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▍ STATISTICAL PROJECTION · YEAR-END 2026

Based on current macro regime conditions and nasdaq 100 etf (qqq)'s historical behaviour in similar regimes, the model projects $748 by 2026-12-31 ( +5.8% from $707 today). The 68% confidence range is $617 to $879; the wider 95% range is $492 to $1,005. Methodology below the headline.

Central Estimate
$748
+5.8% vs current $707
68% Range (±1σ)
$617 to $879
95% Range (±1.96σ)
$492 to $1,005
Blended from 4 regime anchors· sample-weighted
VIX · Normal (15-25)
+9.2%n=3,047 · w=43%
10Y-2Y Yield Curve · Flat (0-100bps)
+16.7%n=2,123 · w=30%
HY OAS Spread · Tight (<350bps)
+4.9%n=922 · w=13%
Trade-Weighted Dollar · Weak (bottom tercile)
-1.3%n=990 · w=14%
METHOD: CENTRAL = SAMPLE-WEIGHTED MEAN OF PER-ANCHOR CURRENT-REGIME 1Y AVERAGES, SCALED TO 156-DAY HORIZON. BAND = ±σ√T USING 23.5% ANNUALIZED REALIZED VOL.
EXPECTED TO BE $748 BY 2026-12-31 (HIGHER FROM $707 ON 2026-05-18). NOT INVESTMENT ADVICE.
▍ MODEL · STATISTICAL FORECAST · 2026

Nasdaq 100 ETF (QQQ) Forecast 2026

Quantitative analysis from 6,298 observations of Nasdaq 100 ETF (QQQ) history, joined to four universal macro regime classifications. Numbers are computed, not narrated.

ByConvex Research Desk·Edited byBen Bleier·
QQQ · LAST
$707.04
AS OF 2026-05-18
Percentile · 25Y History
99.8th
▍ HEADLINE SIGNAL · CONTRARIAN BEARISH
Hist. Avg +252d
-1.3%
vs +11.4% unconditional · -12.7%pp below
When Trade-Weighted Dollar sits in its Weak (bottom tercile) regime — as it does today (118.04) — Nasdaq 100 ETF (QQQ) has historically returned an average of -1.35% over the next 252 trading days, 12.7pp below the all-history average of +11.37%. Sample: 990 observations, 59.7% hit rate.
METHOD: PERCENTILE-RANK MATCHED, LOOK-AHEAD-BIAS-FREE·NOT A FORECAST·HISTORICAL CONDITIONAL AVERAGE

Regime Scan[01/04]

VIX
Normal (15-25)
+9.2%+1Y AVG
Δ -2.2%pp · n=3,047
10Y-2Y Yield Curve
Flat (0-100bps)
+16.7%+1Y AVG
Δ +5.3%pp · n=2,123
HY OAS Spread
Tight (<350bps)
+4.9%+1Y AVG
Δ -6.5%pp · n=922
Trade-Weighted Dollar
Weak (bottom tercile)
-1.3%+1Y AVG
Δ -12.7%pp · n=990

Δ = divergence from +11.4% unconditional all-history average

Performance by Window[02]

WINDOWNANN RETANN VOLRET/VOLHIT %TOTAL
1Y26335.95%16.03%2.2455.3%35.81%
3Y76328.22%19.67%1.4356.8%110.67%
5Y1,26817.08%22.32%0.7754.8%120.01%
10Y2,52620.95%22.27%0.9456.5%569.69%
All6,29811.37%23.52%0.4854.5%1375.71%

Annualized total return = (1 + total)^(1/years) - 1. Ret/Vol is the annualized return divided by annualized volatility (Sharpe-equivalent without risk-free subtraction). Hit % = pct of single periods that were positive.

Where We Are Now[03]

Percentile Rank
99.8th
20.06median 84.11719.79
Current value 708.9300 on a 6,298-observation history going back to Oct 9, 2002.
Volatility Regime
normal
14.60%REALIZED 30D ANN
Sits at the 33.6th percentile vs full history. Median 17.26%.

