Implied volatility parameterization based on a machine learning polynomial approach
Implied volatility parameterization based on a machine learning polynomial approach is a scholarly work, published in 2018 in ''Intelligent Data Analysis''. The main subjects of the publication include econometrics, mathematics, electricity market, artificial intelligence, computer science, machine learning, polynomial, implied volatility, market forecast, and volatility. The authors propose a machine learning polynomial approach due to the smile shaped behavior of implied volatility and investigate it with a regularization penalty term to fit the Out-The-Money volatility data and authors compare the result with the prominent counterpart SVI.