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Improving Portfolio Liquidity with Cash-Value-at-Risk for Covariance Estimations in Quantitative Trading

Author

Listed:
  • Tuan Tran

    (EPHE - École Pratique des Hautes Études - PSL - Université Paris Sciences et Lettres)

  • Nhat Nguyen

Abstract

Understanding characteristics of covariance matrix is an important research topic. In quantitative trading, portfolio liquidity is a hidden dimension and important as others such as portfolio volatility. In this paper, we propose a liquidity impact measure to improve the portfolio liquidity and also a novel Cash Value at Risk to evaluate the liquidity risk from portfolio cash perspective. Experimental results on various scenarios show that our approach improve a portfolio turnover significantly and also better than others on Cash Value at Risk in almost all cases. An interesting finding is that linear shrinkage covariance estimations not only improve the covariance structure but also resolve a large partial of liquidity.

Suggested Citation

  • Tuan Tran & Nhat Nguyen, 2022. "Improving Portfolio Liquidity with Cash-Value-at-Risk for Covariance Estimations in Quantitative Trading," Working Papers hal-03647881, HAL.
    • Handle: RePEc:hal:wpaper:hal-03647881
    Note: View the original document on HAL open archive server: https://hal.science/hal-03647881v1
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    References listed on IDEAS

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    Keywords

    covariance matrix; shrinkage estimation; portfolio liquidity;
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