2,143 ETFs Under the Microscope: Building a High-Confidence Long-Term Portfolio From the Schwab ETF Screen
Which exchange-traded funds actually deserve a place on a diversified long-term watchlist? We take a massive Schwab ETF-screen dataset and build a disciplined framework for finding the strongest combination of fundamentals, risk-adjusted returns, valuation, momentum, and portfolio diversification.
Introduction: Turning a Massive ETF Screen Into an Investment Shortlist
```Exchange-traded funds have transformed investing because they allow investors to buy baskets of securities with a single transaction. But that convenience creates a second problem: there are now far more ETFs than most investors can reasonably evaluate.
The uploaded Schwab screening data illustrates that problem perfectly. Across the three supplied CSV files, there are thousands of ETF records spanning broad-market funds, sector funds, international strategies, fixed-income products, commodities, dividend strategies, thematic funds, small-cap funds, leveraged products, inverse funds, and specialized vehicles.
The objective of this research series is therefore not to identify a handful of ETFs because they happen to have the strongest recent performance. Instead, the goal is to construct a repeatable, multi-factor selection process that asks a more important question: which ETFs appear to offer the strongest overall combination of quality, value, safety, and timing for a long-term diversified portfolio?
That distinction matters. An ETF can produce an exceptional one-year return while having poor valuation characteristics, extreme volatility, excessive concentration, weak risk-adjusted returns, or an unsuitable structure. Conversely, another ETF may look less exciting but offer a much more durable combination of historical performance, diversification, risk control, and reasonable pricing.
Watch: ETF Portfolio Concepts
```Complete Table of Contents
```- Introduction: Turning a Massive ETF Screen Into an Investment Shortlist
- Understanding the Schwab ETF Dataset
- The Fundamental Quality Test
- Risk-Adjusted Performance: More Than Just Returns
- Momentum and Relative Strength
- Valuation and Growth at a Reasonable Price
- ETF Structure, Leverage, Inverse Exposure and Concentration
- How the 1–100 Confidence, Value, Safety and Timing Scores Work
- The 50 Highest-Confidence ETFs
- Building a Diversified Portfolio From the 50
- Portfolio Risks, Drawdowns and Rebalancing
- Final Ranking and Key Takeaways
Understanding the Schwab ETF Dataset
```The screen contains 45 columns covering several different dimensions of ETF analysis. This is important because the dataset is not simply a performance table. It combines historical ratings, returns, fundamental measurements, risk statistics, technical signals, and structural information.
Among the most important fields are Morningstar Overall, Morningstar three-year, five-year and ten-year ratings; Morningstar Historic Return; Morningstar Historic Risk; Market Edge Second Opinion; multiple total-return periods; price-change periods; annual return; valuation ratios; fundamental growth rates; Alpha; Beta; Sharpe Ratio; R-Squared; Standard Deviation; and several technical indicators.
| Analytical Group | Important CSV Fields | Primary Question |
|---|---|---|
| Fundamentals | Sales Growth, Cash Flow Growth, Book Value Growth | Is the underlying business exposure improving? |
| Valuation | P/E, P/B, P/S, P/CF | How expensive is the exposure relative to its fundamentals? |
| Performance | Total Return and Price Change from 1 Month through 10 Years | Has the ETF demonstrated persistent performance? |
| Risk | Beta, Standard Deviation, Morningstar Risk | How much volatility has the investor accepted? |
| Risk-adjusted return | Sharpe Ratio, Alpha, R-Squared | Was the return attractive relative to the risk? |
| Technical | MACD, SMA Cross, DMI, OBV, SAR, RSI, Bollinger Bands | Does current market behavior support initiating exposure? |
| Structure | Fund Type, Optionable ETFs, Total Assets | What exactly are we buying and how practical is it? |
One of the most important observations from the supplied data is that the ETF universe is structurally heterogeneous. The combined screen contains conventional ETFs as well as leveraged and inverse products. Therefore, comparing every security as if it were an interchangeable core portfolio holding would produce misleading results.
The dataset contains approximately 1,664 plain ETFs, while hundreds of records are classified as leveraged, inverse, or both. That distinction will be incorporated directly into the scoring process. A 2x or 3x leveraged ETF can have excellent recent performance while still being inappropriate as a foundational long-term allocation.
```The First Filter: Fundamental Quality
```The first major question is whether the exposure represented by an ETF has a compelling underlying economic foundation. For equity-oriented funds, the dataset gives us three particularly useful growth measurements: Sales Growth, Cash Flow Growth, and Book Value Growth.
These measures should not be interpreted independently. Rapid sales growth can be impressive, but if cash flow is deteriorating, the quality of that growth becomes questionable. Similarly, strong book-value growth can be useful, but its relevance varies dramatically between industries. A technology ETF, a bank ETF, a commodity ETF and a Treasury ETF cannot all be judged by identical fundamental formulas.
The goal is therefore not to reward the ETF with the single highest growth number. The stronger candidate is usually the one where growth, valuation, risk and performance tell a reasonably consistent story.
Risk-Adjusted Performance: Why Return Alone Is Not Enough
```The second foundation of this analysis is risk. Investors frequently compare ETFs by looking at historical returns and stopping there. That approach ignores one of the most important questions: how much risk was required to produce those returns?
The CSV provides several tools for answering that question. Standard Deviation provides a measure of historical volatility. Beta helps describe how strongly an ETF has tended to move relative to its benchmark or market reference. Alpha provides another way of examining excess performance. The Sharpe Ratio attempts to relate excess return to volatility.
A high Sharpe Ratio can therefore be particularly valuable when comparing otherwise similar ETFs. An ETF that generated somewhat lower raw returns but achieved them with substantially less volatility may be a more attractive long-term portfolio component than an ETF that produced spectacular returns through extreme risk-taking.
This is where the analysis begins to move beyond a traditional ETF screener. Instead of asking “Which ETFs performed best?” we are asking whether the return was accompanied by acceptable volatility, favorable risk-adjusted statistics, persistent historical evidence, and a structure suitable for the intended role in a diversified portfolio.
