Syntax Direct℠: a Direct-to-Index Solution
Key takeaways:
- Syntax Direct℠ provides RIA’s the ability to create and manage boundless direct indexing solutions and rules-based portfolios in an instant, providing scale while meeting client needs in a fraction of the time.
- This paper provides an example of how Syntax Direct can be used to develop a customized solution for a client.
Many portfolios have benefitted from their passive exposure to the S&P 500, as have actively managed large cap growth-oriented equity funds. These strategies have performed very well in 2023 and through 2024 (year-to-date). The strong outperformance of these investments has created heavy exposure in many domestic equity portfolios towards technology-related stocks, which have had very strong performance and high valuations as a group. We have written about the risks this dynamic can cause on several occasions over the past year in our Stratified LargeCap Index quarterly reports. One way to address this bias could be to rebalance a portion of an investor’s holdings to track an index strategy with a quality focus.
Investors have numerous options to implement an investment strategy designed to complement existing holdings. For example, an actively managed mutual fund is one option, but this could raise concerns associated with tax considerations and fees. Investing in an ETF could address the tax concerns; however, finding an ETF that is the desired complement to an investor’s portfolio can be challenging. Alternatively, many investors find that a custom index featuring the desired market exposure and tax- and cost-efficiency can be an attractive option.
For illustrative purposes, we created a custom index, which we refer to as Potential Index Solution, that may serve to mitigate the concentration risk embedded in a tech heavy portfolio. The objectives of this model index are outlined below:
- Better balance: Reduce sector concentration risk, allocate more to underweight sectors.
- Downside protection: Likely to outperform the S&P 500 and growth equities in a downturn.
- Quality bias: Focus on profitable companies with stable earnings and low leverage.
- Dividend yield: Seek cash flow from dividends.
Objectives of Potential Index Solution:
The index model was constructed algorithmically from the universe of domestic large cap stocks in the Syntax US LargeCap Index, which has properties and characteristics highly similar to the S&P 500. The index model targets holding 50 stocks to balance diversification, while also trying to limit the universe to the stocks that best fit the investment objectives. The investment objectives are expressed through factor tilts, which are the identified, desired traits and characteristics of the stocks to be held. For this index model, these include quality (profitability, earnings growth), low leverage (to mitigate financial statement risk), and an above market dividend yield. We also assume that the index model would be rebalanced annually and that dividends would be reinvested. All assumptions in the model can easily be modified.
The weighting methodology is referred to as modified cap weight, which weights constituents proportional to their size and then tilts the holdings in the portfolio to the companies with higher scores to the desired factors (higher quality, low leverage, dividends). This tilt is expressed through the conviction level that we targeted as “medium”; higher conviction leads to stronger tilts, while lower conviction would have a more moderate tilt. The graphic on the right shows the Top 10 Constituents of the index model, which represent about 55% of its total weight.
The list is composed of well-known companies with leadership positions within their respective industries. The largest constituents have a weight of roughly 6.0%. The weight of these ten securities can be adjusted up or down by changing the conviction level.
Given the objective of reducing the exposure to technology stocks, we excluded stocks in the Information Technology sector from this index model, which you can see reflected in the 0% weight to this sector in the table to the right.
Note: the Syntax 500 Index (like the S&P 500) has a weight of nearly 32% to the Information Technology sector, which is dominated by large tech stocks like Microsoft, NVIDIA, Apple and Alphabet. The Potential Index Solution, therefore, has larger allocations to the Consumer Discretionary, Consumer Staples, Healthcare, Energy, and Real Estate sectors relative to the benchmark index. These overweights help provide more balance to our hypothetical portfolio. For example, Energy has a weight of 10.1% in the custom index model, compared to just 3.6% of the benchmark. This allocation can be viewed favorably from a diversification perspective given the economic importance of the Energy sector. There is also the ability to exclude stocks involved in certain segments of the Energy sector, like coal or fossil fuels, if desired.
When an index is created in Syntax Direct, a backtest is automatically generated. Below you can see the backtested performance of the Potential Index Solution relative to the Syntax 500. This backtest is based on the methodology described above, implementing those rules at each historical rebalance date from December 15, 2017 to the present. Please see important disclaimers for information regarding backtested index data.
The following page shows the growth of a hypothetical $1,000 investment tracking this index model, gross of fees and implementation costs, as an investor cannot directly invest in an index model. The custom index model shows strong performance, with the initial hypothetical investment of $1,000 increasing to roughly $1,923.
The Potential Index Solution trailed the Syntax 500 benchmark, which is unsurprising as the index model has reduced exposure to the Magnificent Seven stocks that have driven the large cap market’s performance. Over the same period, $1,000 hypothetically invested to track the Syntax 500 Index would have grown to $2,433, gross of fees and implementation costs.
As part of our backtest, we calculated both calendar- and trailing-year returns for the custom index model and the benchmark. The annual returns are shown below. The results for 2022 and 2023 are particularly noteworthy.
In 2022, the custom index model returned -3.37%, substantially outperforming the -19.59% loss for the benchmark. The lack of tech stocks in the index model would have provided better downside protection in this market environment.
Conversely, as tech stocks rebounded in 2023, the custom index model would have underperformed, returning 8.34% vs. 27.11% for the benchmark. During this two-year period, the hypothetical index model would have provided better balance and downside protection when held with an S&P 500 index.
The annualized returns (depicted below) highlight the solid returns provided by the custom index model, despite underperforming the benchmark.
The strong results of the Syntax 500 Index are reflected in this index’s fundamentals, as shown below. The Syntax 500 Index has a price/earnings ratio of 24.3, relative to 18.9 for the custom index model. Stated alternatively, the Syntax 500 price/earnings valuation is roughly 29% higher than the custom index model.
The custom index model, by design, has a higher dividend yield at 2.6%, compared to 1.5% for the Syntax 500. The average market cap of the stocks in the custom index model is $240 billion, well below the average market cap of $663 billion in the Syntax 500 Index, which is driven higher by the market caps of the mega-tech stocks excluded from the custom index model.
In addition to Syntax Direct’s ability to create personalized index solutions, the system supports your regulatory needs by providing immediate access to factsheets for every index created, accompanied by an index rulebook, a compliance-ready document that details the key assumptions used to create an index. To learn more, please visit www.syntaxdata.com