Citation :

Yash Makwana, Sameer Mudaliar, Tanaya Deshmukh, Abdul Rehman, Aman Shaikh, Rajesh Nasare, 2024. "Stock Trading Assistant" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 2, Issue 2: 42-47.

Abstract :

This abstract explores a unique synergy among three pivotal components within the domain of algorithmic trading: Algorithmic Trading, Price Prediction Models, and News Web Scraping. Each element plays a vital role in shaping the landscape of modern trading strategies and financial decision-making. Algo Trading, the cornerstone of automated trading, leverages complex mathematical algorithms to execute high-frequency, data-driven trading strategies with precision and speed. These algorithms are programmed to analyze market conditions, execute trades, and manage portfolios autonomously. Price Prediction Models have emerged as an indispensable asset in the trading realm. Leveraging historical and real-time data, these models employ advanced statistical techniques and machine learning algorithms to forecast asset prices. Their capabilities range from short-term price trends to long-term market cycles, offering traders valuable insights for crafting informed trading strategies. News Web Scraping, on the other hand, forms the bridge between real-world events and financial markets. By aggregating data from diverse news sources and social media platforms, these tools enable traders to stay ahead of market-moving information. Sentiment analysis, natural language processing, and other AI-driven techniques are used to distill valuable insights from the vast sea of textual data, empowering traders with an information edge. The unique synergy of these three components forms a holistic approach to modern trading. Algo Trading algorithms, supported by accurate Price Prediction Models, can adapt rapidly to changing market conditions. News Web Scraping enhances their agility by providing real-time, context-rich information, which further refines trading strategies and risk management.

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Keywords :

Algo Trading, Price Prediction Models, News Web Scraping, Algorithmic Trading, High Frequency Trading, Price Forecasting, Market Conditions, Sentiment Analysis.