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Main Authors: Di Nunno, Giulia, Yurchenko-Tytarenko, Anton
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2209.13054
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author Di Nunno, Giulia
Yurchenko-Tytarenko, Anton
author_facet Di Nunno, Giulia
Yurchenko-Tytarenko, Anton
contents We consider stochastic volatility dynamics driven by a general Hölder continuous Volterra-type noise and with unbounded drift. For these so-called SVV-models, we consider the explicit computation of quadratic hedging strategies. While the theoretical hedge is well-known in terms of the non-anticipating derivative for all square integrable claims, the fact that these models are typically non-Markovian provides is a challenge in the direct computation of conditional expectations at the core of the explicit hedging strategy. To overcome this difficulty, we propose a Markovian approximation of the model which stems from an adequate approximation of the kernel in the Volterra noise. We study the approximation of the volatility, of the prices and of the optimal mean-square hedge. We provide the corresponding error estimates. The work is completed with numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2209_13054
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Sandwiched Volterra Volatility model: Markovian approximations and hedging
Di Nunno, Giulia
Yurchenko-Tytarenko, Anton
Mathematical Finance
We consider stochastic volatility dynamics driven by a general Hölder continuous Volterra-type noise and with unbounded drift. For these so-called SVV-models, we consider the explicit computation of quadratic hedging strategies. While the theoretical hedge is well-known in terms of the non-anticipating derivative for all square integrable claims, the fact that these models are typically non-Markovian provides is a challenge in the direct computation of conditional expectations at the core of the explicit hedging strategy. To overcome this difficulty, we propose a Markovian approximation of the model which stems from an adequate approximation of the kernel in the Volterra noise. We study the approximation of the volatility, of the prices and of the optimal mean-square hedge. We provide the corresponding error estimates. The work is completed with numerical simulations.
title Sandwiched Volterra Volatility model: Markovian approximations and hedging
topic Mathematical Finance
url https://arxiv.org/abs/2209.13054