Manuscript Number : IJSRST162811
The Stock Visualizer : Leveraging Machine Learning for Enhanced Stock Market Analysis and Interactive Financial Insights
Authors(6) :-Alok Mishra, Dr. Razia Sultan, Atebar Haider, Vipin Rawat, M. B. Singh, B. N. Tiwari The Stock Visualizer through Machine Learning is a tool that leverages machine learning techniques to analyze and visualize stock market data. It integrates data from sources like Yahoo Finance and Alpha Vantage, applies preprocessing and feature engineering, and uses models such as ARIMA, LSTM, and random forests for stock predictions and classifications. The system provides interactive visualizations of key financial metrics, including returns, volatility, and the efficient frontier. The tool also evaluates performance through metrics like the Sharpe ratio and offers portfolio optimization insights, aiding decision-making for both individual and institutional investors.
Alok Mishra Stock Visualization, Machine Learning, Stock Predictions, Portfolio Optimization
Publication Details
Published in : Volume 7 | Issue 1 | January-February 2020 Article Preview
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, U.P, India
Dr. Razia Sultan
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, U.P, India
Atebar Haider
Associate Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, U.P, India
Vipin Rawat
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, U.P, India
M. B. Singh
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, U.P, India
B. N. Tiwari
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, U.P, India
Date of Publication : 2020-02-20
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 336-342
Manuscript Number : IJSRST162811
Publisher : Technoscience Academy
Journal URL : https://ijsrst.com/IJSRST162811
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