Stock Market (NIFTY) Forecasting using Machine Learning Analysis on Option Chain

Abstract

Stock market prediction is a long-time intriguing topic to researchers from different fields. Stock market data is extremely volatile and hence laborious to model. In particular, innumerable studies have been conducted to predict the movement of stock market using Machine Learning algorithms such as Regression Techniques, Time Series Forecasting, Indices Modelling, Natural Language Processing and more, but there is still room for improvement. Also, Option chain and Options have been the subjects that not many have ventured into, leading us to this subject. Mainly, NIFTY and BANKNIFTY Options account for 70% of total derivatives traded and much more turnover than all stocks combined. This research paper attempts to figure out the utility of Option Chain in predicting the direction of movement in NIFTY. We have tried how different features from Option chain can be extracted, and the resulting problem can be solved using Machine Learning techniques and Deep Learning techniques.