Possible Application of IdopNetwork in Stock Market
演讲者
时间
2024年11月04日 15:20 至 16:20
地点
A3-2-303
线上
Zoom 230 432 7880
(BIMSA)
摘要
Most existing network reconstruction methods can only infer a whole network from multiple samples and cannot identify the variability between samples. Such as interaction strength, interaction causality, interaction symbol and feedback loop. Although the dynamic model can overcome some of the above limitations, it is limited by the acquisition of high-density dynamic data, which is extremely expensive, unrealistic or not allowed in theory. Dong et al. (2022) propose an information-rich, dynamic, omni-directional, and personalized idopNetwork that can be reconstructed from any dataset, including static data. Due to its own characteristics of the stock market, this talk attempts to apply idopNetowork to the stock market, and intends to build a network structure chart that can analyze the interaction relationship between different stock returns.
演讲者介绍
Shujie Wang is a PHD student at BIMSA and UCAS. Her research interests including digital economy, empirical asset pricing, and data asset pricing.