STOCK MARKET PREDICTION USING LASSO REGRESSION MODEL

Abstract: The term “stock market” describes the exchanges and markets were buyers and sellers trade equities. Without understanding and knowledge of how the stock market operates, one risks suffering significant financial losses. The market is unpredictable; recent instances include COVID-19 and Russia’s invasion of Ukraine, both of which caused significant losses for the market. Without awareness, people suffer more losses, which strains relationships within families. People are becoming victims of scams and other types of fraud more frequently these days due to the increasing market dangers. We must gain a thorough understanding of the stocks and the market’s operation if we are to prevent those losses [15]. In the stock market, stock exchange prediction is quite significant. Forecasting stock exchange rates is an essential financial topic that is getting more attention since it makes it easier to design profitable trading techniques [9]. It is thought that one of the most intriguing concepts and crucial tasks for the investigation of financial time series is the- forecasting of stock price movement in general. The Least Absolute Shrinkage and Selection Operator (LASSO) method is suggested in this paper as a special way for predicting the behavior of financial markets. A linear regression model is the foundation of LASSO. When there are fewer features than observations, the LASSO approach excels at producing sparse solutions.