THE ROLE OF DATA SCIENCE IN MODERN TRADING SYSTEMS

In recent years, data science has become a fundamental component of financial trading systems. By leveraging large datasets, advanced statistical models, and machine learning algorithms, traders and financial institutions can analyze market behavior, forecast price movements, and optimize trading strategies. This article explores the role of data science in trading, focusing on analytical techniques, predictive modeling, and algorithmic decision-making. The study highlights how data-driven approaches improve efficiency, reduce risks, and enhance profitability in financial markets.近年来，数据科学已成为金融交易系统的核心组成部分。借助大规模数据集、高级统计模型与机器学习算法，交易员与金融机构可开展市场行为分析、价格走势预测以及交易策略优化工作。本文探讨数据科学在交易领域的作用，重点关注分析技术、预测建模与算法决策相关内容。本研究阐明了数据驱动方法如何提升金融市场的运行效率、降低风险并提高盈利能力。