Forward Returns by Macro Regime[04]

How Nasdaq 100 ETF (QQQ) has performed historically conditional on the prevailing macro regime. The current bucket is highlighted; +1Y averages drive the headline signal above.

VIX
Volatility regime: Low (<15), Normal (15-25), Elevated (25-40), Extreme (>40)
CURRENT: 17.26 Normal (15-25)
REGIME BUCKETN+30D+90D+1Y AVG+1Y MEDHIT %
Low (<15)2,0941.31%4.43%16.13%15.81%91.5%
Normal (15-25)3,0470.66%2.81%9.19%12.72%75.1%
Elevated (25-40)9484.10%9.10%20.05%26.76%81.1%
Extreme (>40)1935.79%19.33%49.92%53.05%97.9%
10Y-2Y Yield Curve
Yield curve regime: Inverted (<0bps), Flat (0-100bps), Steep (>100bps)
CURRENT: 0.50 Flat (0-100bps)
REGIME BUCKETN+30D+90D+1Y AVG+1Y MEDHIT %
Inverted (<0bps)7802.54%8.69%24.21%25.44%96.8%
Flat (0-100bps)2,1231.75%5.02%16.68%18.20%83.4%
Steep (>100bps)3,3341.19%3.81%11.07%13.63%78.4%
HY OAS Spread
Credit regime: Tight (<350bps), Normal (350-500bps), Stressed (>500bps)
CURRENT: 2.76 Tight (<350bps)
REGIME BUCKETN+30D+90D+1Y AVG+1Y MEDHIT %
Tight (<350bps)9221.21%3.22%4.91%8.41%67.2%
Normal (350-500bps)1,3792.12%7.18%23.91%26.71%89.1%
Stressed (>500bps)5554.07%9.46%27.26%27.09%97.7%
Trade-Weighted Dollar
Dollar regime: bottom/middle/top tercile of trailing 5Y rolling distribution
CURRENT: 118.04 Weak (bottom tercile)
REGIME BUCKETN+30D+90D+1Y AVG+1Y MEDHIT %
Weak (bottom tercile)9900.60%0.31%-1.35%3.68%59.7%
Neutral (middle)1,2282.21%6.37%14.09%17.84%83.2%
Strong (top tercile)2,5952.28%7.43%24.36%24.12%93.7%

Forward returns are forward-looking from each historical observation in the bucket; +252d corresponds to one trading year. Buckets with fewer than 5 forward-return observations are reported as n/a. These are conditional historical averages, not forecasts.

Lead-Lag Relationships[05]

For each universally-recognised leading indicator, the lag at which the daily-return correlation peaks. Positive lag means the anchor leads Nasdaq 100 ETF (QQQ); negative means it lags.

ANCHORROLEPEAK LAGPEAK CORRZERO-LAGRELATIONSHIP
VIXVolatility leader0d-0.659-0.659coincident
HY OAS SpreadCredit risk leader0d-0.503-0.503coincident
10Y Treasury YieldDiscount-rate driver0d0.2540.254coincident
Trade-Weighted DollarFX driver0d-0.240-0.240coincident
CopperGlobal growth proxy0d0.2110.211coincident
Baa-10Y SpreadCredit risk (slow)0d-0.194-0.194coincident
Initial Jobless ClaimsLabor leader-5d-0.169-0.005lags target by 5d
NFCIFinancial conditions+42d-0.0380.003weak
10Y-2Y Yield SpreadRecession leader-3d-0.0330.000weak
U-Mich Consumer SentimentSurvey leader0d0.0000.000weak

Pearson correlation of daily returns over up to 25 years of overlapping history, searched across a ±60-day lag grid. Indicators classified as “weak” don't have meaningful predictive power at daily resolution; many of these (yield curve, NFCI, sentiment) lead at monthly/quarterly horizons instead.

Historical Analogs[06]

Periods where Nasdaq 100 ETF (QQQ) sat at a similar percentile rank to today, with what happened over the next 30 / 90 / 252 trading days. Analogs are clustered to avoid double-counting nearby dates.

