Dr. k. Sundara Velrani, S Kiyas Mohamed, Madhu Metha A, Kishore T, Jivika M, Jose Lyvin S
Abstract
The number of cryptocurrency markets has increased in number over time. Hence, there is a growing demand for advanced trading platforms that are capable of analyzing the current market trends and carrying out the transactions automatically. The process of trading in the traditional way takes a lot of time and effort because of the errors made by traders during transactions. In this study, I would investigate ways in which an Automated Forex Trading Platform that analyzes real-time data from the market of cryptocurrency in Binance would be developed. An Automated Forex Trading Platform assists users in trading cryptocurrencies with parameters such as Relative Strength Index (RSI). The system has several modules that include login by users, trading module, market analysis, and trading history. The platform collects real-time data on prices and candlesticks using the Binance API and then shows the results graphically. The system utilizes a basic machine learning algorithm through linear regression for making predictions about price changes in cryptocurrencies. Several assets are used in carrying out transactions in the Automated Forex Trading Platform and they include BTCUSDT, ETHUSDT, and BNBUSDT.In addition, it is worth pointing out that all trading operations are carried out in the testing mode, which eliminates any financial risks and provides an opportunity to hone his skills.
Automated Forex Trading Platform is the title for this research work in which an automated platform is built that analyzes market data to trade automatically. This system uses live market data provided by the Binance API along with the usage of technical indicators like Relative Strength Index (RSI) and Linear Regression based Machine Learning model for making appropriate decisions.
This paper presents a demonstration of how automation can help in reducing human labor and making faster and accurate decisions for trading. This system provides trading alerts including buy, sell, or hold signal based on current market analysis. Using a simulated environment helps in evaluating trading strategies without any monetary risks involved.
The results indicate that combining real-time data analysis with predictive techniques enhances trading efficiency and provides valuable insights into market behavior. The user- friendly interface further improves accessibility for both beginners and experienced users.
The combination of real-time data analytics, technical indicators, and predictive models improves the efficiency of the trading process and gives valuable insights about market trends. The intuitive graphical user interface guarantees that the platform will be user-friendly and convenient to use even for novice traders.
To conclude, the proposed system is an efficient and effective solution for implementing automated trading with cryptocurrencies. Moreover, it creates great opportunities for further development, including using more advanced technologies like machine learning and implementing real- time trading functions.
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How to Cite This Paper
Dr. k. Sundara Velrani, S Kiyas Mohamed, Madhu Metha A, Kishore T, Jivika M, Jose Lyvin S (2026). Automated Forex Trading Platform Using Binance. International Journal of Computer Techniques, 13(2). ISSN: 2394-2231.
