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dc.contributor.authorHin, L.
dc.contributor.authorDokuchaev, Nikolai
dc.date.accessioned2017-01-30T15:17:44Z
dc.date.available2017-01-30T15:17:44Z
dc.date.created2015-07-16T06:22:02Z
dc.date.issued2015
dc.identifier.citationHin, L. and Dokuchaev, N. 2015. Computation of the implied discount rate and volatility for an overdefined system using stochastic optimization. IMA Journal of Management Mathematics. 27 (4): pp. 505-527.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/45001
dc.identifier.doi10.1093/imaman/dpv007
dc.description.abstract

This paper studies estimation of the implied volatility and the impact of the choice of the corresponding risk-free rate proxy. We suggest to analyse the implied volatility and the risk-free rate proxy inferred in conjunction with the observed option prices. We formulate and solve an overdefined system of non-linear equations for the Black–Scholes model using options data. More precisely, we seek an optimal approximate solution via differential evolution, a stochastic optimization technique. Some experiments with historical prices reveal a higher inferred risk-free rate than commonly used proxies. This leads to narrower volatility spread, or smaller difference between implied and realized volatilities.

dc.publisherOxford University Press
dc.subjectrisk-free rate
dc.subjectoptimization
dc.subjectImplied volatility
dc.titleComputation of the implied discount rate and volatility for an overdefined system using stochastic optimization
dc.typeJournal Article
dcterms.source.volumeTBA
dcterms.source.numberTBA
dcterms.source.startPage1
dcterms.source.endPage35
dcterms.source.issn1471-678X
dcterms.source.titleIMA Journal of Management Mathematics
curtin.note

This is a pre-copyedited, author-produced PDF of an article accepted for publication in IMA Journal of Management Mathematics following peer review. The version of record "Hin, L. and Dokuchaev, N. 2015. Computation of the implied discount rate and volatility for an overdefined system using stochastic optimization. IMA Journal of Management Mathematics" is available online at http://doi.org/10.1093/imaman/dpv007

curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusOpen access


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