In this project, we studied stock option chains and their implied volatilities. We built custom probabilistic models, called Implied Probability Distribution, for stock prices in future. All of the analysis is done in R programming language, using several special libraries for financial analysis.
More concretely, we gathered the option data for various stocks from April 2, 2018 with a maturity date of April 20th. Based on this data, and using a method developed by Breeden and Litzenberger in 1978, we graphed the implied probability distributions of these stocks, and computed their expected value. On April 20th, we compared our expected market prices to the actual market prices, and we observed a remarkable accuracy.
Zou, Xuebin; Salazar, Julio C.; Huang, Jiehao; and Mei, Kevin, "Modeling and Predicting Future Stock Prices Using Stock Options" (2018). CUNY Academic Works.