A neural network approach to understanding implied volatility movements

DOI10.1080/14697688.2020.1750679zbMath1454.91275OpenAlexW2924076447MaRDI QIDQ5139240

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Publication date: 7 December 2020

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2020.1750679

zbMATH Keywords

VIX indexmoneyness of optionvolatility surface movements

Mathematics Subject Classification ID

Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items (4)

Data-driven hedging of stock index options via deep learning ⋮ Forecast the role of GCC financial stress on oil market and GCC financial markets using convolutional neural networks ⋮ A two-step framework for arbitrage-free prediction of the implied volatility surface ⋮ Challenges in approximating the Black and Scholes call formula with hyperbolic tangents

Cites Work

• Risk minimization in stochastic volatility models: model risk and empirical performance
• Learning minimum variance discrete hedging directly from the market
• Dynamics of implied volatility surfaces
• Learning representations by back-propagating errors
• A logical calculus of the ideas immanent in nervous activity

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