Analyzing the Effectiveness of Machine Learning Models in Nifty50 Next Day Prediction: A Comparative Analysis

The stock market is a prediction is a complicated task and is difficult to predict accurately using traditional methods. It also relates to the economy of the country. Advance knowledge and education can make a person a good investor. Machine learning algorithms have shown great efficiency in predicting the short term and long-term stock prices by analyzing a large amount of historical data. In this research, we compare the performance of five popular machine learning algorithms in predicting stock prices: Random Forest, SVR, Ridge, Lasso Regression and KNN model. The study is conducted using a dataset of historical stock prices of the NIFTY50 index, covering the period from March 2022 to March 2023. The performance of the models is evaluated using various metrics, including Mean Absolute Error (MAE) and R squared (R2). The results show that the (SVR) Support Vector Regression model outperforms the other models in terms of accuracy followed by Lasso and Random Forest with same accuracy and then followed by KNN and at last Ridge model.