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Deep Learning Volatility · Study

PreprintShelves

PreprintDeep Learning Volatility

Blanka N. Horvath2019

OA

Preprintgreen2019

Deep Learning Volatility

Blanka N. Horvath · Aitor Muguruza · Mehdi Tomas

52 citations·0/0 files stored·SSRN Electronic Journal

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Stochastic processes and financial applications Financial Risk and Volatility Modeling Stock Market Forecasting Methods

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References

2018Volatility Is Rough 1994A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks 2015Pricing under rough volatility 2007On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility 1994A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks 2013Arbitrage-free SVI volatility surfaces 1970Quelques applications de la formule de changement de variables pour les semimartingales 2004A perfect calibration! now what?

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2020Differential Machine Learning 2023Deep Curve-Dependent PDEs for Affine Rough Volatility

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2025On Deep Calibration of (rough) Stochastic Volatility Modelsarticle · 10 shared references 2023Deep Curve-Dependent PDEs for Affine Rough Volatilityarticle · 10 shared references 2020Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility modelsarticle · 9 shared references 2024Functional central limit theorems for rough volatilityarticle · 9 shared references 2022Empirical analysis of rough and classical stochastic volatility models to the SPX and VIX marketsarticle · 8 shared references 2017On VIX futures in the rough Bergomi modelarticle · 7 shared references

Details

Year2019

Typepreprint

Published2019-01-01

VenueSSRN Electronic Journal

ISSN-L1556-5068

Languageen

Citations52

Files0 public / 0

ShelfStochastic processes and financial applications

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doi10.2139/ssrn.3322085

openalex_workW2914215310

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