A Sensitivity Analysis of a Certain Mathematical Model of Expert Evaluation of Investment Projects
УДК 519.87
Abstract
The paper presents a sensitivity analysis of the developed mathematical model of expert evaluation of investment projects. Processes of investment projects implementations are analyzed as decision-making processes under uncertainty. The mathematical model under study evaluates the effectiveness of an investment project using the NPV index. This index is considered a random variable and can be estimated by an investor as a segment [NPV1; NPV2J. The proposed mathematical model utilizes the probability density function of NPV in the form of Pearson curves of the first type. Another peculiar feature of the mathematical model is utilization of the subjective utility function in decision making of whether to invest or not to invest in some project. The subjective utility function considers individual characteristics of investors and their decision making under risks and uncertainty. Perception of additional information by investors changes depending on their attitude toward risk and missed opportunities and thus reduces uncertainty in decision making. The paper studies this step in detail and provides some conclusions proving the correctness of the developed mathematical model.
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Оскорбин Н.М., Боговиз А.В., Жариков А.В. Информационный аспект принятия решений в системе ЛПР // Динамика современной науки. Экономика : матер. VII между-нар. науч.-практ. конф. 2011. Т. 2.
Оскорбин Н.М., Жариков А.В., Матюнин Е.В. Математические модели оптимизации многоэтапных инвестиционных процессов при информационных ограничениях // Совершенствование управления производством, инновации и инвестиции : матер. 3-го межрегион. семинара. Барнаул, 2013.
Трифонов Ю.В., Плеханова А.Ф., Юрлов Ф.Ф. Выбор эффективных решений в экономике в условиях неопределенности : монография. Н. Новгород, 1998.
Кошечкин С.А. Концепция риска инвестиционного проекта. URL: http://www.aup.ru/articles/investment/1.htm.
Данько Е.В. Функция субъективной полезности инвестиционных решений в условиях информационной неопределенности и метод оценки ее параметров // Вестн. Новосиб. гос. ун-та. Сер. : Информационные технологии. 2015. Т. 13. Вып. 3.
Плаус С. Психология оценки и принятия решений / пер. с англ. М., 1998.
Kahneman D., Tversky A. Prospect Theory: An Analysis of Decision Under Risk. Econometrica. 1979. Vol. 47 (2).
Tversky A., Kahneman D. The framing of decisions and the psychology of choice. Science. 1981. № 211.
Arrow K.I. Social choice and Individual Values. New York, 1951.
Barberis N., Ming Huang M., Santos T. Prospect Theory and Asset Prices. The Quarterly Journal of Economics. Vol. 116. № 1 (Feb., 2001).
Shefrin H. Beyond greed and fear. Boston, 2000.
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