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DFAS vs. SCDS
Performance
Return for Risk
Drawdowns
Volatility
Dividends

Performance

DFAS vs. SCDS - Performance Comparison

The chart below illustrates the hypothetical performance of a $10,000 investment in Dimensional U.S. Small Cap ETF (DFAS) and JPMorgan Fundamental Data Science Small Core ETF (SCDS). The values are adjusted to include any dividend payments, if applicable.

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Returns By Period

In the year-to-date period, DFAS achieves a 15.74% return, which is significantly lower than SCDS's 27.90% return.


DFAS

1D
0.12%
1M
3.77%
YTD
15.74%
6M
12.99%
1Y
31.21%
3Y*
16.27%
5Y*
8.37%
10Y*

SCDS

1D
1.07%
1M
5.98%
YTD
27.90%
6M
24.54%
1Y
48.53%
3Y*
5Y*
10Y*
*Multi-year figures are annualized to reflect compound growth (CAGR)

DFAS vs. SCDS - Yearly Performance Comparison


2026 (YTD)20252024
DFAS
Dimensional U.S. Small Cap ETF
15.74%8.17%10.41%
SCDS
JPMorgan Fundamental Data Science Small Core ETF
27.90%11.27%7.26%

Correlation

The correlation between DFAS and SCDS is 0.94, indicating a strong positive relationship between their price movements. Combining them offers limited diversification - they tend to fall together during downturns.


Correlation
Correlation (1Y)
Calculated over the trailing 1-year period

0.94

Correlation (All Time)
Calculated using the full available price history since Aug 8, 2024

0.96

The correlation between DFAS and SCDS has been stable across timeframes, ranging from 0.94 to 0.96 - a consistent structural relationship.

DFAS vs. SCDS - Sectors Allocation Comparison


Sectors
DFAS
SCDS

Financial Services

19.2%
15.2%

Industrials

18.9%
16.3%

Technology

15.1%
23.8%

Consumer Cyclical

13.0%
10.3%

Healthcare

12.0%
13.8%

Energy

6.4%
4.8%

Basic Materials

5.2%
3.2%

Consumer Defensive

4.2%
2.5%

Utilities

2.8%
2.3%

Communication Services

2.6%
2.4%

Real Estate

0.7%
5.4%

Financial Services

DFAS
19.2%
SCDS
15.2%

Industrials

DFAS
18.9%
SCDS
16.3%

Technology

DFAS
15.1%
SCDS
23.8%

Consumer Cyclical

DFAS
13.0%
SCDS
10.3%

Healthcare

DFAS
12.0%
SCDS
13.8%

Energy

DFAS
6.4%
SCDS
4.8%

Basic Materials

DFAS
5.2%
SCDS
3.2%

Consumer Defensive

DFAS
4.2%
SCDS
2.5%

Utilities

DFAS
2.8%
SCDS
2.3%

Communication Services

DFAS
2.6%
SCDS
2.4%

Real Estate

DFAS
0.7%
SCDS
5.4%

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Return for Risk

DFAS vs. SCDS — Risk / Return Rank

Compare risk-adjusted metric ranks to identify better-performing investments over the past 12 months.

DFAS
DFAS Risk / Return Rank: 6060
Overall Rank
DFAS Sharpe Ratio Rank: 5757
Sharpe Ratio Rank
DFAS Sortino Ratio Rank: 5959
Sortino Ratio Rank
DFAS Omega Ratio Rank: 5252
Omega Ratio Rank
DFAS Calmar Ratio Rank: 6969
Calmar Ratio Rank
DFAS Martin Ratio Rank: 6565
Martin Ratio Rank

SCDS
SCDS Risk / Return Rank: 8585
Overall Rank
SCDS Sharpe Ratio Rank: 8484
Sharpe Ratio Rank
SCDS Sortino Ratio Rank: 8585
Sortino Ratio Rank
SCDS Omega Ratio Rank: 7777
Omega Ratio Rank
SCDS Calmar Ratio Rank: 9191
Calmar Ratio Rank
SCDS Martin Ratio Rank: 8989
Martin Ratio Rank
The rank (0–100) shows how this investment's returns compare to the risk taken. Higher = better. Based on the past 12 months of data, combining Sharpe, Sortino, and other metrics used by quantitative funds and institutional investors.

DFAS vs. SCDS - Risk-Adjusted Trends Comparison

This table presents a comparison of risk-adjusted performance metrics for Dimensional U.S. Small Cap ETF (DFAS) and JPMorgan Fundamental Data Science Small Core ETF (SCDS). Risk-adjusted metrics are performance indicators that assess an investment's returns in relation to its risk, enabling a more accurate comparison of different investment options.

Values are calculated on a 1-year rolling basis and updated daily. Risk-adjusted metrics are more stable over longer periods — use the period switch above to explore them.