DATEVALUE+30D+90D+1Y
May 16, 2025521.51004.89%13.81%33.26%
Feb 14, 2025538.1500-12.86%1.50%12.57%
Nov 15, 2024496.57002.95%-5.57%20.80%
Aug 16, 2024475.03002.75%11.56%19.13%
May 17, 2024451.76007.80%8.35%13.56%

Worst Historical Drawdown[07]

-60.71%PEAK-TO-TROUGH
Peak May 21, 2001 → trough Oct 9, 2002. Recovered to prior peak on Sep 25, 2007 (1,812 days).
All-time high: 719.7900 on May 14, 2026 · Current DD from ATH: -1.51%

Cross-Asset Correlations · 1Y[08]

S&P 500
0.950
n=261
20Y Treasury
0.113
n=261
Gold
0.165
n=261
Bitcoin
0.495
n=261

Largest Single-Period Moves[09]

▲ Up
  • Oct 13, 200812.16%
  • Apr 9, 202512.00%
  • Oct 28, 200811.05%
  • May 8, 200210.70%
  • Mar 13, 20208.47%
▼ Down
  • Mar 16, 2020-11.98%
  • Mar 12, 2020-9.17%
  • Oct 15, 2008-8.96%
  • Sep 17, 2001-8.50%
  • Sep 29, 2008-7.94%

Calendar-Month Seasonality[10]

Average single-period return aggregated by the calendar month in which the period ended.

MONTHAVG RETURNHIT %N
January0.03%55.7%506
February-0.01%54.7%479
March0.07%51.9%545
April0.09%54.3%525
May0.09%53.9%534
June0.00%52.6%529
July0.11%58.8%529
August0.02%54.5%554
September-0.08%51.8%506
October0.15%56.1%553
November0.16%57.6%510
December-0.01%52.8%527

N = 6,298 OBS · GENERATED 2026-05-18 03:00Z

Forecast Approach

scenario weighted: We aggregate probability-weighted outcomes across active tracked scenarios, each with historical base rates and current heat scores. The projection above is the sample-weighted central estimate across current macro regime anchors; the scenario list below adds qualitative context.

Consensus source: Sell-side price targets

Key Drivers & Risks

  • Earnings growth
  • Valuations
  • Monetary policy
  • Risk appetite
  • Economic growth

Historical Volatility

Moderate-high: 15-25% annual range typical

Scenarios That Affect This Forecast

How QQQ Forecasts Have Held Up Historically

QQQ forecasts carry roughly 50% more dispersion than SPY forecasts because the Nasdaq-100 is a concentrated mega-cap-tech vehicle (Magnificent Seven near 50% weight) and behaves more like a single sector than a diversified index. Sell-side targets have missed QQQ by 20%+ in absolute terms in the dot-com bust (2000-2002), the 2020 V (+47% Q2 alone), and the 2022 rate-shock drawdown (-33%).

Regime-conditional models do better on QQQ than point targets but worse than on SPY, with directional accuracy near 64% versus 70% for SPY. The shortfall is structural: QQQ's behaviour is dominated by real-rate and AI-capex factors that move on their own schedule, decoupled from the regime classifier in 2023-2025 because no historical regime template included a $300B/year hyperscaler capex run-rate.

Regime Sensitivity for QQQ

QQQ is the highest-beta major equity index to the regime classifier. Goldilocks maps to forward 252-day returns averaging +18% (vs +14% for SPY); stagflation maps to roughly -7% (vs -3%); reflation maps near +12%; deflation maps near -10%. The amplification factor is roughly 1.3x SPY in regime-up environments and 1.5-2x in regime-down environments because QQQ's duration is longer and its concentration adds idiosyncratic risk.

In April 2026, the 10Y TIPS at 1.93% sits well above the 2010s average and is the dominant regime variable for QQQ specifically. A move below 1.5% would shift the regime conditional toward Goldilocks-with-rate-tailwind and lift the central projection materially; a move above 2.5% would compress the multiple even with no change in earnings.

