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ANALYTICS
AnalysisScreenerGroups

Selection

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IVEP

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Benchmark

Pick one fund or composite — returns and exposures render in excess of it

Peer Universe

Reference set for percentile ranks and factor bars

Equity Funds · 5,640 total

ANALYTICS
AnalysisScreenerGroups

IVEP

Dan IVES Wedbush AI Power & Infrastructure ETF

Expense Ratio
0.75%
AUM
$16M
Inception
4/9/2026
·

The index is comprised exclusively of equity securities (or corresponding American Depositary Receipts (“ADRs”)) of companies included in the Dan Ives AI Power & Infrastructure 30 Research Report (the “AI Power Report”). Under normal circumstances, the fund will invest at least 80% of its net assets (plus borrowings for investment purposes) in the securities of AI Power Companies. It is non-diversified.

Time Series
–

Performance

NameCumulative ReturnAnn. ReturnAnn. VolSharpeMax DD
IVEP
Dan IVES Wedbush AI Power & Infrastructure ETF
-0.5%-1.0%29.8%-0.15-17.5%
ⓘ Methodology

ETF performance based on market prices. Drag on chart to select period. Sharpe Ratio uses the one-month T-bill as the risk-free rate. From 4/9/2026 to 10/7/2026.

Trailing Returns

Name
YTD1D5D1M3M6M1Y2Y3Y5YMAX
IVEP
Dan IVES Wedbush AI Power & Infrastructure ETF
0.7%-1.7%4.2%0.3%-1.0%0.7%
ⓘ Methodology

ETF performance based on market prices. Returns for periods greater than one year are annualized. As of 10/7/2026.

Annual Returns

Name
YTD
IVEP
Dan IVES Wedbush AI Power & Infrastructure ETF
0.7%
ⓘ Methodology

ETF performance based on market prices. As of 10/7/2026.

Correlation Matrix

Benchmark

Select a second series, or to correlate with the seven research factors.

Factor Regression

Not enough overlapping history for a regression in this period.
ⓘ Methodology

ETF performance based on market prices. Daily OLS of excess return (fund − T-bill) on factor spread returns over the selected date range, intersected with each series' history. Bold with * |t| ≥ 1.96, ** |t| ≥ 2.58. Cell shading tracks each loading's t-stat. Betas are returns-based — compare with the holdings-based factor scores below. Factor returns are long-short spread returns (© Ken French, Dartmouth).

SnapshotAs ofvsⓘ

Fund Profile

Family
Registrant
Type
ETF
Asset Class
Equity
Region
Equity Size & Style
Peer Group
Sector - AI (28 peers)
Expense Ratio
0.75%
AUM
$16M
Inception
4/9/2026
Holdings (Reported)
31
Turnover
1%
Equity
100%
Derivatives
0%
Net Equity Exposure
100%
Strategy Summary

The index is comprised exclusively of equity securities (or corresponding American Depositary Receipts (“ADRs”)) of companies included in the Dan Ives AI Power & Infrastructure 30 Research Report (the “AI Power Report”). Under normal circumstances, the fund will invest at least 80% of its net assets (plus borrowings for investment purposes) in the securities of AI Power Companies. It is non-diversified.

ⓘ Methodology

Expense ratio and its components from market data (10/6/2026). Turnover from market data (10/6/2026). Yield as of 10/6/2026, AUM 9/30/2026. Holdings, asset class, style, peer group and exposures as of 7/31/2026. Summary may be from an older prospectus.

Equity Size & Style Map

LargeMidSmall
7%
20%
48%
-
6%
14%
-
1%
3%
Large
ValueCoreGrowth
Size
Large
76%
Mid
20%
Small
5%
Style
Value
7%
Core
28%
Growth
65%
ⓘ Methodology

Equity size and style definitions. Size: each holding is scored against its own market's size curve — Large above $61.7B in the US and $21.4B elsewhere, Small below $10.8B worldwide — and a fund sits at the weighted average of its holdings. Style: each holding's Traditional Value score is ranked against stocks of the same region and size, and a fund sits at the weighted average of those ranks. Both are relative measures — where a holding stands among comparable stocks, not an absolute threshold. The dollar lines are recomputed from total market capitalisation each time the data is refreshed; the shares of the market they mark are what stay fixed. Cell shading and percentages: share of classified holdings weight per box. The grid and the dot are built from one set of per-holding scores — the dot is their weighted average — so they describe the same book at two levels of detail. The Size and Style bars are the grid's row and column totals. Holdings as of 7/31/2026. Stock-level data as of 8/31/2026.

Composite FactorsRef: Equity Funds

Intangible Value24.4
Traditional Value21.7
Small-Cap39.9
Quality51.2
Momentum58.5
ⓘ Methodology

Hover or click for factor definitions. Weighted average of underlying company-level values with weights equal to position size. Ranked within the clean equity fund universe, one entry per fund series (lowest: 0, highest: 100; the middle of the range is denser than the ends). Blue dots mark the fund; the shaded band spans the Equity Funds class 25th–75th percentile of scores, notched at the median. Holdings as of 7/31/2026. Stock-level data as of 8/31/2026.