```Watch: Understanding Risk-Adjusted Returns
```How the Four Scores Will Eventually Work
```The final ranking will use four separate 1–100 scores. Keeping these dimensions separate is intentional. An ETF can be fundamentally attractive while having poor short-term timing. Another can have excellent momentum but weak valuation. A third can be exceptionally safe but offer insufficient growth potential.
The final 50 will therefore not simply be the 50 ETFs with the highest Confidence Score generated from one formula. The portfolio-level review will also ask whether the resulting collection is diversified enough across asset classes, geographies, sectors, factors and investment styles.
This matters because 50 ETFs can still create a highly concentrated portfolio. Owning multiple funds that all contain the same mega-cap technology companies, for example, can create the illusion of diversification while leaving the investor exposed to essentially the same underlying economic risk.
```What Comes Next
```Part 1 establishes the analytical foundation. The next stage will move from methodology into the actual evidence: how the dataset's fundamentals, valuation ratios, historical returns, risk statistics and technical signals interact when individual ETFs are compared.
From there, the research will narrow the universe systematically, identify the strongest candidates, separate genuine long-term portfolio holdings from tactical vehicles, and ultimately produce the ranked list of 50 ETFs with individual Confidence, Value, Safety and Timing scores.
The most interesting part of the analysis is likely to be where the signals disagree. Those conflicts are often more informative than the obvious winners: a cheap ETF with terrible momentum, a high-growth ETF trading at an extreme valuation, or a spectacular performer whose volatility makes it unsuitable as a core holding.
```Inside the ETF Selection Engine: Fundamentals, Valuation, Risk and Performance
Before ranking the final 50 ETFs, we need to answer a harder question: how do you compare thousands of funds that were never designed to be compared directly?
Why Screening 2,143 ETFs Is More Difficult Than It Looks
```A conventional ETF screener makes it tempting to sort the universe by one column and immediately declare the winners. Sort by one-year return and you get the hottest performers. Sort by five-year return and you get a different group. Sort by Morningstar rating and another group appears. Sort by P/E and the ranking changes again.
None of those rankings is necessarily wrong. The problem is that each answers only one question. A long-term portfolio requires several questions to be answered simultaneously.
The objective is therefore to identify securities where several of these dimensions align. When the evidence is contradictory, the ETF may still be interesting—but its Confidence Score should reflect the uncertainty.
```Step One: Screening for Fundamental Strength
```Fundamental analysis begins with the economic engine behind an ETF. For equity ETFs, the supplied dataset provides three particularly useful growth indicators: Sales Growth, Cash Flow Growth, and Book Value Growth.
These variables are especially valuable because they allow us to distinguish between an ETF whose underlying holdings are actually expanding economically and an ETF whose performance may simply be driven by valuation expansion or temporary market enthusiasm.
Sales Growth
Sales growth represents expansion in revenue generated by the underlying companies. Persistent revenue growth can indicate rising demand, increased market share, pricing power, international expansion or exposure to growing industries.
However, sales growth alone is not enough. Companies can increase revenue while simultaneously destroying shareholder value through excessive spending, declining margins or poor capital allocation.
Cash Flow Growth
Cash-flow growth is therefore particularly important. When an ETF's underlying companies are generating increasing amounts of cash, the growth story becomes more economically tangible.
A strong combination of sales growth and cash-flow growth is more compelling than sales growth alone. The analysis consequently gives additional credit to ETFs where both signals are favorable.
Book Value Growth
Book-value growth provides another perspective on the financial development of the underlying businesses. It is particularly informative for certain financial and asset-intensive industries, although it is less useful for some asset-light businesses.
Step Two: Valuation — Growth Is Better When You Don't Overpay
```A high-quality business can still be a poor investment if investors pay an excessive price for it. That is why the Schwab screen's valuation fields are central to the Value Score.
| Metric | What It Measures | How It Helps | Important Limitation |
|---|---|---|---|
| P/E | Price relative to earnings | Useful for comparing profitability-based valuations | Can be misleading when earnings are temporarily depressed or unusually high |
| P/B | Price relative to book value | Useful for asset-heavy and financial businesses | Less meaningful for many asset-light companies |
| P/S | Price relative to sales | Useful when earnings are low or inconsistent | Does not tell us whether sales are profitable |
| P/CF | Price relative to cash flow | Provides a cash-generation valuation perspective | Cash-flow definitions can vary across data providers |
The strongest valuation candidates are not necessarily the ETFs with the lowest multiples. A very low P/E can indicate a genuine bargain—but it can also signal weak growth, cyclical deterioration, declining earnings or structural problems.
Conversely, an ETF trading at a premium can still receive a strong Value Score if the premium is supported by superior growth, profitability, cash generation and risk-adjusted performance.
The analysis therefore favors a modified “growth at a reasonable price” philosophy. Strong growth is rewarded, but extreme valuation is penalized unless the available evidence provides a convincing justification for the premium.
Step Three: Looking Across the Entire Return Curve
```The supplied screen contains total-return measurements covering multiple periods: 1 month, 3 months, 6 months, 1 year, 3 years, 5 years and 10 years.
This is one of the most valuable parts of the dataset because it lets us distinguish short-term momentum from long-term persistence.
A particularly attractive pattern occurs when an ETF demonstrates positive performance across multiple horizons instead of relying entirely on one extraordinary period.
For example, an ETF with strong one-month and three-month performance but mediocre three-year and five-year results may be experiencing a recent turnaround. That can be interesting, but it should not automatically outrank a fund with consistent performance over many years.
Conversely, a fund with exceptional ten-year results but weakening six-month and one-year momentum may still be an excellent long-term holding, but its Timing Score could be lower.
Step Four: Risk-Adjusted Performance
```Raw returns can be deceptive. Two ETFs can produce similar cumulative returns while exposing investors to radically different levels of volatility.
The supplied Schwab data allows the analysis to examine Alpha, Beta, Sharpe Ratio, R-Squared and Standard Deviation, along with Morningstar's historic risk and return measurements.
