Marina Dolfin, George Kapetanios, Leone Leonida, Jose De Leon Miranda
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Investor behavior and multiscale cross-correlations: Unveiling regime shifts in global financial markets
We propose an algorithm to capture emergent patterns in the
cross-correlations of financial markets, highlighting regime changes on a
global scale. In our approach, financial markets are viewed as complex adaptive
systems, and multiscale properties and cross-correlations are considered,
particularly during stress conditions such as the COVID-19 pandemic, the
invasion of Ukraine by Russia in 2022, and Brexit. We investigate whether
significant disruptions reflect an imbalance in investment horizons among
investors, and we propose a measure based on this imbalance to depict the
impact on global financial markets. The detrended cross-correlation cost
(DCCC), which is derived from detrended cross-correlation analysis, uses
cross-correlations at different timescales to capture variations in investment
horizons amid financial uncertainties. Our algorithm, which combines DCCC
analysis and the minimum-spanning-tree filtering approach, tracks system
interconnectedness and investor imbalances. We tested the DCCC indicator using
daily price series of G7, Russian, and Chinese markets over the past decade and
found that it increases sharply during ``crash'' periods compared to ``business
as usual'' periods. Our empirical results confirm that short-term investment
horizons dominate during financial instabilities; this validates our hypothesis
and indicates that the DCCC can serve as a leading indicator of shifts in
financial-market regimes.