Key Takeaways
- Of the factors we track, value and low volatility showed the best performance over the past month, while the growth factor underperformed.
- After struggling in March, our dynamic factor portfolio rebounded strongly in April, outperforming the S&P 500 by 2.7%. Since the start of 2020, this strategy has outperformed the S&P 500 by 7.6%.
- After the latest rebalance, the dynamic factor portfolio is now overweight value and low-volatility and is underweight quality and growth.
- Our stock selection model had a very strong April as a basket of the favored stocks from the model outperformed the S&P 500 by 2.96%. All five of the custom factors that make up the stock selection model outperformed the S&P 500 in April.
- Our market valuation methodology continues to see equities as overvalued relative to investment grade fixed income. As a result, we expect muted returns and sustained volatility to continue in the equity market.
Factor Performance Review
We track the performance of six factors (growth, quality, low-volatility, momentum, size, and value) as part of our multi-factor strategy. Over the past month, the best factors were value, which earned 3.1% over the S&P 500, low-volatility (+2.8% relative to the S&P 500) and quality (+1.8% relative). On the other hand, growth was the worst-performing factor, underperforming the S&P 500 by 3.2%. 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 been by far the best performing factor, as it has outperformed the S&P 500 by 8.9% over that period. Value has also enjoyed strong recent performance, earning 4.9% over the index. Looking back further over a 12-month horizon, size still lags the other five factors by a healthy margin. Small-cap stocks have underperformed the benchmark by 17.5% 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 May 6, 2022, the dynamic multi-factor strategy returned 35.3%. Over that same period, the S&P 500 gained 27.6%, for 7.7% 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 enjoyed very strong performance in April, outperforming the S&P 500 by 2.7%. Allocation toward value and low-volatility, and an underweight to growth, contributed to the strong model performance.
Fig. 3 – Dynamic Strategy Recent Relative Performance
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
Dynamic Model: Factor Weights for May
Fig. 4 below indicates the latest weights assigned to each of the six factors in the dynamic multi-factor strategy. The dynamic strategy continues to be 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 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 during April of each of the 5 composite factors (value, quality, momentum, estimates and investment) that make up the stock selection model, along with the performance of the overall model. The model saw strong performance in April, outperforming the S&P 500 by 2.96% (orange bar at right). All five of the composite factors outperformed last month, which contributed to the strong model performance.
Fig. 6 – Performance of Factors and Overall Model for April
Source: S&P, FactSet, Fundstrat analysis.
Market Valuation: Residual Income Model
We use a residual income model to value the market[1]. 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 April, the equity risk premium implied by the model was 3.3%. This is toward the bottom of the recent historical range of 3-5%.
Fig. 7 – History of the Equity Risk Premium Implied by the 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; April 29, 2022, S&P, FactSet, Fundstrat analysis.
At the end of April, the yield ratio indicated that equities continued to be overvalued. Based on the above relationship, we expect muted returns and higher equity market volatility over the next 3 months.
[1] See https://fsinsight.com/quantitative-strategy/2021/12/21/market-valuation/
