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@article{171967,
        author = {Allu Rajesh and Vimal Dhama and Lagineni Reddy sai and Nallapareddy Lokeshwar Reddy},
        title = {Stock Market Prediction for Manufacturing  Consistency Using Custom Algorithm},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {1614-1618},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171967},
        abstract = {It presents a challenge in the trading activities of stock prices in the manufacturing sector because most traditional methods for trading are incapable of responding effectively and rapidly to changing market conditions. This paper attempts to propose a stock market trading algorithm based on custom strategies developed using Keltner Channel and Simple Moving Average (SMA) indicators. The purpose is to boost trading performance through automated buy and sell signals that ensure timely entry and exit into the market. The approach incorporates real-time data through platforms like Trading View and Google Colab, while utilizing Python libraries including pandas, matplotlib, pandas_ta, and yfinance. This algorithm will optimize returns and minimize risks for traders in the manufacturing sector. It will further provide adequate resource allocation, eliminate the error rate in manual trading, and help with actioning insights for long-term market planning.},
        keywords = {},
        month = {January},
        }