Predicting Individual Equity Options Implied Volatility With Machine Learning

Additional Metadata
Keywords	Machine Learning; Options; Implied Volatility Prediction; Cross-Section of Equity Options; Implied Volatility Surface; Ridge Regression; Lasso Regression; Ordinary Least Squares; Elastic Net; Support Vector Regression; Random Forest; Neural Networks; Ensembles; Variable Importance; Fintech
Thesis Advisor	Grith, M
Persistent URL	hdl.handle.net/2105/67141
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	Knol, L. (2023). Predicting Individual Equity Options Implied Volatility With Machine Learning. In Econometrie.http://hdl.handle.net/2105/67141

Predicting Individual Equity Options Implied Volatility With Machine Learning