This study incorporates economic and financial cycles into asset allocation to enhance portfolio efficiency. Utilizing wavelet decomposition and principal component analysis, we construct variables that represent economic and financial cycles with broad representativeness. We introduce the WISE Clock, a dual-driven investment strategy that expands upon the traditional Merrill Lynch Investment Clock by incorporating financial cycles. Employing machine learning techniques and cyclical information, we forecast asset returns for the U.S. and Chinese markets, integrating these predictions into a Black-Litterman framework. Backtesting results confirm that this approach significantly surpasses traditional models, enhancing portfolio risk-return performance.