Estimating long-term volatility parameters for market-consistent models

dc.contributor.authorFlint, E J
dc.contributor.authorOchse, E R
dc.contributor.authorPolakow, D A
dc.date.accessioned2016-04-28T08:30:04Z
dc.date.available2016-04-28T08:30:04Z
dc.date.issued2014
dc.date.updated2016-04-28T08:28:33Z
dc.description.abstractContemporary actuarial and accounting practices (APN 110 in the South African context) require the use of market-consistent models for the valuation of embedded investment derivatives. These models have to be calibrated with accurate and up-to-date market data. Arguably, the most important variable in the valuation of embedded equity derivatives is implied volatility. However, accurate long-term volatility estimation is difficult because of a general lack of tradable, liquid medium- and long-term derivative instruments, be they exchange-traded or over the counter. In South Africa, given the relatively short-term nature of the local derivatives market, this is of particular concern. This paper attempts to address this concern by: — providing a comprehensive, critical evaluation of the long-term volatility models most commonly used in practice, encompassing simple historical volatility estimation and econometric, deterministic and stochastic volatility models; and — introducing several fairly recent nonparametric alternative methods for estimating long-term volatility, namely break-even volatility and canonical option valuation. The authors apply these various models and methodologies to South African market data, thus providing practical, long-term volatility estimates under each modelling framework whilst accounting for real-world difficulties and constraints. In so doing, they identify those models and methodologies they consider to be most suited to long-term volatility estimation and propose best estimation practices within each identified area. Thus, while application is restricted to the South African market, the general discussion, as well as the suggestion of best practice, in each of the evaluated modelling areas remains relevant for all long-term volatility estimation.en_ZA
dc.identifierhttp://dx.doi.org/10.4314/saaj.v14i1.2
dc.identifier.apacitationFlint, E. J., Ochse, E. R., & Polakow, D. A. (2014). Estimating long-term volatility parameters for market-consistent models. <i>South African Actuarial Journal</i>, http://hdl.handle.net/11427/19263en_ZA
dc.identifier.chicagocitationFlint, E J, E R Ochse, and D A Polakow "Estimating long-term volatility parameters for market-consistent models." <i>South African Actuarial Journal</i> (2014) http://hdl.handle.net/11427/19263en_ZA
dc.identifier.citationFlint, E. J., Ochse, E. R., & Polakow, D. A. (2015). Estimating long-term volatility parameters for market-consistent models. South African Actuarial Journal, 14(1), 19-72.en_ZA
dc.identifier.issn1680-2179en_ZA
dc.identifier.ris TY - Journal Article AU - Flint, E J AU - Ochse, E R AU - Polakow, D A AB - Contemporary actuarial and accounting practices (APN 110 in the South African context) require the use of market-consistent models for the valuation of embedded investment derivatives. These models have to be calibrated with accurate and up-to-date market data. Arguably, the most important variable in the valuation of embedded equity derivatives is implied volatility. However, accurate long-term volatility estimation is difficult because of a general lack of tradable, liquid medium- and long-term derivative instruments, be they exchange-traded or over the counter. In South Africa, given the relatively short-term nature of the local derivatives market, this is of particular concern. This paper attempts to address this concern by: — providing a comprehensive, critical evaluation of the long-term volatility models most commonly used in practice, encompassing simple historical volatility estimation and econometric, deterministic and stochastic volatility models; and — introducing several fairly recent nonparametric alternative methods for estimating long-term volatility, namely break-even volatility and canonical option valuation. The authors apply these various models and methodologies to South African market data, thus providing practical, long-term volatility estimates under each modelling framework whilst accounting for real-world difficulties and constraints. In so doing, they identify those models and methodologies they consider to be most suited to long-term volatility estimation and propose best estimation practices within each identified area. Thus, while application is restricted to the South African market, the general discussion, as well as the suggestion of best practice, in each of the evaluated modelling areas remains relevant for all long-term volatility estimation. DA - 2014 DB - OpenUCT DP - University of Cape Town J1 - South African Actuarial Journal LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 SM - 1680-2179 T1 - Estimating long-term volatility parameters for market-consistent models TI - Estimating long-term volatility parameters for market-consistent models UR - http://hdl.handle.net/11427/19263 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/19263
dc.identifier.urihttp://www.ajol.info/index.php/saaj/article/view/111756
dc.identifier.vancouvercitationFlint EJ, Ochse ER, Polakow DA. Estimating long-term volatility parameters for market-consistent models. South African Actuarial Journal. 2014; http://hdl.handle.net/11427/19263.en_ZA
dc.languageengen_ZA
dc.publisherActurial Society of South Africaen_ZA
dc.publisher.departmentSchool of Management Studiesen_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsCreative Commons Attribution 4.0 International (CC BY 4.0)*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_ZA
dc.sourceSouth African Actuarial Journalen_ZA
dc.source.urihttp://www.actuarialsociety.org.za/Professionalresources/SAActuarialJournal.aspx
dc.subject.otherlong-term volatility modelling
dc.subject.othermarket-consistent valuation
dc.subject.otherhistorical volatility
dc.subject.otherdeterministic volatility models
dc.subject.otherGARCH
dc.subject.otherstochastic volatility
dc.subject.otherbreak-even volatility
dc.subject.othercanonical valuation
dc.titleEstimating long-term volatility parameters for market-consistent modelsen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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