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Robust hedging of barrier options with beliefs on implied Volatility Obłój, Jan
Description
We develop an abstract robust modelling framework accommodating as inputs market priced of options and modelling beliefs formulated in terms of pathspace restrictions. This naturally allows us to talk about robust market models. As an example we consider pricing and hedging of barrier options with beliefs about future levels of implied volatilities. We construct local volatility models which satisfy such constraints and use them to combine static and robust hedging methods. We discuss asymptotic convergence when beliefs become stronger (model specific) or weaker (model independent). Joint work with Sergey Nadtochiy.
Item Metadata
Title |
Robust hedging of barrier options with beliefs on implied Volatility
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2014-05-13
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Description |
We develop an abstract robust modelling framework accommodating as inputs market priced of options and modelling beliefs formulated in terms of pathspace restrictions. This naturally allows us to talk about robust market models. As an example we consider pricing and hedging of barrier options with beliefs about future levels of implied volatilities. We construct local volatility models which satisfy such constraints and use them to combine static and robust hedging methods. We discuss asymptotic convergence when beliefs become stronger (model specific) or weaker (model independent).
Joint work with Sergey Nadtochiy.
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Extent |
15 minutes
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: University of Oxford
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Series | |
Date Available |
2014-10-29
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0044152
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada