Index tracking performance in times of volatility or lack thereof

Abstract

This dissertation sets out to explore whether the tracking ability of exchange-traded funds (ETFs) is compromised during periods of high market volatility. Light is shed on the factors that influence tracking error which is an ETF specific metric. Design/methodology/approach - 98,616 observations, derived from 28 ETFs and their corresponding benchmarks spanning a seven-year period are analysed through the application of methodologies suggested by Pope and Yadav (1994), amongst others. The funds were classed according to categories prescribed by Morningstar's Style Box. ETFs that were categorized under Morningstar's definition of Large/Value, Medium/Blend and Small/Growth were given prominence. Findings - It was found that tracking errors obtained were more pronounced during 2008 and 2009 when compared with 2012 and 2013. It was also found that those ETFs categorized by Morningstar as being 'Small Cap and Growth exhibited the greatest tracking errors during times of high market volatility. Practical implications - This dissertation features the relationship between the actual funds and their underlying or fundamentals. This relationship should aid in discerning which class of ETF are inclined to deliver the most favourable returns to investors in times of high market volatility or lack thereof. Originality/value - This dissertation contributes to the ongoing literature as it splits the ETFs into the classes pre-defined by Morningstar, which, according to the author's knowledge, such approach has not been academically attempted as yet. Three of the nine Morningstar Style Box categories have been given prominence as they were deemed to be the most relevant to the purposes of this dissertation. Daily prices could have a 'noise' effect on the interpretations derived from the statistics. Not all the benchmark prices are readily available, thus, they were obtained through privately owned software, that is, the Bloomberg Information System.