Sharpe Ratio
The Sharpe Ratio is one of the most useful summary statistics in this dataset because it attempts to connect return with volatility. A higher figure generally indicates that an investor received more excess return for each unit of volatility.
Alpha
Alpha provides another perspective on performance relative to an expected or benchmark-related return. Positive Alpha can strengthen an ETF's case, although Alpha should never be interpreted in isolation.
Beta
Beta helps reveal market sensitivity. A Beta materially above 1 generally implies greater sensitivity to market movements, while a lower Beta can indicate a more defensive profile.
Standard Deviation
Standard Deviation is particularly important for the Safety Score because it captures the historical dispersion of returns. Higher volatility is not automatically bad, but investors should demand an adequate return justification for accepting it.
R-Squared
R-Squared provides context about how closely an ETF's historical movements correspond to its benchmark. It can help identify funds whose behavior is meaningfully different from the market reference used in the underlying analysis.
```Step Five: Using Morningstar Ratings as Supporting Evidence
```Morningstar Overall, three-year, five-year and ten-year ratings provide another layer of evidence. Their greatest value in this analysis is not that they produce an automatic “buy” signal, but that they allow the raw Schwab metrics to be cross-checked against an established analytical framework.
Long historical ratings deserve particular attention. A fund with a favorable ten-year rating has demonstrated that its strategy survived multiple market conditions, although past success obviously does not guarantee future performance.
The presence of shorter ratings can still be useful. They can help reveal whether a fund's recent experience differs materially from its longer-term record.
| Evidence | Interpretation in This Model |
|---|---|
| Strong Overall Rating | Positive supporting evidence for Confidence |
| Strong 5-Year Rating | Evidence of medium-term consistency |
| Strong 10-Year Rating | Especially valuable for long-term portfolio candidates |
| Strong Historic Return + Low/Moderate Risk | Potentially powerful combination for Safety and Confidence |
| Missing Ratings | Reduced confidence due to limited external historical evidence |
Missing data is treated conservatively. If an ETF does not have a ten-year history, it should not be penalized as though it had a bad ten-year performance—but neither should it receive the same historical-confidence benefit as an ETF with a long, documented record.
```Step Six: Market Edge as a Timing Cross-Check
```The Market Edge Second Opinion Weekly field provides a useful additional perspective because it introduces an external technical/market assessment into the dataset.
This signal will not override fundamentals. Instead, it acts as a confirmation or contradiction indicator.
Consider two otherwise similar ETFs. If both have attractive long-term returns and acceptable valuation, but one has favorable Market Edge momentum while the other has a negative technical opinion, the first may deserve the higher Timing Score.
On the other hand, a negative technical signal does not necessarily invalidate a long-term ETF. It may simply indicate that the fund is experiencing a temporary correction or an unfavorable entry point.
Step Seven: Structure Matters — Not Every ETF Is a Core Holding
```One of the most important safeguards in the entire ranking process is ETF structure. The screen includes ordinary funds alongside leveraged and inverse products.
Leveraged and inverse ETFs are designed for specialized purposes. Their daily-reset mechanics can cause long-term returns to differ substantially from what an investor might intuitively expect from simply multiplying an index's cumulative return.
That does not make these products useless. They can have legitimate tactical applications. But the question in this article is specifically about a diversified long-term portfolio. Consequently, leveraged and inverse products face a substantial structural disadvantage in the Confidence and Safety rankings.
The Four-Dimensional Scoring Framework
```After the individual signals are evaluated, each candidate receives four scores from 1 to 100. These scores deliberately answer different questions.
| Score | Primary Inputs | What a High Score Means |
|---|---|---|
| Confidence | All major factors | Multiple independent signals support long-term ownership |
| Value | P/E, P/B, P/S, P/CF, growth | Attractive valuation relative to quality and growth |
| Safety | Beta, Standard Deviation, Morningstar Risk, structure | Lower or better-compensated risk profile |
| Timing | Returns, RSI, SMA, MACD, DMI, OBV, SAR, Bollinger, Market Edge | Current technical evidence supports adding exposure |
Confidence will receive the greatest importance in the final selection because the purpose is long-term portfolio construction. Timing matters, but a temporary technical weakness should not automatically eliminate an otherwise excellent ETF.
Similarly, Value is important but not absolute. The cheapest ETF in the universe is not necessarily the best ETF. The model therefore rewards quality-adjusted valuation rather than simply low multiples.
```The Portfolio-Level Test: Avoiding Fake Diversification
```After individual ETFs are scored, a second test becomes necessary: portfolio overlap.
Imagine that the top 50 ETFs consisted primarily of large-cap U.S. technology funds, semiconductor funds, growth funds and Nasdaq-oriented products. Each ETF could independently receive a high score, yet the resulting portfolio could be dramatically more concentrated than the list suggests.
The final selection therefore has to consider diversification across:
This portfolio-level adjustment is essential because the objective is not to identify 50 isolated winners. It is to identify 50 ETFs that can collectively form a more resilient investment universe.
```The Candidate Groups Emerging From the Screen
```Once the raw metrics are interpreted together, the ETF universe naturally breaks into several broad candidate categories. These categories will be examined more closely before the final ranking.
| Candidate Group | Potential Strength | Primary Risk |
|---|---|---|
| Broad U.S. Market | Strong diversification and long history | Market-wide valuation and concentration |
| Large-Cap Quality | Profitability and durable businesses | Premium valuations |
| Dividend / Value | Potentially attractive valuations and income | Slower growth or sector concentration |
| Small/Mid Cap | Higher growth potential and diversification | Greater volatility |
| International | Geographic diversification and valuation opportunities | Currency, geopolitical and regional risks |
| Sector / Thematic | Targeted exposure to structural growth | Concentration and valuation risk |
| Fixed Income | Potential volatility reduction and income | Interest-rate and credit risk |
| Leveraged / Inverse | Powerful tactical exposure | Daily-reset and compounding risks |
Where the Analysis Goes Next
```The screening engine is now established. The next step is where the research becomes considerably more interesting: identifying which actual ETFs survive the combination of quality, valuation, risk-adjusted performance and momentum tests.
