Financial markets are fascinating if you can predict them. Also, the traders acting on financial markets produce a vast
amount of information to analyse the consequences of investing according to the current market trends. Stock Market prediction
is the technique to determine whether stock value will go up or down as it plays an active role in the financial gain of nation's
economic status.
The foundation factor for each investor is to gain maximum profits on their investments. If the company's profits go up, you own
some of those profits and if they go down, you lose profits with them. We propose a framework using Long Short Term Memory
machine learning algorithm and adaptive stock technical indicators for efficient forecasting by using various parameters
obtained from the historical data set considered for a particular company. This algorithm works on historical data retrieved from
Yahoo Finance.
