Investing Made Easy: How to Analyze ETF Performance
By Max Grinold
Exchange-traded funds (ETFs) serve as the cornerstone of a diversified, long-term investment portfolio. Instead of buying and selling individual securities on your own, you can rely on the expertise of an experienced fund manager. ETFs are essentially baskets of securities, ranging from tens to hundreds, that trade on an exchange, aiming to track or outperform a market index. They can represent various industries, asset classes, geographies, commodities, and currencies (even Bitcoin). With a wide array of ETFs available on the market, how do you choose the right one for your portfolio?
Evaluation Starts with the Index
The first step in analyzing the performance of an ETF is to understand which index the fund is tracking. This information is typically found in the fund’s fact sheet or prospectus, which is usually available on the manager’s website. These documents outline the fund’s strategy, returns, holdings, and allocation, and provide insights into the ETF’s performance and objectives. For instance, some ETFs track broad market indices like the S&P 500, while others may focus on specific industries, geographical regions, or commodities. Understanding the index can help you evaluate how well the ETF aligns with your investment goals and individual risk tolerance. For example, a tech-focused ETF might track the NASDAQ-100 index while a High Yield Bond ETF might track the ICE BofA US High Yield Index, both of which have much different volatility and return profiles.
Volatility and Correlation Metrics
R-Squared: the r-squared on an ETF represents how much of the movement in the fund can be attributed to the benchmark index. An r-squared value ranges on a scale of 0 to 100, with 100 meaning that 100% of the movement of the fund is correlated with movements in the benchmark. This means that an ETF with an R-squared of 100 matches the performance of its benchmark exactly.
Beta: the beta of an ETF represents how volatile the fund is with respect to its benchmark. A beta of 1.0 means that the ETF is exactly as volatile as its benchmark. A beta above 1.0 means the fund is more volatile than the benchmark, and below means it is less sensitive to benchmark movements. Beta is a double-edged sword. While a beta of 1.3 means that the fund might outperform a benchmark when performance is strong, it also means that it performs worse than a benchmark when the performance is weak.
Standard Deviation: the standard deviation of an ETF measures the variation around the average return of an ETF, which is often tailored to 1 year, 3 year, or 5 year performance. Using the standalone standard deviation of an ETF is often not a great indicator, as you also want to compare it to the standard deviation of the index as well as similar funds. If an ETF has a lower standard deviation than its benchmark, it means that the fund is providing less volatile returns than the index.
Sharpe Ratio: the sharpe ratio of an ETF is a method of evaluating the risk-adjusted return of an ETF. This is derived through taking the average return of an ETF over a specified period, subtracting the risk-free rate of return, and then dividing that excess return by the standard deviation of the ETF. A higher sharpe ratio means that there is a higher unit of return for each additional unit of risk. Through analyzing the different sharpe ratios of various funds, you can optimize your risk adjusted returns.
A Beginner’s Toolbox
While the above metrics can not be used standalone to identify the ‘the best’ ETF to add to a portfolio, they can be used in tandem with each other to compare fund managers within asset classes and industries to pinpoint successful fund managers with strong risk-adjusted returns. With additional metrics such as alpha, treynor ratios, tracking error, and more, there is an entire universe of evaluating outstanding managers.
Sources:
https://www.investopedia.com/terms/e/etf.asp
https://www.investopedia.com/ask/answers/012915/whats-relationship-between-r-squared-and-beta.asp
