Analyzing diversification opportunities among top-performing ETFs: a multi-wavelet and MGARCH-DCC approach

Purpose This paper aims to examine portfolio diversification opportunities exclusively within Exchange-Traded Funds (ETFs). The goal is to determine potential benefits for investors by analyzing the relationships among a selected group of top-performing ETFs. Design/methodology/approach Focusing on 19 ETFs from May 15, 2019, to May 1, 2024, the study employed the Multivariate Generalized Autoregressive Conditional Heteroskedasticity-Dynamic Conditional Correlation (MGARCH-DCC) and Wavelet Local Multiple Wavelet (WLMC) analysis. The identification of dynamic and time-frequency correlations among the ETFs helps us understand their potential for diversification. Findings The results showed very high correlations and market integration at both low and high frequencies, indicating limited opportunities for diversification within the larger set of ETFs. As a result, we identified a smaller subset with lower correlations. The WLMC analysis revealed short-term diversification opportunities for investment horizons of up to 32–64 days. Our results particularly highlighted the interplay between Amundi US Treasury Bond Long, Amundi MSCI Emerging Markets, iShares Physical Gold and Xtrackers MSCI World Consumer Staples (XDWS). Social implications Integrating thematic ETFs that align with ethical considerations and personal convictions empowers investors to pursue financial goals while staying true to their values. This holistic approach supports responsible investment practices and encourages a more socially conscious and sustainable investment landscape. Originality/value This research introduces a novel Core-Satellite ETF portfolio strategy calibrated for short-term investment horizons. We used the iShares Physical Gold ETF to provide stability for the core. For the satellites, thematic ETFs were picked, specifically, Amundi MSCI Emerging Markets, XDWS and Amundi US Treasury Bond Long ETF. Unlike the Wavelet coherence, limited to pairwise analyses, the novelty lies in using WLMC to capture across multiple ETFs simultaneously, enabling better investment decisions. Integrating MGARCH-DCC with WLMC offers a methodological synergy with novel comprehensiveness that addresses ETF market dynamics for better tactical diversification. This approach outperforms benchmarks, namely the equal-weighted and minimum-variance portfolios.