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A Data Driven Approach to Option Pricing

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dc.contributor.advisor GOSWAMI, ANINDYA en_US
dc.contributor.author TANKSALE, ATHARVA en_US
dc.date.accessioned 2020-06-16T05:45:11Z
dc.date.available 2020-06-16T05:45:11Z
dc.date.issued 2020-05 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/4715
dc.description.abstract Fair pricing of financial instruments is at the heart of market stability. Mispricing securities can lead traders into suffering massive losses which can indirectly affect the financial health of markets. It is thus, vital to be able to derive the fair price of traded financial instruments as this indirectly leads to optimized financial portfolios. This thesis aims to present a new approach to quantify the fair price of an Option contract given the underlying asset data. The models presented here would be constraint free when contrasted with traditional Option pricing models. We attempt to achieve the stated goal by leveraging advances in computational techniques. en_US
dc.language.iso en en_US
dc.subject Option Pricing en_US
dc.subject Machine Learning en_US
dc.subject Deep Learning en_US
dc.subject Finance en_US
dc.subject Markets en_US
dc.subject Decision Trees en_US
dc.subject 2020 en_US
dc.title A Data Driven Approach to Option Pricing en_US
dc.type Thesis en_US
dc.type.degree BS-MS en_US
dc.contributor.department Dept. of Mathematics en_US
dc.contributor.registration 20151140 en_US


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  • MS THESES [1705]
    Thesis submitted to IISER Pune in partial fulfilment of the requirements for the BS-MS Dual Degree Programme/MSc. Programme/MS-Exit Programme

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