Three Reasons Why Dimensional Models Stand Out from the Pack

Dimensional Models seek to deliver a better investment experience. Here are three reasons they stand out from the pack:

1. The investment process is powered by financial science, not speculation.
2. The models are composed of Dimensional funds, which have a strong track record of outperformance over time.
3. They apply strategic asset allocation at the model level with daily active implementation at the fund level.

Dimensional’s investment approach is driven by rigorous and reliable research. Our Research group, which oversees the Dimensional Models, is at the center of our investment process and works closely with leading academics—including five Nobel laureates—to better understand markets and what drives returns.¹

Rather than focusing on what’s shined in a backtest or what is the hot topic today, Dimensional’s investment approach starts with a belief in market prices and is supported by decades of theoretical and empirical research.² Instead of trying to outguess the collective wisdom of the market, our approach uses information in asset prices and empirical data about companies to target reliable drivers of higher expected returns. Within equities, we design portfolios to overweight securities with smaller market capitalization, lower relative price, and higher profitability. Within fixed income, we target higher expected returns along the term, credit, and currency of issuance dimensions. This approach frees us from the unreliability of traditional forecasting.  

With confidence in markets, deep connections to the academic community, and a focus on implementation, we go where the science leads and continue to pursue new insights, both large and small, to help investors reach their goals.

Research tells us that there are drivers of returns, or factors, associated with securities sharing certain characteristics. While many investment managers may claim to use “factor-based” approaches, it’s worth asking whether those factors are truly evidence-based and likely to appear in the future, or merely the product of chasing trends and spurious perceived correlations between data and returns. And factors identified in the data do not necessarily translate into outperformance for investors. 

Dimensional has been a pioneer and leader in an investing approach that incorporates multiple factors, applying a systematic, evidence-based approach for over 40 years. Over that time, we have developed deep expertise in portfolio design, management, and trading. It is this expertise in implementation that has allowed us to deliver reliable equity and fixed income premiums to investors, net of fees and expenses.

Indeed, our multi-asset investment solutions have systematically added value over the long term. The Global Equity Portfolio, the Global Allocation 60/40 Portfolio, and the Global Allocation 25/75 Portfolio have beaten their prospectus benchmarks by an annualized 76, 65, and 46 basis points (hundredths of a percentage point), respectively, since each fund’s first full month.³ For a $1,000 investment in the Global Equity Portfolio starting in January 2004, that’s a difference in ending wealth of $5,994 compared to $5,179 for the benchmark as of September 2024 (see Exhibit 1).

A review of Dimensional’s US-domiciled equity and fixed income funds illustrates that positive long-term premiums and our pursuit of them in a cost-effective way have led Dimensional to outperform benchmarks and peers over long periods and across strategies.⁴ Taking a long-term view, over the 20 years ending September 2024, 84% of Dimensional’s US-domiciled funds outperformed their benchmarks compared to just 17% for the industry. While only 46% of funds in the industry survived the 20-year period, investors in Dimensional funds were unaffected by closures, as 100% of Dimensional funds are still in existence.

We believe a manager’s body of work across all funds launched gives you more information about that manager than evaluating a single strategy. In a model that is composed of multiple funds, a compelling track record across the manager’s fund lineup is of particular importance to investors.

Dimensional models have low turnover by design. Low turnover at the model level can lead to lower transaction costs and more tax-efficient implementation for investors.

Low turnover at the model level is made possible by a thoughtful, strategic approach to asset allocation that focuses on the split between stocks and bonds (one of the most powerful levers investors can pull to manage overall portfolio risk and return), global diversification, and an emphasis on known drivers of higher expected returns. In contrast, a short-term, tactical approach to asset allocation—often motivated by unreliable market forecasts—can cause unnecessary turnover.

Our daily process at the fund level means that our models can incorporate real-time market information within their portfolios and still have low turnover at the model level. An evidence-based approach can reduce unnecessary costs and taxes, incorporate market information that matters, and lead to transparent and understandable outcomes that can help move investors toward their goals.

Asset allocation: The way in which a portfolio is divided among underlying assets.

Correlation: A statistical measure of linear dependence.

Credit premium: The return difference between bonds of similar maturity but different credit quality.

Currency of issuance: The currency in which an asset is issued, such as a USD- versus euro-denominated bond.

Factor-based investing: An investing approach targeting securities associated with higher returns.

