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VolGAN: A Generative Model for Arbitrage-Free Implied Volatility Surfaces
16 references·0 citing·39 second hop
VolGAN: A Generative Model for Arbitrage-Free Implied Volatility Surfaces (2024)VolGAN: A Generative Model for Arbitrage-…Fin-GAN: forecasting and classifying financial time series via generative adversarial networks (2024)Fin-GAN: forecasting and clas…Quant GANs: deep generation of financial time series (2020)Quant GANs: deep generation o…Modeling financial time-series with generative adversarial networks (2019)Modeling financial time-serie…Deep hedging (2019)Deep hedgingThe Volatility Surface: A Practitioner's Guide (2006)The Volatility Surface: A Pra…THE RANGE OF TRADED OPTION PRICES (2006)THE RANGE OF TRADED OPTION PR…Recovering volatility from option prices by evolutionary optimization (2005)Recovering volatility from op…Financial Modelling with Jump Processes (2004)Financial Modelling with Jump…Financial Modelling with Jump Processes (2003)Financial Modelling with Jump…Stochastic Models of Implied Volatility Surfaces (2002)Stochastic Models of Implied …Dynamics of implied volatility surfaces (2002)Dynamics of implied volatilit…Sample Size Requirements for Estimating Pearson, Kendall and Spearman Correlations (2000)Sample Size Requirements for …A market model for stochastic implied volatility (1999)A market model for stochastic…Implied Volatility Functions: Empirical Tests (1998)Implied Volatility Functions:…A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)A Nonparametric Approach to P…A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options (1993)A Closed-Form Solution for Op…Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers. (1996)Confidence intervals for Kendall's tau (1997)Empirical Size, Coverage, and Power of Confidence Intervals for Spearman's Rho (1997)Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning (2014)Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. (2016)The psychological roots of anti-vaccination attitudes: A 24-nation investigation. (2018)The Pricing of Options and Corporate Liabilities (1973)Theory of Rational Option Pricing (1973)A Theory of the Term Structure of Interest Rates (1985)Transform Analysis and Asset Pricing for Affine Jump-diffusions (2000)The Cross‐Section of Volatility and Expected Returns (2006)Empirical Performance of Alternative Option Pricing Models (1997)Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics (2001)Non-parametric calibration of jump–diffusion option pricing models (2004)Specification Analysis of Option Pricing Models Based on Time‐Changed Lévy Processes (2004)Statistical Arbitrage in the U.S. Equities Market (2008)Stochastic Integration and Differential Equations (2005)Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps (2009)Threshold bipower variation and the impact of jumps on volatility forecasting (2010)The Pricing of Options on Assets with Stochastic Volatilities (1987)Post-'87 crash fears in the S&P 500 futures option market (2000)Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices (2001)Differences of Opinion, Short-Sales Constraints, and Market Crashes (2003)Generalized autoregressive conditional heteroskedasticity (1986)Neural Networks for Option Pricing and Hedging: A Literature Review (2019)Recent advances in reinforcement learning in finance (2023)A Stochastic Approximation Method (1951)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)European Option Pricing with Transaction Costs (1993)Exact Simulation of Stochastic Volatility and Other Affine Jump Diffusion Processes (2006)Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis (2021)The Relative Contribution of Jumps to Total Price Variance (2005)A Novel Pricing Method for European Options Based on Fourier-Cosine Series Expansions (2008)What's Vol Got to Do with It (2010)A comparison of biased simulation schemes for stochastic volatility models (2009)Pricing under rough volatility (2015)Volatility Is Rough (2018)
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References

  • 1993A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options8,768 cited
  • 2003Financial Modelling with Jump Processes3,261 cited
  • 1998Implied Volatility Functions: Empirical Tests1,248 cited
  • 2000Sample Size Requirements for Estimating Pearson, Kendall and Spearman Correlations1,131 cited
  • 2006The Volatility Surface: A Practitioner's Guide747 cited
  • 1994A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks718 cited
  • 2004Financial Modelling with Jump Processes443 cited
  • 2002Dynamics of implied volatility surfaces433 cited
  • 2020Quant GANs: deep generation of financial time series351 cited
  • 2019Deep hedging332 cited
  • 2006THE RANGE OF TRADED OPTION PRICES205 cited
  • 2019Modeling financial time-series with generative adversarial networks182 cited
  • 1999A market model for stochastic implied volatility158 cited
  • 2005Recovering volatility from option prices by evolutionary optimization110 cited
  • 2024Fin-GAN: forecasting and classifying financial time series via generative adversarial networks98 cited

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2002
Stochastic Models of Implied Volatility Surfaces
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