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Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion

Author

Listed:
  • Kuangxi Su

    (Xinyang Normal University)

  • Yinhong Yao

    (Capital University of Economics and Business)

  • Chengli Zheng

    (Central China Normal University)

  • Wenzhao Xie

    (Changjiang Securities Company Limited)

Abstract

Noise is an important factor affecting portfolio performance, how to construct an effective denoising strategy is becoming increasingly important for investors. In this study, we theoretically explain the impact of noise on portfolio and argue the necessity of denoising. Next, the empirical mode decomposition (EMD) denoising strategy based on the correlation coefficient test criterion is proposed to improve portfolio performance. In detail, EMD is used to decompose the noisy price, then, a series of correlation coefficient tests are performed to determine which intrinsic mode functions (IMFs) are noise. In the empirical analysis, we apply the proposed method to denoise the SSE 50 index’s constituents, and further test the out-of-sample performance under the mean–variance framework. The empirical results show that the proposed denoising method outperforms four common EMD, Ensemble EMD (EEMD) and wavelet denoising methods in return-risk ratio. The proposed method is the optimal denoising strategy, which can help investors improve portfolio performance to the greatest extent.

Suggested Citation

  • Kuangxi Su & Yinhong Yao & Chengli Zheng & Wenzhao Xie, 2024. "Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 391-421, January.
    • Handle: RePEc:kap:compec:v:63:y:2024:i:1:d:10.1007_s10614-022-10345-4
    DOI: 10.1007/s10614-022-10345-4
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    References listed on IDEAS

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