Application of Data Science in Investment Decision and Its Influence on Market Forecast

Under the background of rapid development of data and information, financial investment decision-making is facing unprecedented challenges and opportunities. Traditional investment decision-making methods have obvious limitations in dealing with massive data and capturing market changes, while the rise of data science provides a new perspective and tool for investment decision-making. The purpose of this study is to explore the specific application of data science in investment decision-making and analyze its improvement and promotion of market forecasting ability. This article discusses the performance of data science forecasting model in market forecasting by combining theoretical analysis with empirical research. By selecting the historical data of the stock market as a sample, the data science model is applied to forecast, and the forecasting accuracy, yield and risk index are tested. The research results show that data science shows significant advantages in investment decision-making. Its powerful data processing ability and forecasting accuracy not only improve the accuracy and timeliness of market forecasting, but also provide investors with more scientific and accurate investment decision support.