IEF vs VGLT ETF Comparison
Compare IEF and VGLT across fund costs, diversification, holdings, performance, income, risk and current AlgovestIQ evidence.
What is the main difference between IEF and VGLT?
IEF is iShares 7-10 Year Treasury Bond ETF, while VGLT is Vanguard Long-Term Treasury ETF. IEF is tied to Fixed Income; VGLT is tied to Government Bond. VGLT is broader by holdings count, with 69 positions versus 16 for IEF. VGLT has the lower expense ratio in the current fund profile.
| Metric | IEF | VGLT | Type |
|---|---|---|---|
| Expense ratio | 0.15% | 0.03% | Fund |
| Assets under management | $42.0B | $14.8B | Fund |
| Holdings | 16 | 69 | Fund |
| Average volume | 10,564,206 | 2,662,683 | Fund |
| Underlying exposure | Fixed Income | Government Bond | Fund |
| Annualized volatility | 4.9% | 8.7% | Risk |
| Max drawdown | -6% | -10.3% | Risk |
| Beta | 0.10 | 0.16 | Risk |
| Sharpe ratio | -1.57 | -0.97 | Risk |
| Sortino ratio | -2.43 | -1.54 | Risk |
| AIQ Score | 56/100 | 48/100 | AlgovestIQ |
| AIQ Edge Score | 6/10 | 3/10 | AlgovestIQ |
| Momentum | 33/100 | 41/100 | AlgovestIQ |
| Risk Resilience | 89/100 | 56/100 | AlgovestIQ |
AlgovestIQ AIQ Comparison
iShares 7-10 Year Treasury Bond ETF vs Vanguard Long-Term Treasury ETF
IEF leads
IEF leads by 8 AIQ points, primarily on Risk Resilience and Value, but the lead has narrowed from 12 points over 30 sessions.
Competitive: 3 of 4 evidence groups support IEF, and its lead is narrowing.
iShares 7-10 Year Treasury Bond ETF
Vanguard Long-Term Treasury ETF
The Algovestiq AIQ Score currently favors IEF over VGLT, 56 versus 48 as of Sep 5, 2026. IEF's advantage is driven primarily by stronger risk resilience and value, while VGLT holds the stronger momentum profile. IEF also shows the stronger technical structure relative to its 50-day moving average. 3 of 4 covered evidence groups favor IEF today, and the comparison is rated Competitive on stability: the leader's advantage has been narrowing. IEF lead: Weakening — the AIQ differential moved from 12 to 8 points over 30 sessions.
Compare iShares 7-10 Year Treasury Bond ETF and Vanguard Long-Term Treasury ETF across performance, expense ratio, dividend yield, drawdown, volatility and the Algovestiq AIQ Score.
Compare IEF and VGLT against another ticker
Open a multi-ticker workspace without changing this focused pair page.
AIQ Factor Divergence
Where the two separate, on the four dimensions behind the AIQ Score. Bars read outward from a shared zero: further from the centre is a wider gap.
- Risk Resilience15%89 vs 56IEF +33
- Value30%45 vs 36IEF +9
- Momentum25%33 vs 41VGLT +8
- Quality30%70 vs 63IEF +7
3 of 4 evidence groups favor IEF. IEF’s edge is concentrated in risk resilience and value; VGLT keeps a meaningful momentum edge.
What changed since the last close
Latest scored session 2026-09-03, compared against the prior scored session 2026-09-02.
Largest factor move: Momentum +4
No new signals fired.
Largest factor move: Momentum +4
No new signals fired.
IEF's lead was unchanged in the latest snapshot.
Deeper signal detail for each name lives on its own signals page — IEF and VGLT both carry a full feed there.
The central trade-off
IEF (iShares 7-10 Year Treasury Bond ETF): the stronger current systematic profile, led by risk resilience and value.
VGLT (Vanguard Long-Term Treasury ETF): the counter-case, on momentum.
Which one fits your objective
The same two names rank differently depending on what you are optimizing for. All six reads are shown at once — none of them is hidden behind a toggle.
Balanced
IEFIEF on the overall AIQ Score, which weights Quality and Value at 30% each.
Growth
EvenGrowth figures are not covered for both names.
Value
IEFIEF on the peer-relative Value factor, by 9 points.
Momentum
VGLTVGLT on the Momentum factor, by 8 points.
Lower downside
IEFIEF on Risk Resilience, by 33 points.
Analyst upside
EvenAnalyst targets are level or not covered for both names.
