Dynamic conditional correlations and connectedness in emerging-market exchange rates§

• Financial integration in international markets has strengthened the financialization of exchange rate markets. • We investigate the dynamics of conditional correlations and connectedness among exchange rates. • We use daily data from 2000 to 2022 and apply DCC-GARCH, SVAR, and connectedness indices. • A shock to the Euro-Pound conditional correlation reduces conditional correlations of emerging currencies. • Connectedness suggests that uncertainty in core economies exacerbates instability in emerging markets. This study investigates the dynamic effects of discretionary shocks on exchange-rate conditional correlations and assesses currency connectedness between developed and emerging economies. Focusing on BRICS + Turkey (BRICS + T) countries and their links to the Euro and the British pound sterling, we apply dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC–GARCH) to estimate time-varying correlations and structural vector autoregression (SVAR) to trace the impacts of shocks on conditional correlations. Connectedness indices are computed to capture directional spillovers across currency pairs. The results reveal strong persistence in exchange-rate co-movements, with contagion-like patterns, especially in response to external perturbations. The Euro–Pound pair plays a dominant role, with a positive shock on their correlation reducing BRICS + T interdependence. The findings highlight the importance of tracking conditional correlations and spillovers for risk management, systemic stability, and policy design in globally integrated markets. By integrating DCC–GARCH, SVAR impulse responses, and connectedness, we offer valuable insights into the transmission mechanisms of financial shocks to increasingly interconnected currency markets.