Unveiling Stock Market Trends Implementing LSTM and KNN Algorithms

Abstract

Abstract: The objective of this study is to enhance and assess the efficacy of Long Short Term Memory (LSTM) and k-Nearest Neighbors (KNN) algorithms in the context of predicting stock prices. This study entails the acquisition of historical data from credible sources pertaining to pricing, as well as other significant variables such trade volume and market mood. Subsequently, the gathered data undergoes a process of cleansing, preprocessing, and refining to ensure its compatibility with the training model. Subsequently, we constructed a forecasting model utilizing Long Short-Term Memory (LSTM) and another forecasting model employing K-Nearest Neighbors (KNN).