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Essays On Applied Machine Learning For Implied Volatility Interpolation And Artificial Counterfactuals, Pablo A. Crespo

Dissertations, Theses, and Capstone Projects

This dissertation consists of two chapters.

Chapter 1: Volatility estimates under the risk neutral density have become a much revisited topic of interest in recent years. The density proves itself a powerful tool for sentiment analysis, since its moments provide insights about expectations in price trends. A standard procedure for its extraction utilizes artificial volatility predictions to form a dense enough grid for approximating a complete probability distribution. This paper proposes two common machine learning technique variations to produce implied volatility predictions when data is very scarce. First, a model using regularization through a variation of a generalized LASSO path …