
doi: 10.1002/for.2648
handle: 10182/18218
AbstractThis study introduces volatility impulse response functions (VIRF) for dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) models. In addition, the implications with respect to network analysis—using the connectedness approach of Diebold and Y lmaz (Journal of Econometrics, 2014, 182(1), 119–134)—is discussed. The main advantages of this framework are (i) that the time‐varying dynamics do not underlie a rolling‐window approach and (ii) that it allows us to test whether the propagation mechanism is time varying or not. An empirical analysis on the volatility transmission mechanism across foreign exchange rate returns is illustrated. The results indicate that the Swiss franc and the euro are net transmitters of shocks, whereas the British pound and the Japanese yen are net volatility receivers of shocks. Finally, the findings suggest a high degree of comovement across European currencies, which has important portfolio and risk management implications.
dynamic connectedness, 330, volatility spillovers, volatility impulse response functions, ANZSRC::3802 Econometrics, ANZSRC::4905 Statistics, exchange rates, variance decomposition
dynamic connectedness, 330, volatility spillovers, volatility impulse response functions, ANZSRC::3802 Econometrics, ANZSRC::4905 Statistics, exchange rates, variance decomposition
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