Fund facts, side by side
Two funds tracking overlapping universes are separated by cost and risk far more than by holdings. Those lead here.
| Measure | IEF | VGLT | Why it matters |
|---|---|---|---|
| Expense ratio | 0.15% | 0.03% | Lower is better — it compounds against you every year you hold. |
| Assets under management | $42.0B | $14.8B | Larger funds generally carry tighter spreads. |
| Holdings | 16 | 69 | More holdings means broader diversification, not better returns. |
| Average volume | 10,564,206 | 2,662,683 | Liquidity — matters most if you trade size. |
| Annualized volatility | 4.9% | 8.7% | Lower is a steadier ride for the same exposure. |
| Max drawdown | -6% | -10.3% | The worst peak-to-trough loss on record for the fund. |
| Sharpe ratio | -1.57 | -0.97 | Return per unit of risk. Higher is better. |
| Beta | 0.10 | 0.16 | Sensitivity to the broad market. Neither direction is better — it depends on the role in your portfolio. |
Where the exposure actually sits
Sector exposure for each fund, ordered by the size of the difference.
Weighted holdings overlap is not available for this pair. Sector exposure above is a related but different measure — it says how much of each fund sits in the same parts of the market, not how much of the same securities they hold.
ETF comparison questions
Short answers to the fund-specific questions behind this comparison.
Which ETF is more diversified, IEF or VGLT?
VGLT currently has more reported holdings, with 69 positions versus 16.
Which has the lower expense ratio?
VGLT has the lower reported expense ratio in the current fund profile.
Which ETF has the higher distribution yield?
The current dataset does not show a higher-yield winner.
Which ETF has been more volatile?
VGLT has the higher annualized volatility in the current risk snapshot.
Which ETF has had the smaller drawdown?
IEF has the less severe max drawdown in the current risk snapshot.
Which ETF has the stronger current AlgovestIQ evidence?
IEF currently leads on supporting AlgovestIQ evidence, 56 to 48.
AIQ Agreement Matrix
3 of 4 covered evidence groups favor IEF. A wide gap backed by one group is a weaker case than a narrow gap backed by five.
| Evidence group | Favors | Reading |
|---|---|---|
| AIQ Score | IEF | 56 vs 48 |
| Fundamentals | Not covered | Not covered |
| Valuation | IEF | Value 45 vs 36 |
| Technicals | Even | Price vs 50-day -1.2% vs -1.4%; vs 200-day -3% vs -4.4% |
| Risk Resilience | IEF | Risk Resilience 89 vs 56 |
| Analyst expectations | Not covered | Not covered |
✓ agrees with the overall verdict · ✕ points the other way. Groups marked “not covered” lack data on one or both of IEF and VGLT and are excluded from the count.
AIQ Decision Stability
The two are close enough that your objective, not the score, should decide.
- The AIQ gap is moderate at 8 points.
- The leader's advantage has been narrowing. (argues the conclusion is provisional)
- The lead has been steady session to session. (supports the conclusion holding)
Stability combines the score gap, how broadly the evidence agrees, how steady the lead has been across daily snapshots, the current signal state on both names, and analyst dispersion on IEF.
How the comparison changed
120 daily snapshots · Apr 22 – Sep 3IEF lead: Weakening — the AIQ differential moved from 12 to 8 points over 30 sessions.
- Today
- IEF +8
- 56 vs 48
- 7 sessions ago
- IEF +9
- 59 vs 50
- 30 sessions ago
- IEF +12
- 59 vs 47
- 90 sessions ago
- IEF +10
- 64 vs 54
The lead has not changed hands in this window.
AIQ Signal Divergence
Only the signals that bear on the head-to-head. A conflicted name is carrying bullish and bearish rules at the same time — the technical evidence is not pointing one way.
0 bullish / 4 bearish / 2 neutral
- Death Cross Active — bearish, trend, long horizon (1.87%)
- Bollinger Band Squeeze — neutral, volatility, short horizon
- 52-Week Low Proximity — bearish, risk, long horizon (0.3%)
1 bullish / 3 bearish / 2 neutral, conflicted
- Death Cross Active — bearish, trend, long horizon (3.02%)
- Bollinger Band Squeeze — neutral, volatility, short horizon
- 52-Week Low Proximity — bearish, risk, long horizon (0.9%)
VGLT is conflicted, so the timing case there is weaker than the score alone suggests.
Price vs model alignment
Whether the latest session's price move confirms what the model did over the same session, or contradicts it.
Neither the price nor the AIQ Score moved enough in the latest session to confirm or contradict the other (price -0.03%, AIQ +1 points).
Price and the AIQ Score both moved up over the latest session (price +0.15%, AIQ +1 points).
What would flip this result
A state, not a forecast. These are the specific, observable changes that would reverse the verdict — not a price prediction.
- 1VGLT closes the Risk Resilience gap — currently 33 points behind, the largest single contributor to IEF's edge.
- 2VGLT's Death Cross Active resolves — a bearish trend rule currently active against it.
- 3IEF starts generating bearish momentum or trend signals.
- 4The narrowing continues — the lead has already given back 4 points over 30 sessions, and a further 8-point move would eliminate IEF's advantage entirely.
The full evidence
Every number behind the verdict. The leader is called above each group so you are not left to solve it from the table.
