报告题目：How does node centrality in a financial network affect asset price prediction
时 间：2025年2月28日（星期五）9:00
地 点：腾讯会议:719-881-205
主 办：数学与统计学院
参加对象：感兴趣的老师和学生
报告摘要：In complex financial networks, systemically important nodes usually play crucial roles. Asset price forecasting is important for describing the evolution of a financial network. Naturally, the question arises as to whether node centrality affects the effectiveness of price forecasting. To explore this, we examine networks composed of major global assets and investigate how node centrality affects price forecasting using a hybrid random forest algorithm. Our findings reveal two counterintuitive phenomena: (i) factors with low centrality usually have better prediction ability, and (ii) nodes with low centrality can be predicted more accurately in direction. These unexpected observations can be explained from the perspective of information theory. Moreover, our research suggests a criterion for factor selection: when predicting an asset price in a complex system, factors with low centrality should be selected rather than only factors with high centrality.
报告人简介：徐玉红，苏州大学研究员，博士生导师，仲英青年学者。师从国际著名金融数学家彭实戈院士。先后在法国西布列塔尼大学(博士后)、新加坡国立大学(研究员)、香港大学、香港理工等学校访问工作。长期从事金融数学和金融工程方面的研究，研究结果在《Mathematical Finance》、《Management Science》、《Quantitative Finance》、《North American Journal of Economics and Finance》等杂志发表。任中国运筹学会金融工程与风险管理分会第三、四届常务理事、中国优选法统筹法与经济数学研究会量化金融与保险分会第一、二届理事、全国工业统计研究会金融科技与大数据分会第一届理事、中国工业与应用数学协会金融工程分会青年组委员、金融数学与数据处理年会程序委员。先后主持国家自然科学基金3项、江苏省自然科学基金2项。