How to measure ETF and mutual-fund risk

“Risk has long been a hot topic in the funds industry,” said Brian Bridger, senior vice president, analytics and data, at Toronto-based Fundata. “Each of these metrics has its pros and cons.” The more types of metrics the company can provide, he added, the more complete the picture of a fund’s risk becomes.

To illustrate how ETFs have performed over the past turbulent few years, Fundata Investment Executive has provided risk measurement data for the three years ended 31 July. (Risk data can be calculated for other time periods as well, Bridger noted.)

Standard deviation — which measures how much a fund or ETF’s returns differ from its mean returns — has received the blessing of securities regulators as a core method for calculating risk ratings. The ratings are based on the last 10 years of performance history. Newer funds use a combined history that also includes a proxy such as a market benchmark or an older series of the same or similar funds.

The five-level risk ratings range from low to high. They must be published in the disclosure documents ETF Facts and Fund Facts. For example, a broadly diversified Canadian equity ETF may be classified as “medium” risk.

The standard deviation is useful for comparing between asset classes, Bridger said. For example: “You can compare the volatility of a stock fund to a bond fund and get a feel for the risk involved.”

As Fundata’s calculations show, investing in a narrow segment of the market — and leverage beyond it — is a recipe for exceptional volatility. It’s the same with the BetaPro Marijuana Companies 2x Daily Bull ETF.

The three-year standard deviation of the ETF’s returns was a whopping 144%. In comparison, the standard deviation of a broad Canadian equity ETF is more than eight times lower.

Sponsored by Toronto-based Horizons ETFs Management (Canada) Inc., BetaPro products employ leverage and inverse leverage and dominate the list of the most volatile ETFs. As Horizons’ prospectus warns, they are speculative and may only be suitable for active traders who can take the risk of losing their entire investment.

Excluding BetaPro, the top three-year standard deviations were 56% for the Blockchain Technologies ETF, sponsored by Oakville, Ontario-based Harvest Portfolios Group Inc., and 52% for the Horizons Marijuana Life Sciences Index ETF.

A limitation of standard deviation is that it cannot accurately predict potential future losses and may actually underestimate risk. “The tail risks of funds and investments are typically much larger than the standard deviation would indicate,” Bridger said, referring to rare but extreme events such as market crashes or natural disasters.

Another disadvantage of the standard deviation is that it is not expressed in dollars.
The average investor, Bridger said, may not fully understand how standard deviation relates to actual dollar losses.

Maximum drawdown is a risk metric that, although expressed as a percentage, is more easily converted to dollar amounts. It measures the percentage loss from a fund’s high to its low over a period of time.

“An investor can see what has happened in the past and what could possibly happen in the future,” Bridger said. But that measure will be misleading, he added, unless the time frame being measured includes a market correction or a bear market.

Aside from leveraged funds and those specializing in marijuana companies, the biggest declines over the past three years have been those of several emerging technology ETFs sponsored by Toronto-based Emerge Canada Inc. The Emerge ARK Fintech Innovation ETF, for example, peaked at 71% -until the downturn.

A measure of risk based on relative performance against a market benchmark is up-down capture. A Down Capture greater than 1 means the fund has underperformed in a falling market. “If a fund has very low down capture, then that’s good,” Bridger said. “That means if the market goes down, they don’t lose as much as the market. You mitigate that risk.”

Use of this metric is appropriate when comparing funds in categories such as Canadian equities where each fund has broadly similar holdings. But in a category as diverse as sector stocks, up-down capture comparisons aren’t that meaningful.

Among the fixed income ETFs, the BMO Long-Term US Treasury Bond Index ETF had the highest value for capturing price losses at 1.7. Like other long-term bond funds, the BMO ETF has suffered large capital losses due to rising interest rates pushing down bond prices.

The Fund’s hitting average is a measure of month-to-month consistency. A one-month return is considered “at-bat”. A beat average greater than 0.500 means the fund has returned above zero for more than half of the monthly performance periods.

The least risky are cash substitutes like the iShares Premium Money Market ETF and the CI High Interest Savings ETF, with perfect hitting averages of 1,000.

At the other extreme were various BetaPro offerings from Horizons. The worst was the 2x leveraged marijuana ETF. With a batting average of just .222, it essentially beat nearly four out of five months.

Bridger said the batting average metric can be useful for evaluating alternative strategy funds with a market-neutral mandate. Ideally, “they don’t have huge monthly returns, but they’re very stable and don’t have a lot of down months, so they have a very high batting average.”

Over the three-year period, average values ​​for these types of ETFs ranged from 0.472 for the Purpose Multi-Strategy Market Neutral Fund to 0.639 for the Picton Mahoney Fortified Market Neutral Alternative Fund. As with any risk metric, results will vary based on the length and date of the measurement period.