Technicals
Split| Metric | IEF | VGLT |
|---|---|---|
| RSI (14) | 39.4 | 49.7 |
| ADX (14) | 13.5 | 15.5 |
| Price vs 50-day | -1.2% | -1.4% |
| Price vs 200-day | -3% | -4.4% |
| Volatility (1M, annualized) | 5.2% | 9.6% |
Risk
IEF is the more resilient| Metric | IEF | VGLT |
|---|---|---|
| Beta | 0.1 | 0.16 |
| Sharpe ratio | -1.57 | -0.97 |
| Sortino ratio | -2.43 | -1.54 |
| Max drawdown | -6% | -10.3% |
| Current drawdown | -5.8% | -9.7% |
| Annualized volatility | 4.9% | 8.7% |
| Value at risk (95%) | -0.5% | -0.9% |
Straight answers
Each answer is regenerated from the current snapshot, not written once and left to age.
Which is better, IEF or VGLT?
On the Algovestiq AIQ Score, IEF is the stronger of the two as of Sep 5, 2026, scoring 56 against VGLT's 48. The edge comes from risk resilience and value. VGLT is not without a case — it holds the better momentum profile, which matters more if that is the objective you are optimizing for. This is a systematic score, not a recommendation: it ranks the two on the same evidence, it does not know your holding period or tax position.
Is IEF or VGLT the better buy right now?
IEF carries the stronger systematic profile as of Sep 5, 2026, and the comparison is rated Competitive — 3 of 4 covered evidence groups agree. A Competitive rating means the two are close enough that your objective, not the score, should decide.
Why does the AIQ Score favor IEF over VGLT?
The composite weights Quality at 30%, Value at 30%, Momentum at 25% and Risk Resilience at 15%. IEF leads Risk Resilience by 33 points; IEF leads Value by 9 points; VGLT leads Momentum by 8 points. Where the two split, the factor with the larger weight carries the result.
Which is better value, IEF or VGLT?
IEF is the better-valued of the two on the peer-relative Value factor. IEF on the peer-relative Value factor, by 9 points. The Value factor reads valuation relative to sector peers and to the company's own fundamental quality, so it is not the same as simply having the lower multiple.
Which has stronger growth, IEF or VGLT?
Growth figures are not covered for both names. Growth here is measured on reported revenue and earnings, not on forward estimates — it describes what the businesses have delivered, not what the Street expects next.
Which has stronger momentum, IEF or VGLT?
VGLT on the Momentum factor, by 8 points. Momentum carries 25% of the AIQ composite. It has documented persistence over three- to twelve-month horizons, which makes it a timing input rather than a reason to hold something indefinitely.
Which is riskier, IEF or VGLT?
IEF is the more resilient of the two, so the other name carries the higher downside risk. IEF on Risk Resilience, by 33 points. The Risk Resilience factor weights 15% of the composite; position sizing usually responds to it more usefully than the buy/avoid decision does.
Is IEF more profitable than VGLT?
Margin data is not comparable for both names in the current snapshot.
Is IEF's lead over VGLT getting stronger or weaker?
IEF lead: Weakening — the AIQ differential moved from 12 to 8 points over 30 sessions. This is measured from 120 daily comparison snapshots between 2026-04-22 and 2026-09-03. The lead has not changed hands in that window.
What would change the IEF vs VGLT verdict?
The result is a state, not a forecast, so it changes when the underlying evidence changes. Concretely: VGLT closes the Risk Resilience gap — currently 33 points behind, the largest single contributor to IEF's edge; VGLT's Death Cross Active resolves — a bearish trend rule currently active against it; IEF starts generating bearish momentum or trend signals; the narrowing continues — the lead has already given back 4 points over 30 sessions, and a further 8-point move would eliminate IEF's advantage entirely.
What do the current signals say about IEF and VGLT?
IEF: 0 bullish / 4 bearish / 2 neutral. VGLT: 1 bullish / 3 bearish / 2 neutral, conflicted. A conflicted state means bullish and bearish rules are active on the same name at once — the technical evidence is not pointing one way, and a decision taken on it carries more timing risk. The most decision-relevant rule on IEF is Death Cross Active (bearish, long horizon). On VGLT it is Death Cross Active (bearish, long horizon).
Compare IEF and VGLT with others
How this comparison is scored
The Algovestiq AIQ Score composites four factors — Quality (30%), Value (30%), Momentum (25%) and Risk (15%). Sentiment is reported separately as SentimentPulse and is not folded into the composite. Scores refresh every trading day, and this page regenerates from the latest snapshot rather than being written once.
The verdict names a leader, states how broadly six independent evidence groups agree, and rates how durable that conclusion is given the score gap, its recent trajectory and the current signal state on both names.
How to use side-by-side comparison →This comparison is informational and educational, not investment advice. AIQ scores update daily; re-check after earnings, guidance or macro data that materially changes either name’s factor profile.