Can Machine Learning Improve Accuracy in Predicting the Implied Volatility Surface of American-Style Options for US Equities?

Additional Metadata
Keywords	Black-Scholes (BS); Ad-Hoc Black-Scholes (AHBS); Carr and Wu (CW); Implied Volatility (IV); Feed-Forward Neural Network (FFNN); Implied Volatility Mean Squared Error (IVRMSE)
Thesis Advisor	Grith, M
Persistent URL	hdl.handle.net/2105/73006
Series	Econometrie
Organisation	Erasmus School of Economics
Citation APA APA Style APA-ALL Style AAA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Watters, A. (2024). Can Machine Learning Improve Accuracy in Predicting the Implied Volatility Surface of American-Style Options for US Equities?. In Econometrie.http://hdl.handle.net/2105/73006

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