Comparing Pure Stock Portfolio with Stock and Crypto-currency mixed Portfolio through LSTM to Compare & Analyze Investment Opportunities for Portfolio Performance Measurement

Abstract

LSTM (Long Short-Term Memory) has revolutionized the approach to time series prediction many folds due to its appropriate capability to forecast through Non-Linear forecasting methods. It’s observed that RNN has the capability to similarly think through given enough training in accordance to desired functionality models. Due to the Gated Structure referring to storing relevant information and forgetting the irrelevant information’s LSTM made revolutionary accomplishments towards non-linear forecasting that is dependent on human-like behavior. In this research, we have focused on making a comparison between two different portfolio’s which will depend upon LSTM’s future forecasting capability in terms of predicting the best possible output which gets illustrated through Portfolio Optimization principles