PALC: Multi-Factor Rotation Recommended For U.S. Portfolio Allocation

Summary

• Individual factors are proven to create alpha over market long periods or market cycles, but not consistently over short periods.
• Rotation among multiple factors can improve performance relative to single-factor investments.
• PALC is a new ETF that effectively uses multi-factor rotation.

Liudmila Chernetska/iStock via Getty Images

I recommend that we include the PALC (Pacer Lunt Large Cap Multi-Factor Alternator ETF) in our US allocations.

The discussion below explains the reasons for the recommendation.

DISCUSSION:

PALC (prospectus) is a factor rotation strategy ETF. (ETF webpage)

• Rotation means it selects among several “factors” periodically to hold the ones with the best recent performance, based on the tendency of performance momentum to have short-term persistence.
• A “factor” is an attribute of a stock that has been demonstrated through rigorous academic study to outperform a market-cap weighted index (like the S&P 500) over long periods and market cycles.
  • However, no factor outperforms a market-cap weighted index during all market cycle stages
• The factors that have been proven are:
  • Quality
  • Value
  • Low Volatility
  • Momentum
  • Low Size
• Lunt Capital Management developed a methodology to rotate large-cap stocks among the Quality, Value, Low Volatility and Momentum factors on a monthly basis that has been shown to outperform the S&P 500.
  • PALC ETF tracks that methodology
• The methodology works with the four factors and their opposite, which I am calling “anti-factors” (e.g., High Quality and Low Quality; High Value and Low Value and so on) giving the method a choice between 8 (4 x 2) groups of stocks within the S&P 500.
  • Each month it selects the 2 of 8 choices that have the best trailing risk-adjusted momentum (a proprietary rules-based measurement) and weights the factors equally with 100 stocks in each factor (or “anti-factor”)
  • Each factor consists of the top 100 stocks in the S&P 500 for the factor, and the anti-factor consists of the bottom 100 stocks for the factor
  • The prospectus does not specify, but it appears the individual stocks are market-cap weighted within their factor or anti-factor
  • The ETF has a 60 basis point expense ratio and as of 10/20/21 has total assets of $121.8 million with approximately 1 year of operations (but the published index goes back through 1996)

Standard and Poor’s in 2010 wrote a paper about rotation between High Quality and Low Quality as a strategy:

https://www.spglobal.com/spdji/en/documents/research/qualityrankings.pdf

They said:

The quality premium... is positive in down markets ... conversely, in up markets, the quality premium turns negative.

• During periods of high volatility, widening credit spread, and steepening yield curve, the quality premium tends to be positive.
• Conversely, in periods of declining risk, narrowing credit spreads, and flattening yield curves, the quality premium tends to be negative.
• In this paper, we suggest viewing quality in the same light as style, size, and sector exposures or, in other words, as subject to rotations in various market environments.

A few years ago, I plotted the S&P 500 High Quality Index (.SPXQUP) versus the S&P 500 Bottom Quintile Quality Index (.SPXQLUP) over a long period and found that each outperformed the S&P 500 if the period of observation included both Bull and Bear markets, but each underperformed the S&P 500 at times. As the Standard and Poor’s paper said, High Quality did well in declining markets and Low Quality did well in rising markets.

The same sort of rotation is found with other factors, such as High Value and Low Value; High Volatility and Low Volatility; High Momentum and Low Momentum; Large Size and Low Size.

Lunt Capital Management (of Holladay, Utah) developed a factor rotation strategy and index around the idea, which is calculated, maintained and published by Standard and Poor’s. Bottom line, the large-cap multi-factor rotation index outperformed the S&P 500 over time.

Here is the longest data for the strategy versus the S&P 500, showing the result of $1,000 invested in each from the beginning of 1996 through mid-October 2021. The rotation index total return is in blue and the S&P 500 total return is in orange. Note that each is calculated without tax effect. The difference in performance in a regular taxable account is not identified in the chart.

The rotation strategy is not intended to prevent large drawdowns, as a risk-on/risk-off rotation strategy would do, but it is meant to participate in the most favored factors at various times throughout a market cycle.

Here is an index comparison from the beginning of the internet era through the DotCom Bear market. The rotation index went down in the Bear market, but not by as much, and outperformed over the period – mostly by its better performance during the Bear market.

Here is a comparison from the peak of the US stock market in 2007 through the Great Financial Crisis of 2008 and subsequent recovery period. The rotation index did not go down quite as much (but still a lot), recovered sooner and outperformed over the full period.

Here it is from 2016 through the current period, considering the tax law changes and the rapid COVID Bear and recovery. The rotation index didn’t manage less damage during the COVID Bear, but it was ahead before COVID and outperformed since the COVID Bear.

Fortunately, there is now an ETF that tracks that multi-factor index (symbol: PALC). It has only been operating since October 2020. It is a small fund (about $122 million) with a short operating history but tracks a proven index with a proven methodology. This is a chart of the rotation index versus SPY, representing the S&P 500.

You can see from this chart of the same period that the index tracking is good.

Here are some graphics that may help illustrate the rotation strategy:

It looks at 4 traditional factors and 4 mirror image non-traditional factors, which I am calling “anti-factors”, and selects stocks for those factors and anti-factors within the S&P 500. Each of the 4 traditional factors includes the top 100 stocks in the S&P 500 for that factor and each of the 4 anti-factors include the bottom 100 stocks of the S&P 500.

Source: https://www.paceretfs.com/products/palc

The method has 8 choices each month from which to choose 2 to reconstitute the portfolio equally.

Source: https://www.paceretfs.com/products/palc

This chart shows which factors and “anti-factors” did better than and worse than the S&P 500 on an annual basis over the past 10 years. Their performance is inconsistent, but the index methodology shows that rotating among them has produced consistent outperformance.

This table shows which 2 factors or anti-factors were used by the ETF for each month since its inception:

Source: https://www.paceretfs.com/products/palc