Portfolio optimization based on empirical mode decomposition

The investigation about the cross-correlation among financial assets has drawn broad attention recently. Due to the nonlinear and non-stationary identities of the financial time series, e.g., stock return time series, the cross-correlation for different level of fluctuations are quite important for both academia and financial practitioners. Here we use the empirical mode decomposition (EMD) method to analyze the cross-correlation structure among different level of fluctuations for financial assets. The correlation-based networks are then employed to determine the clustering property of stock market. We then propose several portfolio optimization strategies based on the EMD correlation-based networks. Using the topological information of the networks, we can construct some portfolios with high return and low risk. Under two portfolio evaluation frameworks, we prove that these portfolios have consistently good performance. •The EMD can discriminate fluctuation levels of the stock market..•The topological structure of the EMD networks signalized the market instability.•The EMD correlation-based network can improve the performance of the portfolio.