Browsing by Author "Ammar Aamir"

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    Trading Bot
    (Library Information Services, CUI Lahore, 2024) Ammar Aamir; FA20-BCS- 076/LHR; Dr. Zeeshan Gillani
    Wealth creation and the stability of the financial system heavily rely on the stock market, which is an essential part of the global economy where brokers and stakeholders usually trade stock manually. Alternatively, intelligent systems are also used that make predictions based on past data to trade automatically. This project proposes “Trading Bot" that facilitates the traders to make trading simpler on NASDAQ stocks by making educated decisions using deep learning models. Utilizing historical data, a deep learning model forecasts stock closing price. The user-friendly interface enables users to visualize predictions and execute manual or automated trades based on these insights. Additionally, “Trading Bot" can also be useful for amateur users that are interested in investing in stocks.