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

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.

Keywords:

• EWMA control chart
• index track
• cointegration
• optimization

Acknowledgments

The authors would like to thank CNPq (grants: 473033/2012-7, 309899/2015-0, and 430192/2016-9) and CAPES, two Brazilian governmental agencies, for supporting the research on which this work was based. Additional thanks are due to the anonymous referees for their valuable comments which greatly improved the quality of the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.