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Measuring the performance of Exchange-traded funds


Measuring the performance of Exchange-traded funds

Xiaying, Zhang (2018) Measuring the performance of Exchange-traded funds. Masters thesis, Concordia University.

Text (application/pdf)
Xiaying_MSc_F2018.pdf - Accepted Version


The purpose of this thesis is to measure the performance of exchange-traded funds (ETFs) from the year 2012 to 2016. I include 312 ETFs from developed markets and 61 ETFs from emerging markets in the sample. I compare the performance of the ETFs with their corresponding benchmark indices and compare the performance of the developed market ETFs with the emerging market ETFs and I find that all of the ETFs underperform their underlying benchmark indices. I use the tracking error of the ETF as a measure of its performance and I define the tracking error as the difference between the return of the ETF and the return of its underlying benchmark index and I expect the tracking error to be significant. Using the absolute value of the difference between the return on ETFs and their underlying benchmark indices and the standard errors of regression models which measure the relationship between those returns as the estimate of tracking error, the results indicate that the tracking error is significantly different from zero. However there is no evidence that ETFs in developed markets have better performance than ETFs in emerging markets. I use the 3-month U.S Treasury bill rate as an estimate of the risk-free rate and determine the risk-adjusted performance of both ETFs and their underlying benchmark indices. Finally, I analyze the impact of different variables on the ETF’s tracking error using a regression analysis, the results indicate that both daily volatility and dividend yield exert significant influence on tracking errors of ETFs in both developed markets and emerging markets.

Divisions:Concordia University > John Molson School of Business > Finance
Item Type:Thesis (Masters)
Authors:Xiaying, Zhang
Institution:Concordia University
Degree Name:M. Sc.
Program:Administration (Finance option)
Date:13 April 2018
Thesis Supervisor(s):Shanker, Latha
ID Code:983758
Deposited On:11 Jun 2018 03:51
Last Modified:11 Jun 2018 03:51
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