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A Framework for Evaluating Momentum Funds (Part 2)

We think that funds that account for risk, leave constraints aside, and account for momentum’s tendency to crash every so often are best-of-breed.

Ben Johnson 24 September, 2020 | 10:20
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In part 1, we looked at the selection universe and selection criteria when evaluating momentum funds. In this part, we will discuss the other aspects.

Weighting Criteria

Momentum ETFs take different approaches to sizing their positions. Most consider the strength of stocks’ momentum in assigning weights, but there are other criteria at play. Most of these funds anchor stocks’ weightings to their market cap, adding or subtracting from their allocation based on how they rank on the relevant momentum measures. Examples include iShares Edge MSCI USA Momentum Factor ETF (MTUM, listed in the U.S.)and Invesco S&P 500 Momentum ETF (SPMO, listed in the U.S.). Other funds take a more aggressive approach. For example, Principal Sustainable Momentum ETF (PMOM, listed in the U.S.)and Alpha Architect U.S. Quantitative Momentum ETF (QMOM, listed in the U.S.)both assign equal weights to those stocks with the strongest momentum characteristics.

There are trade-offs involved. Anchoring to stocks’ market caps may dilute these funds’ factor exposures, but it will also reduce their tracking error relative to their selection universe. Untethering from market-cap weights will likely give these funds a smaller-cap orientation and higher tracking error, resulting in a wilder ride.

Constraints

Investors must also consider other constraints that momentum ETFs put in place. For example, single-stock caps promote diversification. Some funds have sector- and size-related constraints. Fidelity Momentum Factor ETF (FDMO, listed in the U.S.)is both sector- and size-neutral relative to its selection universe. That is, it doesn’t make any bets on the performance of one sector versus another or small caps versus large caps. Morningstar research shows that such constraints may have more merit for some factors that demon­strate persistent industry tilts (such as value) than they do in the context of a momentum portfolio, where industry exposures tend to shift.1 Momentum investors are probably best served by leaving their sector exposures unconstrained.

Maintenance

Momentum is a fast-moving factor. The result is high turnover. The level of turnover of the academic momentum factor would be too costly for real-world application. Momentum funds must strike a balance between maintaining exposure to momentum and the associated costs. With the exception of PMOM, momentum ETFs investing in U.S. stocks rebalance at least twice annually. Actively managed Vanguard U.S. Momentum Factor ETF (VFMO, listed in the U.S.)decides whether or not to rebalance its portfolio every day.

Most of these funds rebalance like clockwork. Two of them have a feature that may have them rebal­ance off-schedule. Both MTUM and PMOM have features that will result in ad hoc rebalancing in response to extreme market volatility. This feature acts as an airbag of sorts, protecting investors from momentum crashes. This is a useful safety feature for a strategy that has a history of slamming into a wall in volatile markets.2

Conclusion

Momentum is tough to harness. Most funds that try fall short. Real-world frictions prevent them from delivering academic momentum in its raw form. Their different approaches to trying to translate academic momentum to practice have yielded mixed results, as measured by both their loadings on the momentum factor as well as their performance versus relevant benchmarks.

Investors should scrutinize these funds’ processes and understand their selection universe and how they select stocks from it, how those stocks are weighted, whether there are any constraints in place, and what the ongoing maintenance schedule looks like. We think that funds that account for risk, leave constraints aside, and account for momentum’s tendency to crash every so often are best-of-breed.

1 Bryan, A., & McCullough, A. 2017. “The Impact of Industry Tilts on Factor Performance.” https://www.morningstar.com/content/dam/marketing/shared/pdfs/Research/The_Impact_of_Industry_Tilts_on_Factor_Performance.pdf

2 Daniel, K., & Moskowitz, T.J. 2016. “Momentum Crashes.” J. Financial Economics, Vol. 122, No. 2, P. 221.

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About Author

Ben Johnson  Ben Johnson, CFA is the Director of Passive Fund Research with Morningstar.

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