[2] Blackburn, J. D., Scudder, G. D., and Van Wassenhove, L. N. 1996. Improving Speed and Productivity of Software Development: A Global Survey of Software Developers. IEEE Trans. Softw. Eng. 22, 12 (Dec. 1996), 875-885. [3] Lam, H.E. and Maheshwari, P. (

Authors

  • VEDANT KAKDE Computer Engineering St. Vincent Pallotti College of Engineering and Technology Nagpur, India
  • YASH CHAUHAN Computer Engineering St. Vincent Pallotti College of Engineering and Technology Nagpur, India
  • SIDDHESH PANJARE Computer Engineering St. Vincent Pallotti College of Engineering and Technology Nagpur, India
  • RAGHAVAN NAIDU
  • DIPAK WAJGI Computer Engineering St. Vincent Pallotti College of Engineering and Technology Nagpur, India

Keywords:

component, Data Mining, Machine Learning, Stock Market forcasting

Abstract

The stock market is a complex and dynamic system that requires constant monitoring and analysis to make informed investment decisions. In recent years, the use of mobile applications has become increasingly popular for tracking stock market trends, providing investors with real-time updates and predictive insights. In this research paper, we present the design and development of an Android app that monitors and predicts the stock market.

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Published

29-04-2023

How to Cite

VEDANT KAKDE, YASH CHAUHAN, SIDDHESH PANJARE, RAGHAVAN NAIDU, & DIPAK WAJGI. (2023). [2] Blackburn, J. D., Scudder, G. D., and Van Wassenhove, L. N. 1996. Improving Speed and Productivity of Software Development: A Global Survey of Software Developers. IEEE Trans. Softw. Eng. 22, 12 (Dec. 1996), 875-885. [3] Lam, H.E. and Maheshwari, P. (. International Journal for Research Publication and Seminar, 14(3), 269–273. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/501

Issue

Vol. 14 No. 3 (2023): Vol 14 | Issue 3 | NCASIT 2023

Section

Original Research Article

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