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DC Field | Value | Language |
---|---|---|
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 |
Appears in Collections: | MS THESES |
Files in This Item:
File | Description | Size | Format | |
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MS_Thesis_Atharva_Tanksale_20151140.pdf | MS Thesis | 1.14 MB | Adobe PDF | View/Open |
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