A comparison of fuzzy regression methods for the estimation of the implied volatility smile function

DOI10.1016/j.fss.2014.11.015zbMath1361.62044OpenAlexW2091178702WikidataQ60255904 ScholiaQ60255904MaRDI QIDQ529267

A. Ruggieri, Silvia Muzzioli, Bernard De Baets

Publication date: 18 May 2017

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11380/1023318

zbMATH Keywords

nonlinear programmingdata analysisfinancefuzzy statisticsimplied volatilityfuzzy regression methods

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70) Fuzziness, and linear inference and regression (62J86)

Related Items (10)

Fuzziness in data analysis: towards accuracy and robustness ⋮ A fuzzy empirical quantile-based regression model based on triangular fuzzy numbers ⋮ A robust support vector regression with exact predictors and fuzzy responses ⋮ The legacy of 50 years of fuzzy sets: a discussion ⋮ Possibilistic linear regression with fuzzy data: tolerance approach with prior information ⋮ Fuzzy spline univariate regression with exact predictors and fuzzy responses ⋮ The Emergence of Fuzzy Sets: A Historical Perspective ⋮ Option implied moments obtained through fuzzy regression ⋮ Option pricing and the Greeks under Gaussian fuzzy environments ⋮ Fuzzy linear least squares for the identification of possibilistic regression models

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