serve as a cautionary message about the use of untested heuristic ROA models.
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