Application of Leading Indicator Forecasting Based on Optimal Transmission in Financial Technology

Leading indicators have been widely used to predict the developing orientation of the economy and provide guidance for investors to make judgements. According to the development trend of financial technology, we explore the application of leading indicators from three aspects: optimal transmission, uncertainty visualization, and knowledge graph construction. The optimal transmission theory automatically calculates the cost of matching two time series, which greatly improves the efficiency and accuracy of finding leading indicators. Besides, we propose a visualization method to illustrate the uncertainty of leading indicators, which can extract meaningful information from a wide variety of data and models. Further-more, we propose to build a network of relationships between industries and indicators using knowledge graph. Leading in-dicators and lagging indicators can be effectively discovered through the proposed methods. Experiments verify the feasibility and effectiveness of the proposed optimal transmission theory while the uncertainty visualization model can provide reasonable guidance for investors.