Market snapshot, not real-time
S&P 500 (SPY) $748.62 +0.88% Nasdaq-100 (QQQ) $708.90 +1.85% Dow (DIA) $522.55 +0.89% Russell 2000 (IWM) $295.82 +1.20% 10-Year Treasury (IEF) $93.32 −0.23% Crude Oil (USO) $128.37 +2.28% Gold (GLD) $373.85 +1.70% US Dollar Index (UUP) $28.45 +0.23% Volatility (VXX) $21.29 −3.77% Semiconductors (SMH) $583.24 +4.37% Silver (SLV) $53.36 +4.67% Emerging Markets (EEM) $65.45 +2.97% Bitcoin (BTC) $66,470.13 +1.90% Ethereum (ETH) $1,922.88 +1.00% S&P 500 (SPY) $748.62 +0.88% Nasdaq-100 (QQQ) $708.90 +1.85% Dow (DIA) $522.55 +0.89% Russell 2000 (IWM) $295.82 +1.20% 10-Year Treasury (IEF) $93.32 −0.23% Crude Oil (USO) $128.37 +2.28% Gold (GLD) $373.85 +1.70% US Dollar Index (UUP) $28.45 +0.23% Volatility (VXX) $21.29 −3.77% Semiconductors (SMH) $583.24 +4.37% Silver (SLV) $53.36 +4.67% Emerging Markets (EEM) $65.45 +2.97% Bitcoin (BTC) $66,470.13 +1.90% Ethereum (ETH) $1,922.88 +1.00%

Study · Leverage · July 2026

Do 2× Single-Stock ETFs Actually Deliver 2×?

By Aydin Ali · July 18, 2026 · ~8 min read · Verified data · Massive Market Data

I hold NBIL — a 2× leveraged ETF on Nebius Group (NBIS) — inside AEA's leveraged sleeve. I wanted to know, with real numbers instead of a textbook diagram, exactly how far a daily-reset fund can drift from its stated multiple over a real holding period. I pulled twelve months of real daily closes for NBIL and six other well-known leveraged/underlying pairs and did the arithmetic myself.

−39.8 pp
Avg. decay gap, six 2× single-stock funds
Author's calculations
−106.5 pp
Worst offender: NBIL (2× NBIS) — the fund I hold
Massive Market Data
+60.7 pp
Best tracker: SOXL (3× SOXX) beat its own target
Massive Market Data
254d
Trading-day window (195d for NBIL, inception-limited)
Jul 2025 – Jul 2026

1. How these instruments actually work

A 2× single-stock ETF does not promise 2× your return over any period you choose — it promises 2× the daily return, reset every single trading day. If NBIS rises 5% today, NBIL is engineered to rise roughly 10% today. Tomorrow, that new, larger position gets leveraged again, from a new base. Over a straight, one-directional move this compounds in the holder's favor. Over a choppy, range-bound stretch — up one day, down the next, net roughly flat — the compounding math works against the holder every single time, because the fund is always leveraging from a slightly smaller base than a buy-and-hold position would have.

This is not a flaw in the product; it is the explicit, disclosed mechanic of daily-reset leverage. It just means the fund's prospectus promise (2× daily) and the number retail investors actually care about (2× over my holding period) are two different claims, and only the first one is guaranteed.

2. The data

Figure 1
NBIL vs. NBIS vs. its own 2× target, indexed to 100

NBIS gained 51% over NBIL's live trading window. A clean 2× fund would sit at index 202. NBIL actually closed at 95.5 — below where it started.

NBIL (actual) NBIS (underlying) 2× target (computed)
050100150200250300350400 NBIL 95 NBIS 151 2× target 202
Source: Massive Market Data (daily adjusted closes). Author's calculations. Window: 2025-10-07 to 2026-07-17 (NBIL inception to latest close).
Figure 2
Decay gap across the full basket, in percentage points

Six of seven funds fell short of their stated multiple. SOXL is the exception — a strong, sustained semiconductor uptrend let 3× daily compounding work in the holder's favor.

-120-80-4004080NBIL 2×-106.5TSLL 2×-42.2NVDL 2×-26.3AAPU 2×-16.0MSFU 2×-8.0TQQQ 3×-15.5SOXL 3×+60.7
Source: Massive Market Data. Author's calculations. Decay gap = actual ETF return − (leverage × underlying return), over each pair's common window.
Figure 3
Decay gap versus underlying volatility

The pattern holds: the more volatile the underlying, the worse the decay — NBIS's ~100% annualized volatility produced by far the worst gap in the basket. SOXX (semis) sits above the zero line despite real volatility, because that volatility ran in one direction.

0%20%40%60%80%100%-120-80-4004080NBISTSLANVDAAAPLMSFTQQQSOXXUnderlying annualized volatility →
Source: Massive Market Data. Underlying volatility = standard deviation of daily log returns × √252, annualized.
Full basket, sorted by decay gap
ETFLev.UnderlyingUnd. return2×/3× targetETF returnDecay gapUnd. ann. volTier
NBILNBIS+50.99%+101.97%−4.52%−106.5 pp100.5%Severe
TSLLTSLA+22.55%+45.09%+2.85%−42.2 pp44.6%Severe
NVDLNVDA+18.81%+37.62%+11.36%−26.3 pp35.6%Moderate
TQQQQQQ+24.90%+74.69%+59.21%−15.5 pp18.7%Moderate
AAPUAAPL+59.60%+119.20%+103.22%−16.0 pp24.3%Moderate
MSFUMSFT−22.15%−44.29%−52.27%−8.0 pp27.5%Mild
SOXLSOXX+111.89%+335.67%+396.41%+60.7 pp42.4%Positive

Tier bands (Severe < −60pp, Moderate −60 to −20pp, Mild −20 to 0pp, Positive > 0pp) are this author's own descriptive buckets for the measured decay gap, not an industry-standard classification.

