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Investigating the use of statistical process control charts for index tracking portfolios

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  • Leonardo Riegel Sant'Anna
  • Tiago Pascoal Filomena
  • João Frois Caldeira
  • Denis Borenstein

Abstract

In this article, our goal is to introduce a statistical process control charts approach (SPC) to monitor the rebalancing process of index tracking (IT) portfolios. SPC methods derive from statistics and engineering as tools to control production process. We use exponentially weighted moving average (EWMA) control charts to monitor IT portfolios based on two combined charts: portfolios’ tracking error performance and portfolios’ volatility. As a result, we endogenously control the rebalancing process of the portfolios based on both their returns and their risk conditions over time. Computational tests are performed to evaluate the developed approach in comparison with the traditional fixed period strategy, using data from Brazilian and U.S. market from 2005 to 2014. Cointegration and optimization methods are applied to form the portfolios. The results show that SPC approach can be a viable alternative to portfolio rebalancing.

Suggested Citation

  • Leonardo Riegel Sant'Anna & Tiago Pascoal Filomena & João Frois Caldeira & Denis Borenstein, 2019. "Investigating the use of statistical process control charts for index tracking portfolios," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1622-1638, October.
    • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:10:p:1622-1638
    DOI: 10.1080/01605682.2018.1495887
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    Cited by:

    1. Julio Cezar Soares Silva & Adiel Teixeira de Almeida Filho, 2023. "A systematic literature review on solution approaches for the index tracking problem in the last decade," Papers 2306.01660, arXiv.org, revised Jun 2023.

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