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Calibrating Rough Volatility Models: A Convolutional Neural Network Approach
| Content Provider | Scilit |
|---|---|
| Author | Stone, Henry |
| Copyright Year | 2019 |
| Description | Journal: SSRN Electronic Journal In this paper we use convolutional neural networks to find the Holder exponent of simulated sample paths of the rBergomi model, a recently proposed stock price model used in mathematical finance. We contextualise this as a calibration problem, thereby providing a very practical and useful application. |
| Related Links | http://arxiv.org/pdf/1812.05315 https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=3327135 |
| ISSN | 10914358 |
| e-ISSN | 15565068 |
| DOI | 10.2139/ssrn.3327135 |
| Journal | SSRN Electronic Journal |
| Language | English |
| Publisher | Elsevier BV |
| Publisher Date | 2019-02-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: SSRN Electronic Journal Operations Research and Management Science Rough Volatility Convolutional Neural Networks |
| Content Type | Text |
| Resource Type | Article |
| Subject | Public Health, Environmental and Occupational Health Psychiatry and Mental Health |