Stock Trend Prediction using Machine Learning
This project can help investors make well-informed decisions, stock market prediction has been a focus of financial study. However, reliable forecasting is a difficult task because stock prices show highly volatile and nonlinear characteristics. The complex dependencies in stock market data are frequently missed by conventional statistical methods like linear regression and autoregressive integrated moving average (ARIMA). Deep learning methods, especially Long Short-Term Memory (LSTM) networks and Recurrent Neural Networks (RNNs), have been popular in recent years as efficient time-series forecasting tools.
Authors
- Jitendra Singh (ORCID: https://orcid.org/0000-0002-0951-4097)
- Archana Potnurwar
- Saloni Sonkusare -
- Aniket Binewale -
- Shivam Kunwar -
- Shraddha Patle -
Publication Details
- Journal
- International Journal on Science and Technology
- Published
- 2025-04-20
- DOI
- https://doi.org/10.71097/ijsat.v16.i2.3868
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00