Global diversification: A portfolio that includes an allocation to securities across the globe, including US, developed ex US, and emerging market securities.

Higher expected returns: Expected outperformance informed by historical data.

Market capitalization: The total value of all a company’s shares of stock, calculated by multiplying the price of a stock by its total number of outstanding shares.

Relative price: Refers to a company’s price, or the market value of its equity, in relation to another measure of economic value, such as book value.

Profitability: A company’s operating income before depreciation and amortization minus interest expense scaled by book equity.

Term premium: The return difference between bonds with different maturities but similar credit quality.

Data Sample

The sample includes US-domiciled, USD-denominated open-end and exchange-traded funds (ETFs) in the following Morningstar categories. Non-Dimensional fund data provided by Morningstar. Dimensional fund data is provided by the fund accountant. Dimensional funds or subadvised funds whose access is or previously was limited to certain investors are excluded. Dimensional Retirement Equity Fund included. Index funds, load-waived funds, and funds of funds are excluded from the industry sample.

Methodology

The beginning samples include funds as of the start of each respective time period. Surviving funds are those with return observations for every month of the sample period. Each fund is evaluated relative to its primary prospectus benchmark. Where the full series of primary prospectus benchmark returns is unavailable, non-Dimensional funds are instead evaluated relative to their Morningstar category index. Outperformers are funds that survived the sample period and whose cumulative net return over the period exceeded that of their respective benchmark. We aggregate funds with multiple share classes to the strategy level.

Morningstar Categories (Equity)

Equity fund sample includes the following Morningstar historical categories: Diversified Emerging Markets, Europe Stock, Foreign Large Blend, Foreign Large Growth, Foreign Large Value, Foreign Small/Mid Blend, Foreign Small/Mid Growth, Foreign Small/Mid Value, Global Real Estate, Japan Stock, Large Blend, Large Growth, Large Value, Mid-Cap Blend, Mid-Cap Growth, Mid-Cap Value, Miscellaneous Region, Pacific/Asia ex-Japan Stock, Real Estate, Small Blend, Small Growth, Small Value, Global Large-Stock Blend, Global Large-Stock Growth, Global Large-Stock Value, and Global Small/Mid Stock.

Morningstar Categories (Fixed Income)

Fixed income fund sample includes the following Morningstar historical categories: Corporate Bond, High Yield Bond, Inflation-Protected Bond, Intermediate Core Bond, Intermediate Core-Plus Bond, Long-Term Bond, Intermediate Government, Long Government, Muni California Intermediate, Muni California Long, Muni Massachusetts, Muni Minnesota, Muni National Intermediate, Muni National Long, Muni National Short, Muni New Jersey, Muni New York Intermediate, Muni New York Long, Muni Ohio, Muni Pennsylvania, Muni Single State Intermediate, Muni Single State Long, Muni Single State Short, Muni Target Maturity, Short Government, Short-Term Bond, Ultrashort Bond, Global Bond, and Global Bond-USD Hedged.

Index Data Sources

Index data provided by Bloomberg, MSCI, Russell, FTSE Fixed Income LLC, and S&P Dow Jones Indices LLC. Bloomberg data provided by Bloomberg. MSCI data © MSCI 2024, all rights reserved. Frank Russell Company is the source and owner of the trademarks, service marks, and copyrights related to the Russell Indexes. FTSE fixed income indices © 2024 FTSE Fixed Income LLC. All rights reserved. S&P data © 2024 S&P Dow Jones Indices LLC, a division of S&P Global. All rights reserved.

Indices are not available for direct investment. Their performance does not reflect the expenses associated with management of an actual portfolio. US-domiciled mutual funds and US-domiciled ETFs are not generally available for distribution outside the US. 

Mutual fund investment values will fluctuate, and shares, when redeemed, may be worth more or less than original cost. Diversification neither assures a profit nor guarantees against a loss in a declining market. There is no guarantee investment strategies will be successful. Past performance is no guarantee of future results. 

ETFs trade like stocks, fluctuate in market value, and may trade either at a premium or a discount to their net asset value. ETF shares trade at market price and are not individually redeemable with the issuing fund, other than in large share amounts called creation units. ETFs are subject to risks similar to those of stocks, including those regarding short-selling and margin account maintenance. Brokerage commissions and expenses will reduce returns.