Nonlinear dynamics and advanced machine learning for inspecting temporal pattern and predictive analytics of financial and market variables

Abstract

newline Global financial markets manifested through stock indexes reflect true characteristics newlineof economic health, financial conditions, household finance, political conditions, etc. of newlinenations. It is extremely important to comprehend the temporal dynamics of stock markets to newlineintrospect the state of financial health to strategize the augmentation of economic growth, GDP, newlineetc. Stock markets have been observed to be highly sensitive to external turbulence, geo- newlinepolitical uncertainty, disasters, etc. Therefore, the temporal dynamics of said assets often newlineexhibit a high degree of volatility and chaotic traits. The presence of significant nonlinearity, newlinenonparametric, and non-stationary has been found as well. Thus, conventional econometric newlinemodels may not capture the inherent pattern of said variables correctly always.