Functional central limit theorems for rough volatility
The non-Markovian nature of rough volatility makes Monte Carlo methods challenging, and it is in fact a major challenge to develop fast and accurate simulation algorithms. We provide an efficient one for stochastic Volterra processes, based on an extension of Donsker’s approximation of Brownian moti...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Springer
2024
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| _version_ | 1811139799256399872 |
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| author | Horvath, B Jacquier, A Muguruza, A Søjmark, A |
| author_facet | Horvath, B Jacquier, A Muguruza, A Søjmark, A |
| author_sort | Horvath, B |
| collection | OXFORD |
| description | The non-Markovian nature of rough volatility makes Monte Carlo methods challenging, and it is in fact a major challenge to develop fast and accurate simulation algorithms. We provide an efficient one for stochastic Volterra processes, based on an extension of Donsker’s approximation of Brownian motion to the fractional Brownian case with arbitrary Hurst exponent H∈(0, 1). Some of the most relevant consequences of this ‘rough Donsker (rDonsker) theorem’ are functional weak convergence results in Skorokhod space for discrete approximations of a large class of rough stochastic volatility models. This justifies the validity of simple and easy-to-implement Monte Carlo methods, for which we provide detailed numerical recipes. We test these against the current benchmark hybrid scheme and find remarkable agreement (for a large range of values of H). Our rDonsker theorem further provides a weak convergence proof for the hybrid scheme itself and allows constructing binomial trees for rough volatility models, the first available scheme (in the rough volatility context) for early exercise options such as American or Bermudan options. |
| first_indexed | 2024-09-25T04:11:49Z |
| format | Journal article |
| id | oxford-uuid:37de18e4-2d87-4ef3-82ee-6bb5fca1529a |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:11:49Z |
| publishDate | 2024 |
| publisher | Springer |
| record_format | dspace |
| spelling | oxford-uuid:37de18e4-2d87-4ef3-82ee-6bb5fca1529a2024-06-28T20:07:10ZFunctional central limit theorems for rough volatilityJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:37de18e4-2d87-4ef3-82ee-6bb5fca1529aEnglishJisc Publications RouterSpringer2024Horvath, BJacquier, AMuguruza, ASøjmark, AThe non-Markovian nature of rough volatility makes Monte Carlo methods challenging, and it is in fact a major challenge to develop fast and accurate simulation algorithms. We provide an efficient one for stochastic Volterra processes, based on an extension of Donsker’s approximation of Brownian motion to the fractional Brownian case with arbitrary Hurst exponent H∈(0, 1). Some of the most relevant consequences of this ‘rough Donsker (rDonsker) theorem’ are functional weak convergence results in Skorokhod space for discrete approximations of a large class of rough stochastic volatility models. This justifies the validity of simple and easy-to-implement Monte Carlo methods, for which we provide detailed numerical recipes. We test these against the current benchmark hybrid scheme and find remarkable agreement (for a large range of values of H). Our rDonsker theorem further provides a weak convergence proof for the hybrid scheme itself and allows constructing binomial trees for rough volatility models, the first available scheme (in the rough volatility context) for early exercise options such as American or Bermudan options. |
| spellingShingle | Horvath, B Jacquier, A Muguruza, A Søjmark, A Functional central limit theorems for rough volatility |
| title | Functional central limit theorems for rough volatility |
| title_full | Functional central limit theorems for rough volatility |
| title_fullStr | Functional central limit theorems for rough volatility |
| title_full_unstemmed | Functional central limit theorems for rough volatility |
| title_short | Functional central limit theorems for rough volatility |
| title_sort | functional central limit theorems for rough volatility |
| work_keys_str_mv | AT horvathb functionalcentrallimittheoremsforroughvolatility AT jacquiera functionalcentrallimittheoremsforroughvolatility AT muguruzaa functionalcentrallimittheoremsforroughvolatility AT søjmarka functionalcentrallimittheoremsforroughvolatility |