Abstract:
The stock market is very volatile in nature. Traders thrive on this volatility by buying stock when they are low and selling high or by exercising options or trading the ...View moreMetadata
Abstract:
The stock market is very volatile in nature. Traders thrive on this volatility by buying stock when they are low and selling high or by exercising options or trading the option contracts. This can only be done if market movement trends are known. Recent advances in deep learning and neural networks have remodeled the markets. This paper attempts to analyze the gains in buying stocks, call options and exercising options. Stock price movements of major oil conglomerates in India are forecasted namely Indian Oil Corporation, Oil and Natural Gas Corporation and Reliance Industries Limited, using a custom LSTM neural network. This stock prediction model is benchmarked against FOREX, Crude oil rates, historical data of companies and their major multinational oil suppliers, along with their financial news sentiments, of the past three years. The option pricing model uses the Monte Carlo simulation, similar to Black-Scholes Model to accurately determine the call option prices. The computational results of these implementations and most importantly their accuracies are deliberated.
Published in: 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Date of Conference: 06-08 July 2021
Date Added to IEEE Xplore: 03 November 2021
ISBN Information: