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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 13, ISSUE 5, MAY 2024

Algorithm based Automatic Trading System

Prof. S. P. Bhadre, Pratik Chougule, Shreya Gore, Prathmesh Pawar, Ramraje Bakle, Sujwal Lambe

DOI: 10.17148/IJARCCE.2024.13555

Abstract: Automatic trading, also known as algorithmic trading, represents the pinnacle of technological advancement in financial markets. Through the utilization of sophisticated algorithms, automatic trading systems execute trades with unparalleled speed and efficiency, operating 24/7 across global markets. These systems remove the human element from decision-making, eliminating emotional biases and executing trades based solely on pre-defined rules and criteria. By leveraging historical data, technical indicators, and statistical models, automatic trading systems can identify and capitalize on market opportunities that may be imperceptible to human traders. However, with the potential for high- speed execution comes inherent risks, including technical glitches, data inaccuracies, and susceptibility to unforeseen market events. Consequently, successful implementation of automatic trading requires meticulous development, rigorous testing, and ongoing monitoring to ensure optimal performance and risk management. Despite these challenges, automatic trading continues to revolutionize the financial landscape, offering both institutional and retail investors unprecedented access to sophisticated trading strategies and opportunities.

Keywords: Algorithm, Automatic, Flutter Framework, Risk Management, Stock Market, Strategies, Trading Bots.

How to Cite:

[1] Prof. S. P. Bhadre, Pratik Chougule, Shreya Gore, Prathmesh Pawar, Ramraje Bakle, Sujwal Lambe, “Algorithm based Automatic Trading System,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2024.13555