An Approach to Identify Machine Learning and Deep Learning Methods and Data to Understand Common Time Variant Models That Can Forecast Both Crypto Currencies and Equities

Cryptocurrencies and Equity markets have been the most attractive investment in the modernworld. While these are very attractive, they have been subject to a lot of volatility in theirbehaviour due to multiple reasons, such as macroeconomic conditions and regulation in variouseconomic activities within countries and the world as a whole. There has been minimal researchin this area to use Machine learning and deep learning approach to help predict the price ofcryptocurrency and equities and other behaviours. There has also been very minimal research tounderstand the relationship on whether the change in the value of equities has an effect on thevalue of cryptocurrencies and vice versa. These effects are due to correlational causal or anyother kind of relationship between the values of both the investment asset classes.This research aims to identify models based on Machine learning and deep learning that canpredict the price or value of cryptocurrencies and equities. Secondly, the study also aims tounderstand the effect of these two asset classes on each other with respect to their value undercertain scenarios to understand if they share causal correlational or any other type of relationship,which is yet to be determined.