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This paper investigates multiscale interdependence between the stock markets of Germany, Austria, France, and the United Kingdom. Wavelet energy additive decomposition was analyzed to investigate which scales capture the most energy (volatility), whereas a wavelet cross-correlation estimator was used to analyze comovement and lead/lag relationship between stock markets' return dynamics on a scale-by-scale basis. The main findings of the paper are as follows. First, major financial market crises had a significant impact on return volatility of investigated stock markets. Among them, the global financial crisis of 2007-2008 had the greatest and the most durable impact. Second, the lowest scale (associated with stock markets' return dynamics over a 2-4 days horizon) and the second lowest scale (associated with stock markets' return dynamics over 4-8 days horizon) MODWT (maximal overlap discrete wavelet transform) decompositions of stock markets' returns captured the greatest share (together about 70-80%) of indices' returns volatility. Third, comovement between stock market returns is a scale-dependent phenomenon. Fourth, a strong comovement between stock market returns of Germany, France, and the United Kingdom exists at all scales, while the Austrian stock market is less correlated with the three biggest stock markets in Europe. Fifth, the dynamics of stock market returns seems to be well time-synchronized at daily (raw returns) and the lowest scale (scale ) return decomposition as most of the return innovations are transmitted between stock markets intraday. Sixth, at the highest investigated scale (associated with stock markets' return dynamics over a 64-128 days horizon), significant leads and lags between dynamics of stock markets' returns were detected. The time-synchronization of the stock markets' return dynamics for investments of 64 to 128 days horizon is less perfect than for investments of shorter investment horizons.

Interdependence Between Some Major European Stock Markets - A Wavelet Lead/Lag Analysis