Factor DetailsRef: Equity Funds

Valuation
Book-to-Price (NTM)19.6
Sales-to-Price (NTM)28.7
Earnings-to-Price (NTM)3.5
Innovation/IP
R&D / Mkt Cap0.61
Patents / Mkt Cap0.21
Brand
Sales & Marketing / Mkt Cap0.68
Trademarks / Mkt Cap0.04
Human Capital
PhD Employees / Mkt Cap1.9
Top University Alumni / Mkt Cap4.6
Politics
Lobbying Spend / Mkt Cap15.0
AI
AI Employees / Mkt Cap0.30
ⓘ Methodology

Hover or click for factor definitions. Weighted average of underlying company-level values with weights equal to position size. Solid blue dots mark the fund's position within the clean equity fund universe (5th–95th percentile scale); the shaded band spans the fund's broad class (Equity Funds) 25th–75th percentile, notched at the median. Holdings as of 7/31/2026. Stock-level data as of 8/31/2026. Expense ratio, yield, and turnover as of 10/6/2026. AUM as of 9/30/2026.

Country Exposure

Level
82.2%
82.2%
17.8%
6.0%
4.7%
4.3%
2.8%
ⓘ Methodology

Holdings as of 7/31/2026. Stock-level data as of 8/31/2026.

Sector Exposure

Level
42.6%
22.7%
14.2%
9.9%
7.9%
2.7%
ⓘ Methodology

Holdings as of 7/31/2026. Stock-level data as of 8/31/2026.

Thematic Exposure

AI Composition

Infrastructure72.4%
Early Adopter3.0%
Laggard24.6%

Magnificent 7

Magnificent 70.0%
Non-Magnificent 7100.0%

Old vs New Economy

Old Economy88.3%
New Economy11.7%

Globalization

Multinational45.9%
Exporter6.8%
Importer15.2%
Domestic32.0%

China Exposure

China/HK Domiciled0.0%
Revenue & Operations6.9%
Operations Only14.8%
Revenue Only3.1%
No Material Exposure75.2%

Company Size

Mega (>$500B)0.0%
Large ($70–500B)55.3%
Mid ($10–70B)40.0%
Small ($1–10B)4.7%
Micro (<$1B)0.0%
ⓘ Methodology

China exposure: domiciled = incorporated in China or Hong Kong, falling back to the filing's country for holdings outside the stock model. Among the rest, revenue = ≥15% of revenue derived from China; operations = ≥3% of LinkedIn-tracked workforce in China, or ≥2 identified Chinese suppliers making up ≥12% of those identified. China revenue is estimated where segment reporting is absent. Company size bands by holding market cap: Mega >$500B, Large $70–500B, Mid $10–70B, Small $1–10B, Micro <$1B. Old vs New Economy partitions Sparkline's 48 industries: New = technology, internet platforms and entertainment, e-commerce, payments, pharma/biotech/medtech, and renewable energy; Old = everything else. Shares are of classified holdings and sum to 100%. China shares are of total equity weight. Size shares are of scored holdings weight. Holdings as of 7/31/2026. Stock-level data as of 8/31/2026.

Holdings

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31 positions (top 10 shown, create for full holdings)

#NameTickerWeight %SectorIndustryCountry
1Schneider ElectricSBGSY
4.68
IndustrialsHeavy MachineryFRA
2EatonETN
4.34
IndustrialsElectrical & Power EqIRL
3Siemens EnergySMERY
4.26
IndustrialsHeavy MachineryDEU
4Nextera EnergyNEE
4.22
UtilitiesRegulated UtilitiesUSA
5Quanta ServicesPWR
4.14
IndustrialsDiv IndustrialsUSA
6Southern Company (the)SO
4.14
UtilitiesRegulated UtilitiesUSA
7Constellation EnergyCEG
4.12
UtilitiesMerchant PowerUSA
8Johnson Controls InternationalJCI
4.07
IndustrialsHeavy MachineryIRL
9EquinixEQIX
4.02
Real EstateGrowth REITsUSA
10GE VernovaGEV
3.89
IndustrialsHeavy MachineryUSA
ⓘ Methodology

Holdings as of 7/31/2026. Stock-level data as of 8/31/2026.

ConcentrationRef: Equity Funds

Total Holdings31
Effective Holdings28.2
Top 10 Weight41.9%
Max Position4.7%
Top Sector (of Net Assets)43%
Top Country (of Net Assets)74%
ⓘ Methodology

Hover or click for definitions. Solid blue dots mark the fund: percentage rows on a 0–100% scale, holdings counts log-scaled across the clean-universe 5th–95th percentile range. The shaded band spans the fund's broad class (Equity Funds) 25th–75th percentile, notched at the median. Holdings as of 7/31/2026.

