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 factor was momentum, which outperformed the S&P 500 index by 5.5%. Quality and value also turned in strong performances over the past month, outperforming the S&P 500 by 2.2% and 1.4%, respectively. The worst-performing factor over the past month was low volatility, which underperformed the S&P 500 by 1.6%. Performance for each of the six factors over the past month is shown as the gray bars in Fig. 1.
Fig. 1 – Recent Performance of Factors
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
Looking back over a 3-month period (blue bars in Fig. 1), momentum has seen the best performance, outperforming the S&P 500 by 4.7%. Much of the outperformance in momentum has occurred since July, when momentum turned in a historically poor month. On a trailing 12-month basis, the size factor continues to lag, as it has underperformed by 7.5%, but growth has also seen poor performance over the past year, underperforming the S&P 500 by 5.1% during that span.
Multi-Factor Portfolio Performance Review
We track a dynamic multi-factor portfolio that 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
From the start of 2020 through October 7, 2022, the dynamic multi-factor strategy returned 19.7%. Over that same period, the S&P 500 has gained 12.7%, for 7.0% of 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.
Fig. 3 – Dynamic Strategy Recent Relative Performance
Source: Bloomberg, S&P, Russell, Fundstrat analysis.
The dynamic strategy continued to outperform the S&P 500 in September, beating the benchmark by 0.1% for the month. The overweight toward the size factor (small-cap stocks) contributed to the dynamic factor strategy’s outperformance in September.
Dynamic Model: Factor Weights for October
Fig. 4 below indicates the latest weights assigned to each of the six factors in the dynamic multi-factor strategy. For the next month, the dynamic strategy remains overweight in the size (small-cap) and growth factors while being underweight quality and value.
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
Our quantitative stock selection model uses composite factors across five dimensions (value, quality, momentum, estimates, and investment) to predict individual stock performance. The model produces a list of 100 favored investments from across the S&P 500. Fig. 5 below shows the historical performance of the basket of favored stocks, rebalanced monthly (orange line) compared to the S&P 500 (black dotted line).
Fig. 5 – Performance of Long Basket of Stock Selection Model (Relative to S&P 500)
Source: S&P, FactSet, Fundstrat analysis.
Fig. 6 (next page) shows the performance during September for each of the 5 composite factors that make up the stock selection model (blue bars), along with the performance of the overall model (orange bar at right). The model continued to outperform in September, as its basket of favored stocks outperformed the S&P 500 index by 0.2% for the month. Year to date, the model has outperformed the S&P 500 by 3.4%.
The composite factors that make up the model showed varying performance in September, with the value factor performing worst. Three of the five factors (momentum, estimates and investment) contributed positive return during September. The momentum factor continued to pace the five composite factors, as it turned in the best performance for the second consecutive month, earning 3.4% relative to the benchmark. After generating historically poor performance in July, the momentum factor has since rebounded strongly, generating 4.9% of cumulative outperformance relative to the S&P 500 during August and September.
Fig. 6 – Performance of Factors and Overall Model for September
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 September, the equity risk premium implied by the model was 3.52%. This latest value for the equity risk premium falls toward the lower end of the recent historical range of 3-5%. Despite the sell-off in the market during September, the equity risk premium only increased by 3 basis points from its end-August value (typically, the equity risk premium moves inversely with the market).
Fig. 7 – History of the Equity Risk Premium Implied by the Residual Income Model
Using the equity risk premium, we can 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; September 30, 2022, S&P, FactSet, Fundstrat analysis.
At the end of September, the yield ratio indicated that equities remain overvalued relative to investment grade fixed income. Based on the above relationship, we continue to expect muted returns and higher equity market volatility over the next 3 months.
[1] See Our Market Valuation Report
