Index Option Greek Analysis with Heikin-Ashi Transformed Data and Its prediction with Artificial Neural Network

Abstract

This paper analyses the Index Option Greek with respect to a transformed data set of Index that has been Heikin Ashi Transformed. It has been noted that Heikin Ashi Transformation can provide better prediction than normal data and the noise effect can also be used to filter out if volume weights are also considered. This paper tries to predict option greeks for index option with the help of a Neural Network setup. Since option greeks play a very important role in understanding the correct pricing of index option, the paper provides some useful insights in such models.