Commodity price risk supervision in the context of "data element×"
With the advent of the era of digital economy,the commodity market faces risks such as significant price fluctuations and supply chain uncertainties.To examine the commodity price risk supervision challenges in the context of"data element×",this paper analyzes the pivotal role and policy measures concerning commodities,the influential force of"data element×"on the commodity market,the challenges and prospects related to commodity trading risks,and the pressing need for commodity price risk supervision.The study reveals that emerging technologies such as data analysis and artificial intelligence are reshaping China's commodity market entirely.Commodities encounter four central issues:data collection,requirements for price data labeling,construction of knowledge maps,and dynamic risk alerts.Research suggests leveraging deep learning for gathering multi-source heterogeneous data,employing knowledge element indexing and integration technology to establish data labels,utilizing data mining for knowledge map construction,and implementing hierarchical calibration to establish a dynamic risk alert system.These measures aim to enhance the risk response capabilities of investors and decision-makers in commodity markets.
NETL
NSTL
万方数据