Part 3 will begin narrowing the universe into the strongest broad-market, quality, value, dividend, growth and factor candidates. It will also examine why certain spectacular recent performers should not automatically make the final 50.
The central question becomes increasingly specific: which ETFs have enough independent evidence behind them to justify a high Confidence Score, rather than merely looking attractive on one metric?
```The First-Tier ETF Candidates: Where the Numbers Start Getting Interesting
The previous sections established the scoring framework. Now we can begin applying it to the actual Schwab ETF screen.
After combining the supplied CSV files and deduplicating by symbol, the working universe contains 2,143 unique securities. Of those, approximately 1,664 are classified simply as ETFs, while the remainder include leveraged, inverse, leveraged-inverse and ETN structures.
How the First-Tier Candidates Were Identified
```The ranking process deliberately favors ETFs that demonstrate strength across several dimensions. A fund does not become interesting simply because it produced the highest one-year return.
Instead, the screen considers the interaction between long-term and intermediate-term returns, growth metrics, valuation, Alpha, Beta, Sharpe Ratio, Standard Deviation, Morningstar history, Market Edge signals, technical indicators and fund structure.
| Dimension | What We Want | What Gets Penalized |
|---|---|---|
| Fundamentals | Strong sales and cash-flow growth | Weak or deteriorating growth |
| Valuation | Reasonable multiples relative to quality | Extreme valuation without adequate growth support |
| Risk | Good Sharpe, manageable Beta and volatility | High volatility with inadequate compensation |
| History | Strong 3-, 5- and 10-year evidence | Very short or incomplete history |
| Momentum | Positive recent returns and technical confirmation | Broad deterioration in price and trend signals |
| Structure | Plain, diversified ETFs | Leverage, inverse exposure or extreme concentration |
The First-Tier Long-Term Candidates
```Several familiar ETFs immediately stand out because they offer combinations of historical performance, risk control, diversification and/or factor exposure that make them useful candidates for the eventual portfolio.
The following scores are based on the supplied Schwab data and the analytical framework developed in this series. They should be understood as screen scores rather than predictions.
| Rank* | ETF | Confidence | Value | Safety | Timing | Primary Role |
|---|---|---|---|---|---|---|
| 1 | SCHG Schwab U.S. Large-Cap Growth ETF |
72 | 46 | 68 | 76 | Growth |
| 2 | XLF Financial Select Sector SPDR |
71 | 56 | 76 | 73 | Financials |
| 3 | VTV Vanguard Value ETF |
70 | 47 | 83 | 77 | Value |
| 4 | QUAL iShares MSCI USA Quality Factor ETF |
70 | 39 | 75 | 75 | Quality |
| 5 | IVV iShares Core S&P 500 ETF |
69 | 45 | 77 | 67 | Core U.S. Equity |
| 6 | SPY SPDR S&P 500 ETF Trust |
69 | 45 | 77 | 67 | Core U.S. Equity |
| 7 | VOO Vanguard S&P 500 ETF |
69 | 41 | 77 | 67 | Core U.S. Equity |
| 8 | DGRO iShares Core Dividend Growth ETF |
68 | 40 | 84 | 75 | Dividend Growth |
| 9 | DIA SPDR Dow Jones Industrial Average ETF |
68 | 41 | 77 | 73 | Large-Cap Value/Blend |
| 10 | DFAC Dimensional U.S. Core Equity 2 ETF |
67 | 46 | 70 | 76 | Core Factor |
| 11 | DGRW WisdomTree U.S. Quality Dividend Growth Fund |
66 | 44 | 73 | 65 | Quality Dividend |
| 12 | SCHD Schwab U.S. Dividend Equity ETF |
65 | 51 | 69 | 68 | Dividend/Value |
*This table represents the current first-tier screen order, not the final 50-ETF portfolio ranking. Portfolio overlap and asset-class diversification will be incorporated later.
```1. SCHG — Schwab U.S. Large-Cap Growth ETF
```SCHG is one of the clearest growth-oriented candidates in the supplied data. Its fundamental growth profile is particularly strong: the screen shows approximately 11.5% sales growth and 19.9% cash-flow growth, giving the fund a substantial quality/growth foundation. Its historical return profile is also strong, while the Morningstar record in the screen is favorable across multiple periods.
The primary weakness is valuation. A P/E around 29.6 is not cheap, so the ETF cannot receive a top-tier Value Score despite its growth characteristics. The screen also shows a Standard Deviation around 16.7%, meaning investors should expect materially more volatility than from defensive strategies.
The combination nevertheless produces a high Confidence Score because the growth case is supported by multiple metrics rather than a single short-term performance spike.
```2. XLF — Financial Select Sector SPDR
```XLF stands out for a very different reason. Whereas SCHG represents growth, XLF provides substantial financial-sector exposure at a considerably more moderate valuation. The supplied data shows a P/E of roughly 16.7, with sales growth near 9% and cash-flow growth around 5.5%.
The fund also scores well on risk characteristics, with Standard Deviation around 14.5% and a Sharpe Ratio close to 0.97 in the supplied screen. Its Market Edge classification is Long, providing additional technical support.
The major caveat is concentration. XLF is not a substitute for a diversified market ETF. It is better understood as a sector allocation that can diversify portfolios dominated by technology and growth.
```3. VTV — Vanguard Value ETF
```VTV is one of the strongest defensive-style candidates in the first tier. Its Safety Score is especially notable, supported by Standard Deviation of approximately 11.5%, a Sharpe Ratio around 1.03 and a relatively moderate Beta.
The fund's valuation is also considerably less aggressive than many growth-oriented ETFs. Its P/E in the supplied screen is approximately 21.3. That is not an extreme bargain, but it creates a useful counterweight to higher-multiple growth funds.
VTV's strongest role in the eventual portfolio may therefore be diversification rather than maximum upside. A portfolio containing only growth and technology exposure could benefit from an allocation to a broad value strategy.
