Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach

Abstract

Wavelet coherence of time series provide valuable information about dynamic correlation and its impact on time scales. Here we analyze the wavelet coherence of FTSE100 and S&P 500 with selected Asian markets of S&P/ASX 200 (Australia), S&P/ASX200 A-REIT (Australia), BIST (Turkey), HIS (Hong Kong), IDX (Indonesia), KLSE (Malaysia), KOSPI (Korea), N225 (Japan), RTS (Russia), Shenzhen (China), 0050.TW (Taiwan). Wavelet coherence results revealed interconnected relationships between stock markets and how these relationships vary in the time–frequency space. We conclude that developed economy stock markets have strong influences over Asian stock markets, although market dependencies vary by country and change over time. We also suggested that because co-movements shift over time, short term and middle term diversification could be more beneficial taking into account the degree of interrelations. From investors point of view, these relationships provides beneficial information, especially for portfolio diversification and risk elimination.

Estimating stock closing indices using a GA-weighted condensed polynomial neural network

“…Huang et al proposed a non linear manifold learning technique for early warnings in financial markets (Huang et al 2017). A wavelet-based approach for co-movement analysis of Asian stock markets against the FTSE 100 and S&P 500 was proposed in (Yilmaz and Unal 2016). A multi-criteria decision-based approach for financial risk analysis was offered in (Kou et al 2014), where the authors evaluated six popular clustering algorithms and eleven cluster validity indices over three real-world financial data sets.…”