3. Why it happens

The math is symmetric compounding applied to an asymmetric problem. Say a stock goes up 10% one day and down 10% the next. A buy-and-hold position ends at 1.10 × 0.90 = 0.99 of where it started — down 1%. A 2× daily fund goes up 20% then down 20%: 1.20 × 0.80 = 0.96 — down 4%, not 2%. The higher the daily swings, the worse this arithmetic drag compounds, entirely independent of where the underlying actually ends up. NBIS's roughly 100% annualized volatility — nearly triple QQQ's — is precisely why NBIL's gap is the worst in the basket even though NBIS itself had a genuinely good year.

SOXL's positive gap is the honest counter-case: when a trend is strong and directional rather than choppy, that same compounding mechanism works in the holder's favor. Leverage decay is not a guaranteed loss — it is a bet on path, not just on direction, and the path is the part almost nobody prices in before buying.

Illustrative only · same up-10%/down-10% chop, at increasing leverage · not from real ticker data
LeverageDay 1 (+10%)Day 2 (−10%)Two-day resultArithmetic drag
1× (buy & hold)1.1000.990−1.00%
2× daily-reset1.2000.960−4.00%3.0 pp worse
3× daily-reset1.3000.910−9.00%8.0 pp worse
4× daily-reset1.4000.840−16.00%15.0 pp worse

The drag doesn't scale linearly with leverage — it scales closer to the square of it, since each extra turn of leverage both amplifies the move and shrinks the base it compounds from on the down day. This is a clean, hypothetical two-day illustration of the mechanism, not a ticker-specific measurement; the real, measured numbers are the basket in Figure 2 and the table above.

4. What this means for a long-term holder

Every fund in this basket discloses, in its own prospectus, that it targets a daily return multiple and is not designed to be held for extended periods without active monitoring. That disclosure is accurate and I had read it before buying NBIL — what this study changed is the size of the number I actually attach to that warning. A theoretical "decay happens" is a different decision input than a measured −106.5 percentage points on a position I hold.

This is also, concretely, why AEA's Investment Policy Statement caps the leveraged sleeve at 5% of the book, separate from and tighter than every other bucket cap. NBIL is currently under that cap. This study is the quantitative case for why the cap exists at all, not just a rule I inherited from a template.

5. What I'd actually change, given these numbers

I'm not selling NBIL over this. The position is small (2.87% of the book, well under the 5% leveraged-sleeve cap), I understood the daily-reset mechanic before I bought it, and NBIS itself remains a name I want exposure to. But this study changed three specific things about how I hold it. First, I now treat NBIL as a position with an active shelf life, not a buy-and-forget holding — daily-reset funds are a different instrument category from the underlying stock, not just a leveraged wrapper around the same bet. Second, I check the decay gap periodically rather than assuming the October entry math still holds; a −106.5pp gap measured today says nothing about what the gap looks like in another six months of different volatility. Third, I now run every leveraged position I'm considering through the Risk X-Ray before adding it, specifically for the hidden double-exposure check — because NBIL sitting next to a direct NBIS position is exactly the kind of overlap this study exists to catch.

The uncomfortable, honest version of the finding: SOXL's +60.7pp gap and NBIL's −106.5pp gap are the same mechanism, pointed in opposite directions by nothing more than which way the underlying happened to trend. Betting on daily-reset leverage isn't betting on a company being right. It's betting on that company being right smoothly — and smooth is a much harder thing to predict than direction.

Check your own portfolio

If you hold a leveraged ETF, the fastest way to see whether you also hold hidden double-exposure to its underlying — or any other single-name concentration — is to run it through The Risk X-Ray, a free tool that runs entirely in your browser.

Open the Risk X-Ray →

Methodology

Data source. Daily adjusted closes from Massive Market Data, the same provider cited throughout this site, pulled 2026-07-18.

Window. 2025-07-15 to 2026-07-17 (254 trading days) for all pairs except NBIL/NBIS, measured over NBIL's own live trading history (2025-10-07 to 2026-07-17, 195 trading days) since the fund launched after the standard window began. NBIS in the NBIL pair is measured over that same shorter, aligned window — not the full 254 days — so the comparison is apples-to-apples.

Formulas. Underlying return = last close / first close − 1. Target = stated leverage × underlying return. ETF return computed identically on the ETF's own closes. Decay gap = ETF return − target, in percentage points. Underlying annualized volatility = standard deviation of daily log returns × √252, expressed as a percentage.

Reproducibility. The pull, storage, and every number above were computed via SQL aggregation over the raw daily bars, then verified against a standalone reproducibility script: research/_scripts/leverage_decay.py, which recomputes identical arithmetic from a flat CSV of date/ticker/close. The computed dataset backing this page's figures and table is at research/_data/leverage_decay.json.

Limitations. Seven pairs is a basket, not a census of the leveraged-ETF universe; results would differ over a different twelve-month window, particularly one with different volatility regimes. This is a historical, backward-looking measurement, not a forecast of future decay. Nothing here is investment advice or a recommendation to buy, sell, or avoid any of the securities discussed.