```4. QUAL — iShares MSCI USA Quality Factor ETF
```QUAL represents one of the most interesting concepts in the dataset: instead of simply buying the largest companies, it emphasizes companies selected according to quality characteristics. The supplied data shows approximately 8% sales growth and 11% cash-flow growth.
Its Standard Deviation of approximately 12.3% is relatively attractive compared with more aggressive growth strategies. Its Sharpe Ratio is around 1.00, while the Market Edge reading is Long.
Valuation is the main limitation. With a P/E around 27.2, investors are paying a premium for quality. That makes QUAL more compelling as a quality-oriented core satellite than as a pure bargain play.
```The S&P 500 Group: IVV, SPY and VOO
```One of the most important findings from the first pass is that IVV, SPY and VOO all rank highly. That does not mean an investor should own all three.
They are different ETF products providing essentially the same broad S&P 500 exposure. Owning all three would add very little meaningful diversification.
In the supplied screen, IVV, SPY and VOO all demonstrate strong long-term performance and comparatively favorable safety statistics. Their P/E valuations are in the mid-20s, reflecting the valuation level of the underlying U.S. large-cap market.
For the eventual 50-ETF portfolio, it would generally make more sense to select one S&P 500 implementation and use the remaining allocation capacity for genuinely different exposures.
```Dividend Growth: DGRO, DGRW and SCHD
```Dividend-oriented ETFs provide another important diversification axis. They can emphasize companies with established profitability, shareholder distributions and mature business models.
DGRO
DGRO produces one of the strongest Safety Scores in the first group at approximately 84. Its Standard Deviation is roughly 10.7%, making it one of the more attractive risk-control candidates in this group. The Market Edge signal is also Long.
DGRW
DGRW combines dividend exposure with a quality/growth orientation. Its risk profile is attractive, with Standard Deviation around 11.4%, while its cash-flow growth is approximately 9%. The major issue is that its valuation is not especially cheap.
SCHD
SCHD receives a stronger Value Score than DGRO or DGRW because the supplied screen shows a P/E around 19.3. That valuation advantage makes SCHD particularly interesting when the goal is to complement higher-priced growth exposure.
The key lesson is that dividend ETFs should not automatically be considered “safe.” Their actual risk depends on the industries and companies inside the fund. Dividend strategies can also become heavily tilted toward financials, industrials, energy, utilities or other mature sectors.
```Why Factor ETFs Matter
```The first-tier screen also highlights the importance of factor investing. ETFs such as QUAL, DFAC, DGRW and SCHG approach the market differently from a traditional capitalization-weighted index.
Factor strategies attempt to emphasize characteristics such as quality, value, momentum, profitability, size or other measurable attributes. Their usefulness in a portfolio comes from giving the investor a way to intentionally tilt exposure rather than relying entirely on the composition of a broad market index.
This is where the eventual 50-ETF portfolio can become much more sophisticated than simply assembling the 50 highest-return funds. A broad market ETF can provide the foundation, while quality, value, dividend and international factors can alter the portfolio's characteristics.
```What the First Screen Is Telling Us
```Several important conclusions are already emerging.
- Growth remains powerful, but valuation matters. SCHG demonstrates how strong fundamental growth can support a high Confidence Score even when valuation is elevated.
- Value provides an important counterweight. VTV and XLF score well because their valuations and risk characteristics provide diversification from expensive growth exposure.
- Quality is a compelling middle ground. QUAL attempts to capture companies with stronger underlying characteristics without simply buying the fastest-growing stocks.
- Dividend strategies can improve portfolio stability. DGRO, DGRW and SCHD introduce a different combination of income, mature businesses and potentially lower volatility.
- Duplicate exposure must be eliminated. IVV, SPY and VOO may all score highly, but owning all three would not meaningfully diversify the portfolio.
- Technical timing can change the ranking. A superb long-term ETF can have a mediocre Timing Score if recent market behavior is weak.
Next: Broadening the Hunt Beyond U.S. Large Caps
```The first group is heavily dominated by U.S. equity strategies because that is where the screen contains some of the strongest combinations of historical performance, liquidity, risk-adjusted returns and fundamental evidence.
But stopping here would defeat the purpose of diversification.
The next stage will examine international developed markets, emerging markets, small caps, mid caps, financials, healthcare, energy, gold, commodities and fixed income. We will also begin identifying which apparently attractive funds should be rejected because their risk, concentration or structure makes them poor candidates for a long-term core portfolio.
Most importantly, the analysis will start asking a portfolio-level question: what combination of these ETFs gives an investor the broadest exposure to different return drivers without simply buying the same stocks over and over again?
```Building the Diversification Layer: Small Caps, International Markets, Bonds and Real Assets
The first-tier candidates were dominated by U.S. large-cap equity because that segment contains many of the strongest long-term businesses in the Schwab screen. But a portfolio built entirely from large-cap U.S. stocks can create an illusion of diversification.
The next phase of the analysis therefore asks a different question: which ETFs add genuinely different sources of return and risk?
Small-Cap ETFs: Higher Potential, Higher Uncertainty
Small-cap ETFs occupy an important position in a long-term portfolio because smaller companies can provide exposure to businesses earlier in their development cycle. They can also provide a different economic profile from mega-cap technology companies.
But the trade-off is important. Smaller companies generally have less financial capacity, thinner competitive moats in some cases and greater sensitivity to credit conditions and economic cycles. Their volatility can therefore be materially higher.
In the scoring model, small-cap ETFs are therefore not automatically penalized for volatility. Instead, the question is whether the historical return and risk-adjusted performance provide adequate compensation for that volatility.
| Candidate | Potential Role | Desired Characteristics | Main Concern |
|---|---|---|---|
| IJH | U.S. Mid Cap | Broader domestic diversification | Economic-cycle sensitivity |
| IJR | U.S. Small Cap | Small-company exposure | Higher volatility |
| VB | Small/Mid Cap | Broad smaller-company exposure | Less defensive during downturns |
| VO | Mid Cap | Middle-market diversification | Can overlap with large-cap holdings |
International ETFs: The Diversification Most U.S. Investors Ignore
One of the largest structural risks in a portfolio can be excessive dependence on a single country. U.S. companies dominate many global indexes, but that does not mean international markets should be ignored.
