Portfolio optimization based on empirical mode decomposition

Li Yang, Longfeng Zhao and Chao Wang

Physica A: Statistical Mechanics and its Applications, 2019, vol. 531, issue C

Abstract: 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.

Keywords: Stock market; Correlation-based network; Empirical mode decomposition; Portfolio optimization (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119309975

DOI: 10.1016/j.physa.2019.121813

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