Time-dependent complexity measurement of causality in international equity markets: A spatial approach

摘要: Abstract A nonlinear temporal complexity approach is proposed in order to properly model the evolution of randomness, self-similarity and information transmission for thirty-four international stock markets, grouped into four major geographical segments: America, Europe, Asia Oceania. The causality between each type time-dependent measures investigated assess state system flows across all geographic segments. empirical results show that vastly transmitted financial markets. Moreover, significant emissions entropy are found America Europe. Informational observed only Europe Asia, Our findings may have important implications portfolio management based on spatial dimension spillovers stochasticity, informational content world These would not emerged by means standard econometric approaches investigation returns.