Performance analysis of ETFs and comparative evaluation by category

Abstract

This study investigates the performance of various Exchange-Traded Funds (ETFs) over a five-year period from the start of 2020 to the end of 2024. It begins with a review of the history of ETFs, how they are created and their various operating mechanisms. It then explores the advantages and risks associated with ETFs and comparing them with other financial products. After this, ETFs are separated into categories according to the nature of their tracking indexes and they are discussed along with their characteristics. The aim of the ETF overview section is to provide a fundamental understanding of ETFs and to organize them into the categories that will be analyzed in the research part. In the research section, a quantitative analysis is first conducted by comparing ETFs within each category followed by a comparison across ETF categories over this five-year period as well as in each year individually. This comparison focuses on key performance metrics, and it includes total returns, expense ratio, standard deviation, Sharpe ratio, beta, CAPM expected returns and alpha. The comparison of ETFs within each category is based on the ten most significant and representative ETFs of each category, while the comparison across ETF categories is done by analyzing the average performances of their ETFs. The aim of this comparison is to evaluate the differences between ETF categories and also to identify their unique characteristics. The findings of the study revealed that Cryptocurrency ETFs achieved the strongest total returns and alpha, while categories which experienced low volatility like Bond ETFs and Currency ETFs underperformed and delivered negative total returns. Additionally, the majority of ETF categories recorded negative Sharpe ratios and alpha values over the selected five-year period. Ultimately, ETF category selection should be aligned with investors goals and risk tolerance as high total return ETF categories usually include high levels of volatility.