Kijeong Park

Dynamic Higher-Order Relations and Event-Driven Temporal Modeling for Stock Price Forecasting

In stock price forecasting, modeling the probabilistic dependence between stock prices within a time-series framework has remained a persistent and highly challenging area of research. We propose a novel model to explain the extreme co-movement in multivariate data with time-series dependencies. Our