Quantile Tracking Errors (QuTE)

31 Pages Posted: 22 Feb 2020

See all articles by Mike Aguilar

Mike Aguilar

University of North Carolina (UNC) at Chapel Hill - Department of Economics

Ruyang Chengan

Independent

Anessa Custovic

Cardinal Retirement Planning Inc.

Date Written: January 24, 2020

Abstract

The tracking error is a ubiquitous tool among active and passive portfolio managers, used widely for fund selection, risk management, and manager compensation. In this paper we show that traditional measures of tracking error are incapable of detecting variations in higher order moments (e.g. skewness and kurtosis). As a solution, we introduce a new class of Quantile Tracking Errors (QuTE), which measures devations in the quantile of return distributions between a tracking portfolio and its benchmark. Through an extensive simulation study we show that QuTE can detect variations in higher order moments. We also offer guidance on the granularity of the quantile grid and weighting schemes for the relative importance of various quantiles. A case study illustrates the benefits of QuTE during the Dot Com Bubble and the Great Recession.

Keywords: tracking error, index tracking

JEL Classification: G11

Suggested Citation

Aguilar, Mike and Chengan, Ruyang and Custovic, Anessa, Quantile Tracking Errors (QuTE) (January 24, 2020). Available at SSRN: https://ssrn.com/abstract=3525171 or http://dx.doi.org/10.2139/ssrn.3525171

Mike Aguilar (Contact Author)

University of North Carolina (UNC) at Chapel Hill - Department of Economics ( email )

Chapel Hill, NC 27599
United States

HOME PAGE: http://mikeaguilar.web.unc.edu

Ruyang Chengan

Independent ( email )

Anessa Custovic

Cardinal Retirement Planning Inc. ( email )

2530 Meridian Pkway #100
Durham, NC 27713
United States

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