The Stock Visualizer : Leveraging Machine Learning for Enhanced Stock Market Analysis and Interactive Financial Insights

Authors

  • Alok Mishra  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

Keywords:

Stock Visualization, Machine Learning, Stock Predictions, Portfolio Optimization

Abstract

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.

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Published

2020-02-20

Issue

Section

Research Articles

How to Cite

[1]
Alok Mishra, Dr. Razia Sultan, Atebar Haider, Vipin Rawat, M. B. Singh, B. N. Tiwari "The Stock Visualizer : Leveraging Machine Learning for Enhanced Stock Market Analysis and Interactive Financial Insights" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 7, Issue 1, pp.336-342, January-February-2020.