Business cycles (BCs) have always attracted considerable attention by policymakers, practitioners & politicians for monitoring current economic conditions & predicting future trends. Recent works present mixed evidence about BC co-movement in the EU & globally depending on the period, data frequency & methodology employed. A flurry of interest in econometric modelling based on spectral methods is observed mostly during the last decade. Until recently multiscale spectral analysis (MSA) represented an important research area only in engineering & natural sciences, wherein the utilization of timescales in the analysis of different modes of behavior isvery common. The use of MSA in economic sciences is in its infancy and many properties are still unexplored. In economics the focus is attributed to long-run equilibrium relationships derived after disaggregating at different time horizons. Via MSA, the low-frequency component of BCs that captures the true dynamics is identified & the high-frequency fluctuations that distort the economic systems are extracted.In this multidisciplinary project advanced spectral techniques that allow for simultaneous analysis in the time & frequency domain are utilized to detect the latent complex dynamics of global markets & particularly of the Eurozone. The study intends to quantify domestic/international interdependencies & analyze BC synchronicity & convergence in the Euro area. Moreover, it investigates macroeconomic & financial causal linkages, reveals new market stylized facts & develops new forecasting models. Integration proceeded in the Eurozone due to the introduction of Euro, until the financial crisis of 2007-2010. The EU debt crisis serves as a catalyst towards therevision of institutional regulations for monetary & fiscal consolidation. Project results are bound to provide new insights for policy making & crisis management in the Euro area, as well as influence the greater predictability of EU markets.