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Turnover of investment portfolio via covariance matrix of returns

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  • A. V. Kuliga
  • I. N. Shnurnikov

Abstract

An investment portfolio consists of $n$ algorithmic trading strategies, which generate vectors of positions in trading assets. Sign opposite trades (buy/sell) cross each other as strategies are combined in a portfolio. Then portfolio turnover becomes a non linear function of strategies turnover. It rises a problem of effective (quick and precise) portfolio turnover estimation. Kakushadze and Liew (2014) shows how to estimate turnover via covariance matrix of returns. We build a mathematical model for such estimations; prove a theorem which gives a necessary condition for model applicability; suggest new turnover estimations; check numerically the preciseness of turnover estimations for algorithmic strategies on USA equity market.

Suggested Citation

  • A. V. Kuliga & I. N. Shnurnikov, 2024. "Turnover of investment portfolio via covariance matrix of returns," Papers 2412.03305, arXiv.org.
    • Handle: RePEc:arx:papers:2412.03305
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    References listed on IDEAS

    as
    1. Zura Kakushadze & Willie Yu, 2018. "Notes on Fano Ratio and Portfolio Optimization," Journal of Risk & Control, Risk Market Journals, vol. 5(1), pages 1-33.
    2. Zura Kakushadze, 2014. "Can Turnover Go to Zero?," Papers 1406.0044, arXiv.org, revised Oct 2014.
    3. Zura Kakushadze, 2014. "Notes on Alpha Stream Optimization," Papers 1406.1249, arXiv.org, revised Mar 2015.
    4. Zura Kakushadze & Willie Yu, 2017. "Notes on Fano Ratio and Portfolio Optimization," Papers 1711.10640, arXiv.org, revised Apr 2018.
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    7. Zura Kakushadze, 2016. "101 Formulaic Alphas," Papers 1601.00991, arXiv.org, revised Mar 2016.
    8. Zura Kakushadze, 2014. "Combining Alpha Streams with Costs," Papers 1405.4716, arXiv.org, revised Jan 2015.
    9. Zura Kakushadze, 2014. "Factor Models for Alpha Streams," Papers 1406.3396, arXiv.org, revised Oct 2014.
    10. Zura Kakushadze, 2014. "A Spectral Model of Turnover Reduction," Papers 1404.5050, arXiv.org, revised Nov 2015.
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