{"title":"Practical possibilistic fuzzy pay-off method for real option valuation","authors":"Jan Stoklasa , Mikael Collan , Pasi Luukka","doi":"10.1016/j.fss.2024.109072","DOIUrl":null,"url":null,"abstract":"<div><p>This paper describes a set of proposed additions to the recently introduced possibilistic fuzzy pay-off method for real option valuation that enhances the practical usability of the method. The additions are focused on the practical usability of the method and concentrate on emphasizing the consideration of the downside-risk found in projects. Technically the additions are based on using a novel interpretation of the possibilistic mean as a proxy respectively for the weight of the downside and the upside of a possibility distribution in the context of project profitability. This interpretation of the possibilistic mean is a new theoretical contribution.</p><p>The proposed new method-variant, called the “practical possibilistic fuzzy pay-off method for real option valuation”, can effectively distinguish between projects with an identical upside and non-identical downsides and allows for a more finance-theoretically comprehensive consideration of situations, where the circumstances surrounding the downside risk of a project change. Changes in the downside are reflected in the real option value. The proposed changes constitute the first variant of the possibilistic fuzzy pay-off method for real option valuation and they remarkably increase the practical usability of the method.</p></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0165011424002185/pdfft?md5=d52d13f8c84eb71c7f2d35782213c5b2&pid=1-s2.0-S0165011424002185-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fuzzy Sets and Systems","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165011424002185","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
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Abstract
This paper describes a set of proposed additions to the recently introduced possibilistic fuzzy pay-off method for real option valuation that enhances the practical usability of the method. The additions are focused on the practical usability of the method and concentrate on emphasizing the consideration of the downside-risk found in projects. Technically the additions are based on using a novel interpretation of the possibilistic mean as a proxy respectively for the weight of the downside and the upside of a possibility distribution in the context of project profitability. This interpretation of the possibilistic mean is a new theoretical contribution.
The proposed new method-variant, called the “practical possibilistic fuzzy pay-off method for real option valuation”, can effectively distinguish between projects with an identical upside and non-identical downsides and allows for a more finance-theoretically comprehensive consideration of situations, where the circumstances surrounding the downside risk of a project change. Changes in the downside are reflected in the real option value. The proposed changes constitute the first variant of the possibilistic fuzzy pay-off method for real option valuation and they remarkably increase the practical usability of the method.
期刊介绍：
Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies.
In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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