Volatility extraction in information based asset pricing framework via non-linear filtering

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dc.contributor.authorIkamari, Cynthia
dc.date.accessioned2021-05-12T10:59:03Z
dc.date.available2021-05-12T10:59:03Z
dc.date.issued2019-08
dc.descriptionPaper presented at the 5th Strathmore International Mathematics Conference (SIMC 2019), 12 - 16 August 2019, Strathmore University, Nairobi, Kenyaen_US
dc.description.abstractThis study looks at the derivation of a state space model that is applied in nonlinear filtering. The model is based on the Brody, Hughson and Macrina information based asset pricing model, also known as the BHM approach or BHM model. The objective of this study is to extend the application of a filtering approach used in estimation of volatilities for the Heston model to the BHM model. The measurement and transition equations obtained in the state space model are used in the extended kalman filter to extract volatility. The option price is obtained from the BSBHM Updated Model by incorporating information in the Black-Scholes Model. This option price is used to obtain the measurement equation while the variance process is used as the transition equation.en_US
dc.description.sponsorshipMultimedia University of Kenya, Kenya.en_US
dc.identifier.urihttp://hdl.handle.net/11071/11854
dc.language.isoen_USen_US
dc.publisherStrathmore Universityen_US
dc.subjectKalman filteren_US
dc.subjectExtended Kalman Filteren_US
dc.subjectMeasurement Equationen_US
dc.subjectState Space Modelen_US
dc.subjectTransition Equationen_US
dc.titleVolatility extraction in information based asset pricing framework via non-linear filteringen_US
dc.typeArticleen_US
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