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Autori principali: Hambly, Ben, Kolliopoulos, Nikolaos
Natura: Preprint
Pubblicazione: 2019
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Accesso online:https://arxiv.org/abs/1906.05898
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author Hambly, Ben
Kolliopoulos, Nikolaos
author_facet Hambly, Ben
Kolliopoulos, Nikolaos
contents We consider a structural stochastic volatility model for the loss from a large portfolio of credit risky assets. Both the asset value and the volatility processes are correlated through systemic Brownian motions, with default determined by the asset value reaching a lower boundary. We prove that if our volatility models are picked from a class of mean-reverting diffusions, the system converges as the portfolio becomes large and, when the vol-of-vol function satisfies certain regularity and boundedness conditions, the limit of the empirical measure process has a density given in terms of a solution to a stochastic initial-boundary value problem on a half-space. The problem is defined in a special weighted Sobolev space. Regularity results are established for solutions to this problem, and then we show that there exists a unique solution. In contrast to the CIR volatility setting covered by the existing literature, our results hold even when the systemic Brownian motions are taken to be correlated.
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publishDate 2019
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spellingShingle Stochastic PDEs for large portfolios with general mean-reverting volatility processes
Hambly, Ben
Kolliopoulos, Nikolaos
Probability
Analysis of PDEs
Portfolio Management
Pricing of Securities
Risk Management
60H15, 60H07, 91G80
We consider a structural stochastic volatility model for the loss from a large portfolio of credit risky assets. Both the asset value and the volatility processes are correlated through systemic Brownian motions, with default determined by the asset value reaching a lower boundary. We prove that if our volatility models are picked from a class of mean-reverting diffusions, the system converges as the portfolio becomes large and, when the vol-of-vol function satisfies certain regularity and boundedness conditions, the limit of the empirical measure process has a density given in terms of a solution to a stochastic initial-boundary value problem on a half-space. The problem is defined in a special weighted Sobolev space. Regularity results are established for solutions to this problem, and then we show that there exists a unique solution. In contrast to the CIR volatility setting covered by the existing literature, our results hold even when the systemic Brownian motions are taken to be correlated.
title Stochastic PDEs for large portfolios with general mean-reverting volatility processes
topic Probability
Analysis of PDEs
Portfolio Management
Pricing of Securities
Risk Management
60H15, 60H07, 91G80
url https://arxiv.org/abs/1906.05898