The Application and Accuracy of Big Data in Financial Market Forecasting

Abstract

With the rapid development of information technology, the application of big data in financial markets has become increasingly widespread. Big data technology can process and analyze vast amounts of data to extract valuable information, providing new methods and tools for financial market forecasting. This paper explores the application and accuracy of big data technology in financial market forecasting, focusing on its specific applications in the stock market, bond market, and foreign exchange market. The study finds that big data technology has a significant advantage in enhancing the accuracy of financial market predictions by constructing more accurate forecasting models through the integration of various data sources. However, the paper also highlights challenges in practical applications, such as data quality, algorithm selection and optimization, and high costs. Nevertheless, with the ongoing development and improvement of technology, the application of big data in financial market forecasting remains promising, with the potential to further improve prediction accuracy and reliability, providing strong support for investors and financial institutions.