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Deep Learning Volatility
16 references·2 citing·37 second hop
Deep Learning Volatility (2019)Deep Learning VolatilityVolatility Is Rough (2018)Volatility Is RoughShort-time near-the-money skew in rough fractional volatility models (2018)Short-time near-the-money ske…Perfect hedging in rough Heston models (2018)Perfect hedging in rough Hest…Machine Learning for Quantitative Finance: Fast Derivative Pricing, Hedging and Fitting (2018)Machine Learning for Quantita…Hybrid scheme for Brownian semistationary processes (2017)Hybrid scheme for Brownian se…Model Calibration with Neural Networks (2016)Model Calibration with Neural…Stochastic Volatility Modeling (2015)Stochastic Volatility ModelingProbability Distribution in the SABR Model of Stochastic Volatility (2015)Probability Distribution in t…Pricing under rough volatility (2015)Pricing under rough volatilityArbitrage-free SVI volatility surfaces (2013)Arbitrage-free SVI volatility…Asymptotic analysis for stochastic volatility: martingale expansion (2010)Asymptotic analysis for stoch…On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility (2007)On the short-time behavior of…A perfect calibration! now what? (2004)A perfect calibration! now wh…A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)A Nonparametric Approach to P…A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)A Nonparametric Approach to P…Quelques applications de la formule de changement de variables pour les semimartingales (1970)Quelques applications de la f…Deep Curve-Dependent PDEs for Affine Rough Volatility (2023)Deep Curve-Dependent PDEs for…Differential Machine Learning (2020)Differential Machine LearningOn Square Integrable Martingales (1967)Martingales on Jump Processes. I: Representation Results (1975)Sur l'int�grabilit� uniforme des martingales exponentielles (1978)Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models (2020)The Pricing of Options and Corporate Liabilities (1973)A Theory of the Term Structure of Interest Rates (1985)A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options (1993)The Little Heston Trap (2006)Calibration and hedging under jump diffusion (2007)The Pricing of Options on Assets with Stochastic Volatilities (1987)Limit Theorems for Stochastic Processes (2003)Multifactor Approximation of Rough Volatility Models (2019)Transform Analysis and Asset Pricing for Affine Jump-diffusions (2000)Time Dependent Heston Model (2010)The Variance Gamma Process and Option Pricing (1998)Option valuation using the fast Fourier transform (1999)A neural network-based framework for financial model calibration (2019)Machine learning sentiment analysis, COVID-19 news and stock market reactions (2023)Fractional Brownian Motions, Fractional Noises and Applications (1968)Modeling and Forecasting Realized Volatility (2003)The microstructural foundations of leverage effect and rough volatility (2018)The characteristic function of rough Heston models (2019)Martingales and arbitrage in multiperiod securities markets (1979)Martingales and stochastic integrals in the theory of continuous trading (1981)Brownian Motion and Stochastic Calculus (2007)BENCHOP – The BENCHmarking project in option pricing (2015)Neural Networks for Option Pricing and Hedging: A Literature Review (2019)The Volatility Surface: A Practitioner's Guide (2006)Realized Volatility: A Review (2008)A Stochastic Approximation Method (1951)Theory of Rational Option Pricing (1973)Nonparametric risk management and implied risk aversion (2000)Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)Deep Learning for Finance: Deep Portfolios (2016)Regularization Neural Network for Construction Cost Estimation (1998)Forecasting exchange rates using general regression neural networks (2000)Pricing and hedging derivative securities with neural networks and a homogeneity hint (2000)
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References

  • 2018Volatility Is Rough793 cited
  • 1994A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks718 cited
  • 2015Pricing under rough volatility461 cited
  • 2007On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility239 cited
  • 1994A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks239 cited
  • 2013Arbitrage-free SVI volatility surfaces224 cited
  • 1970Quelques applications de la formule de changement de variables pour les semimartingales191 cited
  • 2004A perfect calibration! now what?175 cited
  • 2010Asymptotic analysis for stochastic volatility: martingale expansion160 cited
  • 2018Machine Learning for Quantitative Finance: Fast Derivative Pricing, Hedging and Fitting158 cited
  • 2018Perfect hedging in rough Heston models138 cited
  • 2017Hybrid scheme for Brownian semistationary processes128 cited
  • 2015Probability Distribution in the SABR Model of Stochastic Volatility107 cited
  • 2015Stochastic Volatility Modeling100 cited
  • 2016Model Calibration with Neural Networks70 cited

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2018
Short-time near-the-money skew in rough fractional volatility models
68 cited

Cited by

  • 2020Differential Machine Learning34 cited
  • 2023Deep Curve-Dependent PDEs for Affine Rough Volatility33 cited