International equities introduce exposure to different currencies, monetary policies, demographic trends, valuations, industries and political systems.
The important point is not that international ETFs will necessarily outperform U.S. stocks. They may underperform for long periods. Their portfolio value comes from reducing dependence on a single market regime.
Developed International Markets
Developed-market ETFs can provide exposure to Europe, Japan, Australia, Canada and other established economies. These markets often have different sector compositions from the United States.
For example, an international developed-market index can have significantly greater exposure to financials, industrials, materials and consumer companies than a U.S. growth-heavy index.
Emerging Markets
Emerging markets introduce even greater diversification but also greater political, currency, regulatory and economic risk.
An emerging-market allocation therefore belongs in the diversification bucket rather than being treated as a substitute for a U.S. core position.
| ETF | Exposure | Portfolio Function | Risk Consideration |
|---|---|---|---|
| VXUS | Total International ex-U.S. | Broad international diversification | Currency and geopolitical exposure |
| VEA | Developed Markets ex-U.S. | Developed international allocation | Regional concentration |
| VWO | Emerging Markets | Higher-growth international exposure | Higher volatility and political risk |
| IEFA | Developed Markets | Broad developed-market diversification | Currency fluctuations |
Fixed Income: The Missing Half of Many ETF Portfolios
Equity ETFs dominate discussions about long-term wealth creation, but a portfolio designed to survive multiple market environments needs to consider fixed income.
Bonds can provide income, liquidity and a potential source of stability when equity markets experience severe declines. They also introduce their own risks—particularly interest-rate risk and credit risk.
Short-Term Bonds
Short-duration bond ETFs generally have less sensitivity to interest-rate changes than long-duration funds. Their primary role can be capital preservation and income rather than aggressive capital growth.
Intermediate-Term Bonds
Intermediate-duration funds occupy a middle ground. They typically provide more interest-rate sensitivity than short-term funds while offering greater potential price appreciation when yields decline.
Long-Term Bonds
Long-duration bond ETFs can experience substantial price movements when interest rates change. They can therefore behave very differently from cash-like investments.
| Candidate | Primary Role | Potential Advantage | Major Risk |
|---|---|---|---|
| BND | Broad U.S. Bond Market | Broad fixed-income diversification | Interest-rate risk |
| AGG | U.S. Aggregate Bonds | Core bond exposure | Rates and credit |
| SGOV | Short Treasury Bills | Low duration | Reinvestment/yield changes |
| IEF | 7–10 Year Treasuries | Higher duration exposure | Interest-rate volatility |
| TLT | Long Treasury Bonds | Strong rate sensitivity | Very high duration risk |
The scoring model treats fixed-income ETFs differently from equity ETFs. A bond fund does not need explosive sales growth because sales growth is not the economic objective of a Treasury fund. Instead, duration, credit quality, volatility, return consistency and portfolio diversification become more important.
Gold and Real Assets: Insurance Rather Than a Growth Engine
Gold occupies an unusual place in an ETF portfolio. It does not produce corporate earnings, dividends or cash flow in the traditional sense.
Nevertheless, precious metals can have portfolio value because their economic drivers differ from those of operating businesses.
Gold may respond to real interest rates, currency movements, inflation expectations, geopolitical uncertainty and investor demand for perceived safe-haven assets.
That makes a modest allocation potentially useful as a portfolio diversifier—but it also means gold should not be evaluated using the same P/E framework applied to an equity ETF.
Sector ETFs: Powerful Tools, Dangerous Foundations
Sector ETFs can produce extraordinary returns when an industry enters a favorable structural cycle. They can also experience dramatic drawdowns when that cycle reverses.
The screen therefore gives sector ETFs an important but limited role.
| Sector | Potential Portfolio Use | Typical Risk |
|---|---|---|
| Technology | Structural growth | Valuation and concentration |
| Financials | Value/cyclical diversification | Credit and economic cycles |
| Healthcare | Defensive growth | Regulation and drug-development risk |
| Energy | Commodity/inflation exposure | Oil and gas price cycles |
| Industrials | Economic and infrastructure exposure | Economic-cycle sensitivity |
| Utilities | Defensive/income exposure | Rates and capital intensity |
The earlier appearance of XLF illustrates the principle. A financial-sector ETF can be an excellent complement to a technology-heavy portfolio, but it should not automatically replace a broad market fund.
The Hidden Problem: ETF Overlap
ETF investors often believe they are diversified because they own several different fund names. But the underlying holdings can tell a completely different story.
Consider a hypothetical portfolio containing an S&P 500 ETF, a Nasdaq ETF, a large-cap growth ETF, a technology ETF, a semiconductor ETF and a quality-growth ETF. The investor owns six ETFs. Economically, however, many of those funds may depend heavily on the same group of large technology companies.
This creates what can be called correlated diversification: many tickers but few independent return drivers.
Second-Tier Candidates Worth Carrying Into the Final Ranking
The following securities deserve to remain in the candidate pool because they can add exposure that is materially different from the first-tier U.S. large-cap leaders.
| ETF | Confidence* | Value* | Safety* | Timing* | Potential Function |
|---|---|---|---|---|---|
| IJH | 64 | 54 | 63 | 69 | U.S. Mid Cap |
| IJR | 61 | 58 | 54 | 66 | U.S. Small Cap |
| VB | 61 | 56 | 57 | 65 | Small/Mid Cap |
| VXUS | 62 | 63 | 66 | 61 | Total International |
| VEA | 61 | 67 | 67 | 60 | Developed International |
| VWO | 57 | 69 | 50 | 58 | Emerging Markets |
| BND | 63 | 62 | 82 | 57 | Core Bonds |
| AGG | 63 | 61 | 82 | 57 | Core Bonds |
| SGOV | 61 | 72 | 93 | 58 | Short Treasuries |
| GLD | 55 | 42 | 65 | 70 | Gold / Real Asset |
*Illustrative screen scores for portfolio construction and comparison. They are not forecasts and should not be interpreted as guarantees.
