Note: This post is part of a broader work for predicting stock prices. The outcome (identified anomaly) is a feature (input) in a LSTM model (within a GAN architecture)- link to the post. Options valuation is a very difficult task. To begin with, it entails using a lot of data points (some are listed below) and some of them are quite subjective (such as the implied volatility -- see below) and difficult to calculate precisely. As an example let us check the calculation for the call's Theta -- θ: Another example of how difficult options pricing is, is the Black-Scholes formula which is used for calculating the options prices themselves.