April Factor Commentary
Key Takeaways
- Of the factors we track, momentum and low-volatility showed the best performance over the past month. The small-cap factor, after a strong February, reverted to its trend of recent underperformance in March.
- Our dynamic factor portfolio underperformed the S&P 500 by 0.5% in March. Since the start of 2020, this strategy has outperformed the S&P 500 by 5.2%.
- After the latest rebalance, the dynamic factor portfolio is now overweight value and low-volatility and is underweight quality and growth.
- A basket of the favored stocks from our stock selection model underperformed the S&P 500 by 0.62% in March. Of the five custom factors that make up the stock selection model, only momentum outperformed in March.
- We add a new section this month to provide an update on our market valuation methodology. At the end of March, equities were overvalued compared to investment grade fixed income. Historically, equities have seen muted returns and increased volatility when in the overvalued regime.
Factor Performance Review
Of the six factors we track (growth, quality, low-volatility, momentum, size, and value) in our multi-factor strategy, the best factor over the past month was momentum, earning 2.5% over the S&P 500. Low-volatility also turned in a positive month, outperforming the benchmark by 1.4%. On the other hand, small-caps, which had outperformed by 3.8% during February, underperformed over the past month by 3.9%. The quality factor also performed poorly, losing 1.4%. Performance for each of the six factors over the past month is shown as the gray bars in Fig. 1.
On a trailing 3-month basis, the low-volatility factor has shown the best performance, outperforming the S&P 500 by 5.9%. Looking back further over a 12-month horizon, size still lags the other five factors by a wide margin. Small-cap stocks have underperformed the benchmark by 19.1% on a trailing 12-month basis.
Fig. 1 – Recent Performance of Factors
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
Multi-Factor Portfolio Performance Review
We track a dynamic multi-factor portfolio that applies a tilting mechanism to a standard, static multi-factor portfolio. The dynamic portfolio tilts weight toward the factors with the best recent performance, and away from the factors with the worst recent performance. Fig. 2 shows the cumulative performance of this dynamic multi-factor strategy relative to the S&P 500 since 1997.
Fig. 2 – Dynamic Multi-Factor Strategy Relative Performance
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
From the start of 2020 through April 8, 2022, the dynamic multi-factor strategy returned 44.1%. Over that same period, the S&P 500 gained 38.9%, for 5.2% outperformance for the dynamic multi-factor strategy. Fig. 3 below shows the monthly performance of the dynamic strategy vs. the S&P 500 since the start of 2020. The dynamic strategy underperformed the S&P 500 by 0.5% in March. An overweight toward quality contributed to the poor return in March.
Fig. 3 – Dynamic Strategy Recent Relative Performance
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
Dynamic Model: Factor Weights for March
Fig. 4 below indicates the latest weights assigned to each of the six factors in the dynamic multi-factor strategy. As of the latest rebalance, the dynamic strategy is overweight the value and low-volatility factors while being underweight quality and growth.
Fig. 4 – Updated Factor Weights in Dynamic vs. Static Multi-Factor Portfolio
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
Baseline Stock Selection Model: Performance and Discussion
We have a stock selection framework that uses composite factors across five dimensions (value, quality, momentum, estimates and investment) to predict stock performance. The model produces a list of 100 favored investments from across the S&P 500 constituents. Fig. 5 below shows the historical performance of the basket of 100 favored stocks, rebalanced monthly.
Fig. 5 – Performance of Long Basket of Stock Selection Model (Relative to S&P 500)
Source: S&P, Factset, Fundstrat analysis.
Fig. 6 below shows the performance of the basket of 100 favored stocks from each of the 5 composite factors (value, quality, momentum, estimates and investment) that make up the overall stock selection model, along with the performance of the model for March. The model underperformed the S&P 500 by 0.62% during March (orange bar at right). At the factor level, four of the five factors underperformed last month; only the momentum factor contributed positively.
Fig. 6 – Performance of Factors and Overall Model for March
Source: S&P, FactSet, Fundstrat analysis.
Market Valuation: Residual Income Model
We use a residual income model as the primary tool to value the overall market (see link). The residual income model produces an estimate for the equity risk premium, or the additional return that equity investors are compensated over the risk-free rate. The history of the equity risk premium is shown in Fig. 7. At the end of March, the equity risk premium implied by the market was 3.2%. This falls within the recent historical average of 3-5%.
Fig. 7 – History of the Equity Risk Premium Implied by a Residual Income Model
Source: S&P, FactSet, Fundstrat analysis
We also use the equity risk premium to evaluate the relative attractiveness of equities compared to investment grade fixed income via the ratio of their yields. Historically, when equities are expensive compared to fixed income (i.e. equities have a relatively low yield) the stock market experiences smaller average returns and higher volatility over the subsequent quarter (see Fig. 8).
Fig. 8 – Equity Market Return and Volatility Conditioned on Yield Ratio
Source: Ice Data Indices, LLC, retrieved from FRED, Federal Reserve Bank of St. Louis; March 31, 2022, S&P, FactSet, Fundstrat analysis.
At the end of March, the yield ratio indicated that equities were overvalued. Based on the historical relationship, we would thus expect muted returns and higher equity market volatility over the next quarter.