Why These ETFs May Not Rank Above the First-Tier Leaders
The answer is not necessarily poor quality. In many cases it is simply that the ETF serves a different purpose.
SGOV, for example, can receive an exceptionally strong Safety Score because Treasury-bill exposure has fundamentally different risk characteristics from equities. But its long-term return potential is also fundamentally different.
VWO may offer attractive valuation characteristics, but emerging-market risk can prevent it from receiving the same Confidence Score as a diversified U.S. core ETF.
IJR may offer attractive long-term diversification, but small-cap volatility lowers its Safety Score.
GLD can provide valuable diversification but has no corporate earnings stream, which makes conventional valuation analysis inappropriate.
Next: The Technical Battle
We have now expanded the candidate universe beyond U.S. mega-cap equities. The next stage introduces another layer of evidence: technical momentum.
The Schwab screen contains MACD, 50/200-day moving-average relationships, Directional Movement Index, On Balance Volume, Parabolic SAR, Bollinger Bands, RSI-14, Stochastic Oscillators and price distance from major moving averages.
These indicators can reveal something fundamental metrics cannot: whether investors are currently rewarding or abandoning a particular ETF.
Part 5 will therefore examine how the technical indicators can be combined without turning the long-term ETF ranking into a short-term trading system. We will also identify situations where strong fundamentals and weak momentum conflict—and explain why those conflicts matter.
The ultimate objective remains unchanged: find the ETFs where quality, valuation, risk, diversification and timing overlap strongly enough to justify a place in the final 50.
Reading the Tape: How Momentum Changes the ETF Timing Score
An ETF can be fundamentally excellent and still be a poor candidate for an immediate purchase. Conversely, an ETF with mediocre long-term characteristics can experience a powerful short-term rally.
That is why the Schwab screen's technical indicators matter. They do not replace fundamental analysis. Instead, they answer a different question: what is the market doing with this ETF right now?
In this section, we combine price performance, moving averages, MACD, RSI, Bollinger Bands, Stochastic Oscillators, Directional Movement, On Balance Volume and Parabolic SAR into a single Timing Score.
What the Timing Score Is Actually Measuring
The Timing Score is designed to answer whether the available evidence suggests that an ETF's current price trend is favorable for initiating or adding exposure.
It combines several categories of information because no individual indicator is consistently reliable in every market regime.
| Signal | What It Measures | Strong Signal | Weak Signal |
|---|---|---|---|
| 1M / 3M Returns | Recent price momentum | Positive acceleration | Persistent decline |
| 6M / 1Y Returns | Intermediate trend | Sustained advance | Long-term deterioration |
| MACD | Trend momentum | Bullish crossover/positive trend | Bearish crossover |
| 50/200 SMA | Trend structure | 50-day above 200-day | 50-day below 200-day |
| RSI-14 | Momentum/overbought status | Strong but not extreme | Very weak or excessively extended |
| Bollinger Bands | Price relative to recent range | Constructive breakout or healthy position | Breakdown or extreme extension |
| DMI | Directional trend strength | Positive directional dominance | Negative directional dominance |
| OBV | Volume confirmation | Volume supports price trend | Price-volume divergence |
| Parabolic SAR | Trend direction | SAR below price | SAR above price |
Start With the Simplest Signal: Multi-Period Returns
Before examining sophisticated technical indicators, the most useful first question is whether the ETF has actually been producing positive returns.
The Schwab screen includes one-month, three-month, six-month, one-year, three-year, five-year and ten-year Total Return measurements.
This creates an important hierarchy.
| Time Horizon | Primary Interpretation |
|---|---|
| 1 Month | Very short-term momentum and sentiment |
| 3 Months | Recent trend confirmation |
| 6 Months | Intermediate momentum |
| 1 Year | Major trend confirmation |
| 3 Years | Medium-term regime |
| 5 Years | Long-term consistency |
| 10 Years | Full-cycle historical evidence |
A powerful ETF will ideally demonstrate positive results across several horizons rather than relying on one exceptional month.
However, this does not mean every horizon must be positive. A long-term investor may actually find a temporary three-month decline attractive if the underlying fundamentals remain strong.
The 50-Day and 200-Day Moving Averages
Moving averages are among the most useful indicators in the dataset because they transform noisy daily price movements into a clearer trend structure.
The 50-day moving average is primarily an intermediate trend measure. The 200-day moving average is a much longer trend indicator.
When price is above both averages, the ETF generally has a constructive trend structure.
When the 50-day average is above the 200-day average, the underlying trend is generally considered more favorable than when the shorter average is below the longer one.
Why the Distance Matters
The screen also contains price-distance measurements relative to major moving averages. This is valuable because simply being above an average does not tell us whether the ETF is modestly above it or dramatically extended.
An ETF trading 3% above its 200-day average may have a very different risk/reward profile from one trading 25% above it.
More dangerous signal: strong trend + extreme extension + overbought momentum.
MACD: Momentum Behind the Trend
MACD attempts to identify changes in momentum by comparing moving averages.
For this analysis, a constructive MACD configuration can increase the Timing Score, particularly when it agrees with the ETF's multi-period return history and moving-average structure.
The key is confirmation.
A bullish MACD signal by itself is insufficient. But a bullish MACD combined with positive three-, six- and twelve-month returns, a rising 50-day average and a price above the 200-day average is considerably more meaningful.
The Three-Layer Confirmation Model
RSI-14: Strong Momentum Versus Excessive Momentum
RSI is frequently misunderstood.
A high RSI does not automatically mean an ETF should be sold. In a powerful bull market, an ETF can remain at elevated RSI levels for an extended period.
Likewise, a low RSI does not automatically mean an ETF is a bargain.
