dc.creatorMaciel
dc.creatorLeandro; Ballini
dc.creatorRosangela; Gomide
dc.creatorFernando
dc.date2016
dc.date2017-11-13T13:50:49Z
dc.date2017-11-13T13:50:49Z
dc.date.accessioned2018-03-29T06:07:21Z
dc.date.available2018-03-29T06:07:21Z
dc.identifier978-1-5090-2583-1
dc.identifierProceedings Of The 2016 Ieee Conference On Evolving And Adaptive Intelligent Systems(eais). Ieee, p. 57 - 64, 2016.
dc.identifierWOS:000392268300008
dc.identifierhttp://ieeexplore.ieee.org/document/7502372/
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/329284
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1366309
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionThe correct pricing of financial derivatives plays a key role in risk management and in hedge operations. Besides the Black and Scholes closed-form formula simplicity and good results for pricing European options, several of the assumptions used in the method may be unrealistic and influence the results significantly. In order to overcome this limitation, this paper suggests an evolving possibilistic fuzzy modeling (ePFM) approach for European equity options pricing. The approach is based on an extension of the possibilistic fuzzy c-means clustering and functional fuzzy rule-based modeling. ePFM employs memberships and typicalities to recursively cluster data, and uses participatory learning to adapt the model structure as a stream data is input. The model does not require any assumptions about data distribution, it is an effective robust method to handle noisy data and outliers in option price dynamics modeling, and it is also capable to access volatility clustering due to its clustering based nature. Computational experiments consider the pricing of European equity options (calls and puts) on preference shares of Petrobras (PETR4), one of the most liquidity options traded in the Brazilian derivatives market. The results show that ePFM is a potential candidate for equity options pricing, with comparable or better performance than the Black and Scholes method and alternative evolving fuzzy approaches.
dc.description57
dc.description64
dc.descriptionBrazilian Ministry of Education (CAPES)
dc.descriptionBrazilian National Research Council (CNPq)
dc.descriptionResearch of Foundation of the State of Sao Paulo (FAPESP)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionIEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)
dc.descriptionMAY 23-25, 2016
dc.descriptionNatal, BRAZIL
dc.description
dc.languageEnglish
dc.publisherIEEE
dc.publisherNew York
dc.relationProceedings of the 2016 IEEE Conference on Evolving and Adaptive Intelligent Systems(EAIS)
dc.rightsfechado
dc.sourceWOS
dc.titleEvolving Possibilistic Fuzzy Modeling For Equity Options Pricing
dc.typeActas de congresos


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