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 growth, with the S&P 500 Growth index outperforming S&P 500 Value by 3.0%. The low-volatility factor just barely beat the benchmark, earning 0.1% over the S&P 500. The other four factors all underperformed, with momentum and value each underperforming by over 2%. 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
Note: Shows the performance of six factors (growth, quality, low-volatility, momentum, size, and value) relative to the S&P 500. Gray bars indicate performance over the past month, blue bars over the past 3 months, and orange bars over the past 12 months. Analysis runs through July 8, 2022. Transaction costs are not considered.
Looking back over a 3-month period, low-volatility has still performed best, as it outperformed the S&P 500 by 3.3%. The low-volatility factor is also the best performer over the past 12 months, as it has outperformed by 10.4% over that span. Size continues to be a laggard, as small-cap stocks have underperformed the benchmark by 13.1% on a trailing 12-month basis.
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
Note: Shows the cumulative returns of the dynamic multi-factor investing strategy. Strategy assigns factor weights using the inverse of 52-week trailing return volatility, and overweights (underweights) the factor with the best (worst) trailing momentum. Strategy is rebalanced monthly. Period of analysis is from November 1997 through July 8, 2022. Transaction costs are not considered.
From the start of 2020 through July 8, 2022, the dynamic multi-factor strategy returned 27.7%. Over that same period, the S&P 500 gained 20.7%, 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. June marked the third consecutive winning month for the dynamic strategy, as it outperformed the S&P 500 by 0.9%. An overweight toward the low-volatility factor contributed to the outperformance for the dynamic factor strategy in June.
Fig. 3 – Dynamic Strategy Recent Relative Performance
Note: Shows the monthly returns of the dynamic multi-factor investing strategy. Strategy assigns factor weights using the inverse of 52-week trailing return volatility, and overweights (underweights) the factor with the best (worst) trailing momentum. Strategy is rebalanced monthly. Period of analysis is from January 2020 through June 2022. Transaction costs are not considered.
Dynamic Model: Factor Weights for July
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 is overweight the value and size (small-cap) factors while being underweight low-volatility and growth.
Fig. 4 – Updated Factor Weights in Dynamic vs. Static Multi-Factor Portfolio
Note: Shows weight for each of the six factors in the dynamic and static multi-factor portfolios as of July 8, 2022.
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. 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)
Note: Shows the cumulative return of the favored basket of 100 stocks from baseline 5-factor stock selection model (orange line) and the S&P 500 index (dotted black line). Basket of favored stocks is weighted using square root of market capitalization and rebalanced monthly. Period of analysis is from 2001 through June 2022. Transaction costs are not considered.
Fig. 6 below shows the performance during June 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). After outperforming the S&P 500 by over 6% during the first five months of 2022, the model struggled in June, underperforming the S&P 500 by 1.45%.
Of the five of the composite factors that make up the model, four underperformed last month, with only momentum outperforming the index. The value and estimates were particularly weak during June, underperforming by 3.6% and 1.6%, respectively. Despite the poor performance over the past month, the model’s basket of favored stocks outperformed the S&P 500 by 4.3% during the first half of 2022.
Fig. 6 – Performance of Factors and Overall Model for June
Note: Shows the performance for June 2022 for the top quintile of the five composite factors (value, quality, momentum, estimates and investment – blue bars) and for the overall model (orange bar). Baskets are weighted using square root of market capitalization. Universe is the S&P 500. Transaction costs are not considered.
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 June, the equity risk premium implied by the model was 3.97%. This falls within the recent historical range of 3-5%.
Fig. 7 – History of the Equity Risk Premium Implied by the Residual Income Model
Note: Shows the equity risk premium implied by a residual income model. Gray shaded regions indicate recessions. Period of analysis is from January 2005 through June 2022.
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
Note: Shows subsequent 3-month S&P 500 return (blue bars) and volatility (orange bars, right-hand axis) conditioned on the ratio of equity-to-investment grade yield. High (low) equity-to-investment grade yield is defined as the equity-to-investment grade yield being above (below) the 75th (25th) percentile observation using a rolling 60-month window. Medium equity-to-investment grade yield is when the equity-to-investment grade yield is between the 25th and 75th percentile observations, using a rolling 60-month window. Period of analysis is from January 2006 through June 2022. Transaction costs are not considered.
At the end of June, the yield ratio indicated that equities continued to remain in the overvalued state. Based on the above relationship, we continue to expect muted returns and higher equity market volatility over the next 3 months.
[1] See fsinsight.com