DFASSCDSDifference
Sharpe ratioReturn per unit of total volatility

-0.77

Sortino ratioReturn per unit of downside risk

-0.90

Omega ratioGain probability vs. loss probability

1.32

1.44

-0.12

Calmar ratioReturn relative to maximum drawdown

3.35

5.51

-2.16

Martin ratioReturn relative to average drawdown

11.51

19.13

-7.63

DFAS vs. SCDS - Sharpe Ratio Comparison

The current DFAS Sharpe Ratio is 1.85, which is comparable to the SCDS Sharpe Ratio of 2.62. The chart below compares the historical Sharpe Ratios of DFAS and SCDS, calculated using daily returns over the previous 12 months. A higher Sharpe Ratio indicates better risk-adjusted performance relative to the risk-free rate.


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Drawdowns

DFAS vs. SCDS - Drawdown Comparison

The maximum DFAS drawdown since its inception was -26.13%, roughly equal to the maximum SCDS drawdown of -26.71%. Use the drawdown chart below to compare losses from any high point for DFAS and SCDS.


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Drawdown Indicators


DFASSCDSDifference

Max Drawdown

Largest peak-to-trough decline

-26.13%

-26.71%

+0.58%

Max Drawdown (1Y)

Largest decline over 1 year

-9.36%

-8.85%

-0.51%

Max Drawdown (3Y)

Largest decline over 3 years

-26.13%

Max Drawdown (5Y)

Largest decline over 5 years

-26.13%

Current Drawdown

Current decline from peak

-0.12%

0.00%

-0.12%

Average Drawdown

Average peak-to-trough decline

-8.24%

-5.16%

-3.08%

Ulcer Index

Depth and duration of drawdowns from previous peaks

2.72%

2.54%

+0.18%

Volatility

DFAS vs. SCDS - Volatility Comparison

The current volatility for Dimensional U.S. Small Cap ETF (DFAS) is 4.70%, while JPMorgan Fundamental Data Science Small Core ETF (SCDS) has a volatility of 6.04%. This indicates that DFAS experiences smaller price fluctuations and is considered to be less risky than SCDS based on this measure. The chart below showcases a comparison of their rolling one-month volatility.


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Volatility by Period


DFASSCDSDifference

Volatility (1M)

Calculated over the trailing 1-month period

4.70%

6.04%

-1.34%

Volatility (6M)

Calculated over the trailing 6-month period

11.92%

13.57%

-1.65%

Volatility (1Y)

Calculated over the trailing 1-year period

17.00%

18.67%

-1.67%

Volatility (5Y)

Calculated over the trailing 5-year period, annualized

20.81%

21.26%

-0.45%

Volatility (10Y)

Calculated over the trailing 10-year period, annualized

20.82%

21.26%

-0.44%

DFAS vs. SCDS - Expense Ratio Comparison

DFAS has a 0.26% expense ratio, which is lower than SCDS's 0.40% expense ratio.


Dividends

DFAS vs. SCDS - Dividend Comparison

DFAS's dividend yield for the trailing twelve months is around 0.90%, more than SCDS's 0.88% yield.


PositionTTM20252024202320222021
DFAS
Dimensional U.S. Small Cap ETF
0.90%0.99%0.93%1.00%1.03%2.87%
SCDS
JPMorgan Fundamental Data Science Small Core ETF
0.88%1.15%0.42%0.00%0.00%0.00%

Frequently Asked Questions


With a correlation of 0.94, DFAS and SCDS move almost identically. Holding both adds very little diversification - you're essentially doubling your position in the same market segment. Choosing one is usually more capital-efficient.

SCDS has higher volatility (6.04%) compared to DFAS (4.70%). In terms of maximum drawdown, DFAS dropped -26.13% vs SCDS's -26.71%.

On 1-year performance, SCDS leads with 48.53% vs 31.21% for DFAS. On fees, DFAS is cheaper at 0.26% per year. On volatility, DFAS has been the lower-risk option at 4.70%. The better choice depends on whether you care most about return, fees, risk, or income.

Over the 1-year period, SCDS has performed better with a 48.53% return vs 31.21%. Past performance does not guarantee future results, so compare this with risk, fees, and fund exposure.

DFAS is cheaper with a 0.26% expense ratio, compared with 0.40% for SCDS.

DFAS has the higher dividend yield at 0.90%, compared with 0.88% for SCDS.

They also come from different issuers: Dimensional and JPMorgan. Their fees differ too: 0.26% for DFAS and 0.40% for SCDS.

SCDS currently has the higher Sharpe Ratio (2.62 vs 1.85), meaning it's delivered slightly more return per unit of risk over the trailing 12 months. However, this ranking shifts over time - use the Risk/Return Score above for a more comprehensive view that combines Sharpe, Sortino, and other measures used by quantitative funds.

Portfolio Optimizer

Find the right allocation for DFAS and SCDS

Add both to a portfolio and optimize allocations for your target — whether that's maximizing returns, minimizing drawdowns, or balancing risk across holdings.

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