Despite a temporary return to normalcy in 2022, equity factor strategies face performance challenges compared to cap-weighted indices since the 2020 COVID-19 market crash . There are many explanations for these challenges, but the focus here is on another question. :
Is it possible to more closely match the performance of factor portfolios to cap-weighted benchmarks while retaining the benefits and economically sound underpinnings of the factor approach to equity investing?
Before answering that, let’s briefly review the drawbacks of market cap weighted indices. In a market capitalization weighted index, companies with higher market capitalization are given more weight in the index. On the other hand, smaller companies, who are considered to have the most room for growth, are underrepresented. There are three risks associated with investing in a market capitalization weighted index strategy. The first is that the companies with the largest weighting can “mean back” to lower price levels and thus suffer losses. Second, by undervaluing SMEs, cap-weight strategies may prevent investors from making meaningful returns on companies with the greatest growth potential. Finally, market cap-weighted index strategies are relatively concentrated on a small subset of the largest stocks. This lack of diversification goes against the foundations of modern investing and leaves investors vulnerable to significant downside risk should one or more of his largest index constituents experience significant drawdowns. increase.
In contrast, a well-constructed equity factor strategy is driven by risk factors that are proven to benefit investors over the long term. These factors (value, momentum, scale, profitability, investment, low volatility) have been empirically tested for decades by various researchers and have clear and intuitive economic underpinnings. A multi-factor portfolio with exposure to all six factors typically represents a more diversified, lower volatility investment vehicle compared to cap-weighted indices and products that emulate their behavior. The latter characteristic works well for factor portfolios, but as we have seen, equity factor portfolios can underperform cap-weighted strategies in some market environments. The question is, is there a way to retain the benefits of factor investing while staying more in line with the performance of market cap-weighted indices?
what to do?
As you can see below, there is no need to choose between factor investing and cap-weighted performance. Leaning into cap-weighted benchmarks in a massive way is likely not going to pay off for investors in the long run, but there are ways around the middle. In other words, continue to invest in factor strategies, but apply tracking error constraints to reduce the performance gap between cap-weighted benchmarks and “unconstrained”. ” Factor portfolio over time. As our analysis shows, applying the latter adjustment to factor portfolios has both short- and long-term advantages and disadvantages.
How does the Tracking Error Constraint Factor Portfolio work?
The graph below shows the recent performance difference between a standard six factor portfolio (with equal weight for each factor) and a tracking error (TE) constrained variation of that portfolio. The table shows that applying the TE constraint significantly narrows the performance gap between the factor portfolio and the cap-weighted index. However, the cost these portfolios pay is about 100 basis points (bps) more volatility and worse downside protection when measured at maximum drawdown.
factor portfolio with tracking error constraint,
From December 31, 2022 to June 30, 2023
cap Weighted |
Six factor equal weight |
Six factor equal weight 1% TE target |
Six factor equal weight 2% TE target |
|
return | 17.13% | 6.04% | 14.70% | 12.38% |
volatility | 14.44% | 13.10% | 14.05% | 13.72% |
sharp ratio |
1.01 | 0.27 | 0.87 | 0.72 |
maximum.drawdown | 7.43% | 7.90% | 7.51% | 7.61% |
Relative return |
– | -11.09% | -2.43% | -4.75% |
tracking error |
– | 4.65% | 0.98% | 1.95% |
information ratio |
– | N/A | N/A | N/A |
maximum.Relative drawdown |
– | 10.04% | 2.19% | 4.29% |
The sector composition of TE-managed portfolios in the table below shows that the strong underexposure to the technology sector is significantly reduced compared to standard multi-factor portfolios. This may not be all that surprising. Ultimately, large tech companies are one of the main drivers for outperforming capweight vehicles relative to capital adequacy strategies.
Sector allocation as of 30 June 2023
cap weight | Six factor equal weight |
Six factor equal weight 1% TE target |
Six factor equal weight 2% TE target |
||||
absolute weight | relative weight | absolute weight | relative weight | absolute weight | relative weight | ||
energy | 4.7% | 6.3% | 2.0% | 5.3% | 0.6% | 5.9% | 1.2% |
Basic material |
2.3% | 2.6% | 0.3% | 2.4% | 0.0% | 2.4% | 0.1% |
industrial | 8.8% | 7.4% | -1.4% | 8.3% | -0.4% | 7.9% | -0.9% |
circular consumer | 12.4% | 11.7% | -1.0% | 12.0% | -0.3% | 11.7% | -0.7% |
non circular consumer |
6.5% | 11.2% | 5.1% | 7.4% | 0.9% | 8.3% | 1.8% |
Finance | 12.7% | 13.1% | 1.5% | 12.9% | 0.2% | 13.1% | 0.4% |
health Care |
14.2% | 17.7% | 4.2% | 14.8% | 0.6% | 15.4% | 1.2% |
technology | 34.5% | 21.5% | -15.7% | 31.7% | -2.8% | 28.9% | -5.7% |
Telecommunications | 1.1% | 2.0% | 0.9% | 1.3% | 0.2% | 1.6% | 0.4% |
public works | 2.7% | 6.6% | 4.1% | 3.8% | 1.0% | 4.8% | 2.1% |
Over a longer measurement period, the following graph shows that controlling for TE increases volatility and decreases returns, thus hurting long-term risk-adjusted performance. Information ratios and the odds of outperforming market cap-weighted indices over various time periods also deteriorate slightly.
long-term risk-adjusted performance,
From June 30, 1971 to December 31, 2022
cap weighted | Six factor equal weight |
|||
standard portfolio |
standard portfolio TE 1% |
standard portfolio TE 2% |
||
a year Return value |
10.22% | 13.10% | 10.95% | 11.63% |
a year volatility |
17.33% | 15.53% | 16.82% | 16.38% |
sharpe ratio | 0.33 | 0.55 | 0.38 | 0.43 |
maximum. drawdown |
55.5% | 50.9% | 54.0% | 53.5% |
a year Relative Return value |
– | 2.88% | 0.72% | 1.41% |
a year tracking error |
– | 4.20% | 1.14% | 2.21% |
information ratio |
– | 0.69 | 0.63 | 0.64 |
maximum.Relative drawdown |
– | 20.1% | 5.8% | 10.7% |
excellent performance probability (1 year) |
– | 66.89% | 67.71% | 67.38% |
excellent performance probability (3 years) |
– | 79.42% | 75.81% | 75.30% |
excellent performance probability (for 5 years) |
– | 86.94% | 84.62% | 84.44% |
Conclusion
Tracking error risk management is an effective way to manage out-of-sample tracking error in multi-factor indices and also helps reduce sector deviation in multi-factor indices. You don’t have to throw your baby out with the bath water.
Over the long term, however, matching the performance of factor portfolios to cap-weighted indices can have a negative impact on both absolute and risk-adjusted returns. Moreover, the simple cap-weight approach to equity investing lacks the economic and conceptual underpinnings to justify its use. While they may perform well in certain market conditions, they do not have a formula for good long-term risk-adjusted performance.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, and the opinions expressed do not necessarily reflect those of the CFA Institute or the author’s employer.
Image credit: ©Getty Images/Wengen Ling
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