Benchmark DifferentiationRef: Equity Funds

vs SPYBroad Benchmark
Active Share97.2%
Benchmark Correlation0.66
vs IWFStyle Benchmark
Active Share97.4%
Benchmark Correlation0.64
ⓘ Methodology

One sub-card per benchmark: the market primary, then the style secondary — the gap between them is the style sleeve itself. Both anchors are Sparkline-inferred (market from asset class and region, style from the holdings size-and-style map), not the fund's official prospectus benchmark. Solid blue dot marks the fund; the shaded band spans the reference set's 25th–75th percentile, notched at the median (band follows the Peer Universe selector). Active Share compares the fund's book with the benchmark's, share for share; Tracking Error is the annualized daily deviation over the trailing two years (ruler runs to just past the universe's 95th percentile, or past the fund's own figure where that is larger); Benchmark Correlation is the plain daily correlation over the trailing year. Hover the labels for full definitions.

Peer Group Rank

See All Peer Groups
Metric
IVEP
Dan IVES Wedbush AI Power & Infrastructure ETF
Peer Group
28 funds
Peer Asset Class
5,640 funds
YTD Return
0.68%41.62%711.63%11
1Y Return
---
3Y Return (Ann.)
---
5Y Return (Ann.)
---
Expense Ratiohigher = cheaper
0.75%0.67%110.74%47
ⓘ Methodology

Sparkline's own holdings-based peer taxonomy (32 share classes across 28 funds). One share class shown per fund — the exchange-listed class where the SEC series has one, else its longest-history class; percentile ranks and medians are computed against the same deduped set. Quartile chips fill the layer the fund's rank falls in (top layer = best quartile). Funds without a full return history rank only on the horizons they cover.

Similar Funds

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Nearest funds across the whole universe, by holdings and behavior — the peer taxonomy is ignored, so matches can come from any category.

Top Similarity50
Top Overlap
Top Active Tilt
Top Factor Match
FundPeer Group
1VOLT
Tema Electrification ETF
Sector - Infrastructure
Sector - Infrastructure
50---
2AIPO
Defiance AI & Power Infrastructure ETF
Sector - AI
Sector - AI
46---
3NXG
NXG NextGen Infrastructure Income Fund
Leveraged - Equity
Leveraged - Equity
46---
4TSES
Truth Social American Energy Security ETF
Sector - Infrastructure
Sector - Infrastructure
46---
5RSRFX
Reaves Infrastructure Fund
Sector - Infrastructure
Sector - Infrastructure
45---
6RACK
VanEck Data Center Supply Chain ETF
US Large Growth
US Large Growth
43---
7FSKGX
Fidelity Growth Strategies K6 Fund
US Mid Growth
US Mid Growth
21---
8POWR
iShares U.S. Power Infrastructure ETF
Sector - Infrastructure
Sector - Infrastructure
21---
9POW
VistaShares Electrification Supercycle ETF
Global Large Growth
Global Large Growth
21---
10GRID
First Trust NASDAQ Clean Edge Smart Grid Infrastructure Index Fund
Sector - Infrastructure
Sector - Infrastructure
21---

The method columns are members-only — create a free account to see these figures.

ⓘ Methodology

Rows are the consensus top matches (a fund must place in at least two methods' top 250 to qualify, and matches missing more than one of this fund's own methods are not ranked — a row scored on fewer methods is a noisier estimate, not a better match). Click a method column to see that method's own top matches across the whole universe instead. Gray (N) beside each method's metric is that fund's rank in the whole universe on that method. Similarity is a percentile among match-grade fund pairs, 0–100 — 87 means the pair is closer than 87% of the strongest matches in the universe, averaged across the methods — so it compares across funds: index clones tie at the top with thousands of other clone pairs, so scores top out in the high 80s to 90s, while a one-of-a-kind fund's best match can score in the 30s. Rows are ordered by the Consensus Rank — the geometric mean of those universe ranks, shown in each cell's tooltip — and the score is held down the list to the level of the closest match above it, so equal scores mean equally close and the number reads as a floor. A dash means that method has no figure for the pair at all (one of them lacks the holdings or return history it needs). Hover a column header for each method's definition. The “Top…” strips above compare against every fund's own top match across the whole universe (they deliberately don't follow the Peer Universe selector); Top Similarity is simply the best match's score, with no reference band; the Holdings and Active Tilt strips carry no reference band because computing every fund's best book overlap would require a full holdings scan per fund — the dot stands alone on its natural 0–100% scale. One share class shown per fund, and a fund's own sister share classes are excluded from its Top-match strips. Holdings as of 7/31/2026. Consensus Rank is the geometric mean of the match's universe-wide rank across the methods (#1.0 = top match on every one). Holdings Overlap = common-holdings weight (sum of the minimum weight across shared positions, long only). Active Tilt Overlap = the same statistic on active weights (holdings minus the fund's own default benchmark, floored at 0), which strips the benchmark ballast that dominates raw overlap. Factor Similarity = 100 − a signature-weighted RMS gap across the composite factor scores (0–100 ranks within the clean equity fund universe), each axis weighted by how far this fund sits from the universe median of 50.