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Paper Information

Journal:   IRANIAN JOURNAL OF FUZZY SYSTEMS   2012 , Volume 9 , Number 3; Page(s) 61 To 78.
 
Paper: 

PRICING STOCKS BY USING FUZZY DIVIDEND DISCOUNT MODELS

 
 
Author(s):  LIN H.W., YAO J.S.
 
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Abstract: 

Although the classical dividend discount model (DDM) is a well-known and widely used model in evaluating the intrinsic price of common stock, the practical pattern of dividends, required rate of return or growth rate of dividend do not generally coincide with any of the model’s assumptions. It is just the opportunity to develop a fuzzy logic system that takes these vague parameters into account. This paper extends the classical DDMs to more realistic fuzzy pricing models in which the inherent imprecise information will be fuzzified as triangular fuzzy numbers, and introduces a novel-signed distance method to defuzzify these fuzzy parameters without considering the membership functions. Through the conscientious mathematical derivation, the fuzzy dividend discount models (FDDMs) proposed in this paper can be regarded as one more explicit extension of the classical (crisp) DDMs, so that stockholders can use it to make a specific analysis and insight into the intrinsic value of stock.

 
Keyword(s): FUZZY SET, PRICING STOCK, DIVIDEND DISCOUNT MODEL (DDM),λ-SIGNED DISTANCE METHOD, UNIFORM CONVERGENCE
 
 
References: 
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Citations: 
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+ Click to Cite.
APA: Copy

LIN, H., & YAO, J. (2012). PRICING STOCKS BY USING FUZZY DIVIDEND DISCOUNT MODELS. IRANIAN JOURNAL OF FUZZY SYSTEMS, 9(3), 61-78. https://www.sid.ir/en/journal/ViewPaper.aspx?id=273658



Vancouver: Copy

LIN H.W., YAO J.S.. PRICING STOCKS BY USING FUZZY DIVIDEND DISCOUNT MODELS. IRANIAN JOURNAL OF FUZZY SYSTEMS. 2012 [cited 2021September18];9(3):61-78. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=273658



IEEE: Copy

LIN, H., YAO, J., 2012. PRICING STOCKS BY USING FUZZY DIVIDEND DISCOUNT MODELS. IRANIAN JOURNAL OF FUZZY SYSTEMS, [online] 9(3), pp.61-78. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=273658.



 
 
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