Hedging the risk of delayed data in defaultable markets
Hedging the risk of delayed data in defaultable markets
We investigate hedging the risk of delayed data in certain defaultable securities through the local risk minimization approach. From a financial point of view, this indicates that in addition to the risk of default, investors also face incomplete accounting data. In our analysis, the delay is modeled by a random time change, and different levels of information, including the full market's, management's, and investors' information, are distinguished. We obtain semi-explicit solutions for pseudo locally risk minimizing hedging strategies from the perspective of investors where the results are presented according to the solutions of partial differential equations. In obtaining the main results of this paper, we apply a filtration expansion theorem that determines the canonical decomposition of {stopped} special semimartingales in an enlarged filtration of investors' information.
Defaultable claims, Pseudo local risk minimization, Intensity, Delayed data, Random time change
101-130
Okhrati, Ramin
e8e0b289-be8c-4e73-aea5-c9835190a54a
2019
Okhrati, Ramin
e8e0b289-be8c-4e73-aea5-c9835190a54a
Abstract
We investigate hedging the risk of delayed data in certain defaultable securities through the local risk minimization approach. From a financial point of view, this indicates that in addition to the risk of default, investors also face incomplete accounting data. In our analysis, the delay is modeled by a random time change, and different levels of information, including the full market's, management's, and investors' information, are distinguished. We obtain semi-explicit solutions for pseudo locally risk minimizing hedging strategies from the perspective of investors where the results are presented according to the solutions of partial differential equations. In obtaining the main results of this paper, we apply a filtration expansion theorem that determines the canonical decomposition of {stopped} special semimartingales in an enlarged filtration of investors' information.
Text
Okhrati 2019 intensity 11
- Accepted Manuscript
More information
Accepted/In Press date: 1 March 2019
e-pub ahead of print date: 6 May 2019
Published date: 2019
Keywords:
Defaultable claims, Pseudo local risk minimization, Intensity, Delayed data, Random time change
Identifiers
Local EPrints ID: 430242
URI: http://eprints.soton.ac.uk/id/eprint/430242
ISSN: 1350-486X
PURE UUID: 8de0e78e-84e6-4d33-86fe-bdf795204d23
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Date deposited: 23 Apr 2019 16:30
Last modified: 16 Mar 2024 07:46
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Author:
Ramin Okhrati
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