Research on the Construction of a Financial Early Warning System Based on Binary Time Series Algorithm

Questions of financial risk management are the first to be tackled in this paper where we also review theoretical and practical methods for creating a financial early warning system that is binary time series based. It tells initial review of the recent works which are connected both to financial early warning systems and to time series analysis, with special attention to domestic and international levels, and shows how these methods are insufficent in terms of timeliness and accuracy. In addressing this, the following hardwires the case of processing financial data into dynamic and preprocessing by employing binary time series algorithms. A largely simple system scheme is envisioned with the modules being data collection, processing, algorithm computation, and the last early warning visualization. The comparative experiments conclude that most of the model's advantages are in prediction accuracy, response speed, and system stability. The research findings supply businesses with new technical instruments to manage risk and this by so doing widens the scope for relevant theoretical and practical applications also.