Deep learning volatility : a deep neural network perspective on pricing and calibration in (rough) volatility models
Blanka Horvath, Aitor Muguruza and Mehdi Tomas
| Year of publication: |
2021
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|---|---|
| Authors: | Horvath, Blanka Nora ; Muguruza, Aitor ; Tomas, Mehdi |
| Published in: |
Quantitative finance. - London : Taylor & Francis, ISSN 1469-7696, ZDB-ID 2027557-2. - Vol. 21.2021, 1, p. 11-27
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| Subject: | Accurate price approximation | Calibration | Machine learning | Model assessment | Monte Carlo | Rough volatility | Volatility modelling | Volterra process | Volatilität | Volatility | Neuronale Netze | Neural networks | Künstliche Intelligenz | Artificial intelligence | Optionspreistheorie | Option pricing theory | Prognoseverfahren | Forecasting model | Stochastischer Prozess | Stochastic process | Monte-Carlo-Simulation | Monte Carlo simulation |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1080/14697688.2020.1817974 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012424629