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 Style AAA Style APA 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, April 11). Can Machine Learning Improve Accuracy in Predicting the Implied Volatility Surface of American-Style Options for US Equities?. Econometrie. Retrieved from http://hdl.handle.net/2105/73006

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