Utility-based valuation and hedging of basis risk with partial information

We analyse the valuation and hedging of a claim on a non-traded asset using a correlated traded asset under a partial information scenario, when the asset drifts are unknown constants. Using a Kalman filter and a Gaussian prior distribution for the unknown parameters, a full information model with r...

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Main Author: Monoyios, M
Format: Journal article
Published: 2010
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author Monoyios, M
author_facet Monoyios, M
author_sort Monoyios, M
collection OXFORD
description We analyse the valuation and hedging of a claim on a non-traded asset using a correlated traded asset under a partial information scenario, when the asset drifts are unknown constants. Using a Kalman filter and a Gaussian prior distribution for the unknown parameters, a full information model with random drifts is obtained. This is subjected to exponential indifference valuation. An expression for the optimal hedging strategy is derived. An asymptotic expansion for small values of risk aversion is obtained via PDE methods, following on from payoff decompositions and a price representation equation. Analytic and semi-analytic formulae for the terms in the expansion are obtained when the minimal entropy measure coincides with the minimal martingale measure. Simulation experiments are carried out which indicate that the filtering procedure can be beneficial in hedging, but sometimes needs to be augmented with the increased option premium, that takes into account parameter uncertainty, in order to be effective. Empirical examples are presented which conform to these conclusions.
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spelling oxford-uuid:14c5c4e6-3310-4f61-8631-c1b07607a3ec2022-03-26T10:21:37ZUtility-based valuation and hedging of basis risk with partial informationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:14c5c4e6-3310-4f61-8631-c1b07607a3ecMathematical Institute - ePrints2010Monoyios, MWe analyse the valuation and hedging of a claim on a non-traded asset using a correlated traded asset under a partial information scenario, when the asset drifts are unknown constants. Using a Kalman filter and a Gaussian prior distribution for the unknown parameters, a full information model with random drifts is obtained. This is subjected to exponential indifference valuation. An expression for the optimal hedging strategy is derived. An asymptotic expansion for small values of risk aversion is obtained via PDE methods, following on from payoff decompositions and a price representation equation. Analytic and semi-analytic formulae for the terms in the expansion are obtained when the minimal entropy measure coincides with the minimal martingale measure. Simulation experiments are carried out which indicate that the filtering procedure can be beneficial in hedging, but sometimes needs to be augmented with the increased option premium, that takes into account parameter uncertainty, in order to be effective. Empirical examples are presented which conform to these conclusions.
spellingShingle Monoyios, M
Utility-based valuation and hedging of basis risk with partial information
title Utility-based valuation and hedging of basis risk with partial information
title_full Utility-based valuation and hedging of basis risk with partial information
title_fullStr Utility-based valuation and hedging of basis risk with partial information
title_full_unstemmed Utility-based valuation and hedging of basis risk with partial information
title_short Utility-based valuation and hedging of basis risk with partial information
title_sort utility based valuation and hedging of basis risk with partial information
work_keys_str_mv AT monoyiosm utilitybasedvaluationandhedgingofbasisriskwithpartialinformation