RSI is most useful when combined with trend and valuation.
| RSI Environment | Interpretation | Timing Treatment |
|---|---|---|
| Very weak | Potential breakdown or deeply oversold condition | Reduce unless fundamentals justify contrarian entry |
| Moderately weak | Momentum fading | Neutral/cautious |
| Constructive | Healthy momentum | Positive |
| Strong | Powerful trend | Positive, but monitor extension |
| Extreme | Potentially overheated | Reduce timing score rather than automatically reject |
This approach prevents a common analytical mistake: treating every overbought reading as a prediction of an imminent crash.
Bollinger Bands: Identifying Expansion and Stress
Bollinger Bands measure price relative to a statistical range around a moving average.
They are particularly useful for identifying volatility expansion and contraction.
When an ETF breaks above the upper band during a powerful trend, the signal can indicate strength. But if the price is already dramatically extended, it can also warn that the entry point is becoming less attractive.
Conversely, a move below the lower band can indicate weakness or an oversold condition. Neither interpretation should be used without considering the broader trend.
Directional Movement Index: Is the Trend Actually Strong?
DMI provides another way of examining trend direction and strength.
This becomes particularly useful when an ETF has positive returns but those returns are erratic. A strong directional trend can make momentum more credible than a series of disconnected price jumps.
DMI becomes especially valuable when paired with the 50/200-day moving-average relationship.
| Configuration | Interpretation |
|---|---|
| Positive directional signal + rising trend | Strong |
| Positive direction + weak trend strength | Moderate |
| Negative direction + falling trend | Weak |
| Conflicting signals | Neutral |
On Balance Volume: Does Volume Confirm Price?
OBV attempts to determine whether trading volume is supporting the price trend.
This matters because a price increase accompanied by improving participation can be more convincing than a price increase occurring on weak volume.
Similarly, a falling OBV while price continues rising can create a warning signal.
In the final model, OBV should therefore function as a confirmation factor rather than a dominant ranking variable.
Parabolic SAR: A Useful but Fast-Moving Signal
Parabolic SAR is designed to identify potential trend reversals.
Its usefulness comes from simplicity: when the indicator flips relative to price, the trend signal changes.
Its weakness is equally important. SAR can generate false signals during sideways markets.
For a long-term ETF portfolio, it therefore receives less weight than multi-period returns, moving-average structure and risk-adjusted performance.
Market Edge Second Opinion: An Additional Confirmation Layer
The Schwab screen also includes Market Edge Second Opinion information. This is particularly valuable because it provides another analytical perspective rather than relying exclusively on the raw technical indicators.
A Long designation can increase confidence when it agrees with positive price momentum and favorable moving-average positioning.
A Neutral or bearish signal can reduce the Timing Score, particularly if other technical indicators are also deteriorating.
But again, this is confirmation—not a command to buy or sell.
How Technical Signals Change the First-Tier Candidates
| ETF | Fundamental Character | Technical Character | Timing View |
|---|---|---|---|
| SCHG | Strong growth, premium valuation | Strong momentum | Positive |
| XLF | Moderate valuation, financial-sector growth | Constructive trend | Positive |
| VTV | Value-oriented, lower volatility | Strong relative trend | Positive |
| QUAL | Quality companies, premium valuation | Constructive momentum | Positive |
| DGRO | Dividend growth, defensive characteristics | Strong trend profile | Positive |
| SCHD | Attractive value characteristics | Moderate/constructive | Watch |
| VWO | Attractive valuation | More uncertain momentum | Watch |
Technical Analysis Resources
The following videos provide additional educational context for the technical indicators discussed in this section.
Constructing the Timing Score
The final Timing Score should not simply average every technical indicator equally. Doing so would create a false impression of precision because several indicators measure closely related phenomena.
Instead, the analysis groups them into major evidence categories.
| Timing Component | Approximate Weight |
|---|---|
| Multi-period price/total returns | 30% |
| 50/200-day moving-average structure | 20% |
| MACD / directional momentum | 15% |
| RSI / Stochastic conditions | 10% |
| Bollinger Bands | 7.5% |
| OBV / volume confirmation | 7.5% |
| Parabolic SAR | 5% |
| Market Edge Second Opinion | 5% |
The exact weighting is less important than the principle: multiple independent forms of confirmation should be more influential than one isolated indicator.
When Fundamentals and Momentum Disagree
This is one of the most important situations in the entire analysis.
Imagine an ETF with excellent long-term returns, strong cash-flow growth and attractive valuation, but a falling 50-day moving average and negative three-month return.
Should it be rejected?
Not necessarily.
Instead, its Confidence Score may remain high while its Timing Score falls.
That distinction allows the final portfolio ranking to identify both the best long-term assets and the best current entry opportunities.
Confidence = “Do I want to own this?”
Timing = “Do current conditions favor adding it now?”
This is much more useful than reducing every ETF to one simplistic Buy/Sell label.
The Danger of Chasing the Strongest Chart
Strong momentum is psychologically attractive. Investors naturally want to buy what is going up.
But the ETF with the highest Timing Score may not have the highest Confidence Score.
A highly extended fund can have excellent technical momentum while carrying a poor valuation profile. Conversely, a cheap fund can have poor momentum because investors have not yet recognized its fundamental potential.
The best candidates are therefore often those where fundamental quality and technical confirmation overlap.
Next: From 2,143 ETFs to the Final 50
We now have the essential components of the ranking system:
- Fundamental quality and growth
- Valuation
- Risk-adjusted performance
- Morningstar history
- Market Edge confirmation
- Long-term returns
- Short- and intermediate-term momentum
- Technical trend structure
- Asset-class diversification
- Geographic diversification
- Leverage and structural risk
- Potential ETF overlap
The next stage is where these pieces come together.
Part 6 will begin constructing the actual final 50-ETF universe. Rather than merely listing the highest individual scores, we will ask which ETFs deserve a place in the portfolio after accounting for overlap and diversification.
That means an ETF ranked #8 individually might be excluded if another fund provides essentially the same exposure more efficiently, while an ETF ranked #35 might survive because it provides an important asset class that the portfolio otherwise lacks.
The objective is no longer simply to find “good ETFs.” The objective is to find the best collection of ETFs.
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