What Drives QQQ Forecast Errors

Three distinct error sources dominate QQQ forecast misses. First, real-rate sensitivity is non-linear: a 50bp TIPS move from 1.0% to 1.5% has materially less impact than a 50bp move from 2.0% to 2.5% because of duration math. The model uses a linear rate beta and consistently underestimates rate-shock drawdowns above 2% TIPS.

Second, AI capex narrative regime is not in the macro classifier. From November 2022 (ChatGPT launch) to 2025, QQQ outperformed SPY by 30+ percentage points cumulatively on AI optimism that no rates-and-credit regime model can capture.

Third, single-name idiosyncratic risk: NVDA alone has been responsible for roughly one-third of QQQ's 2024-2025 gains. A single guide-down from any of the top five names can move QQQ 2-3% in a session, producing realized vol that swamps the model's bootstrap distribution for that month.

How to Use This Forecast in Practice

For QQQ, weight the regime conditional more lightly than for SPY and supplement with two cross-checks. First, the QQQ-SPY relative strength line: when QQQ leads SPY, growth is winning the regime; when SPY leads, the rotation is underway. Inflection points front-run sector moves by 2-4 weeks.

Second, NVDA datacenter revenue and hyperscaler capex guidance from MSFT, GOOG, META, and AMZN. The four hyperscalers' combined annual capex is the single most important driver of QQQ above the macro layer. If any of the four guides capex down materially, scale QQQ position size down regardless of what the regime classifier says.

The 68% confidence band on QQQ is structurally wider than SPY's; treat the central projection as a reference point, not a target.

Frequently Asked Questions

What factors could push Nasdaq 100 ETF (QQQ) higher?

The primary drivers that tend to lift Nasdaq 100 ETF (QQQ) depend on the current macro regime. Invesco QQQ tracking the Nasdaq 100, tech-heavy growth index. Convex tracks these drivers live across the Equity Index category and flags when multiple forces align in the same direction. See the "Key Drivers & Risks" section on this page for the current list, and check the regime dashboard for how the macro backdrop is currently tilted.

What factors could push Nasdaq 100 ETF (QQQ) lower?

The same transmission channels that drive Nasdaq 100 ETF (QQQ) higher operate in reverse when conditions flip. The risk drivers listed above map directly to scenarios that, if triggered, would pull this metric in the opposite direction. Convex aggregates these into a scenario-weighted probability distribution rather than a point forecast, so the magnitude depends on which scenarios activate.

Where does consensus see Nasdaq 100 ETF (QQQ) heading?

Rather than publish a point target that goes stale the day after release, Convex assembles consensus from the macro regime classification, active scenario probabilities, and historical base rates. Point forecasts from banks and strategists are worth reading for context, but they typically cluster around the consensus and miss the tail events that actually move markets. The scenario-weighted approach here captures that tail risk explicitly.

What is the historical range for Nasdaq 100 ETF (QQQ)?

Historical ranges for Nasdaq 100 ETF (QQQ) vary dramatically by regime. A level that is extreme in Goldilocks can be routine in Stagflation, and vice versa. The Historical Volatility section on this page describes the typical range and regime-specific behavior. For the full multi-decade history, visit the Nasdaq 100 ETF (QQQ) chart page, which includes selectable time ranges up to five years and downloadable data.

How often is the Nasdaq 100 ETF (QQQ) forecast updated?

This forecast page recalculates whenever the underlying data or regime classification changes, typically within hours of new data releases. The scenario probabilities refresh daily as the macro state is regenerated. Specific drivers listed on this page reflect the current state of the Convex regime engine, not static historical assumptions.

Is this forecast actionable for trading?

Convex forecasts are informational and educational. They describe probability distributions and regime-conditional paths rather than specific entry and exit levels. Traders and portfolio managers use them alongside other inputs including position sizing rules, risk management, and their own conviction calibration. They are not investment advice.

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Forecasts are model-based projections derived from current regime classification, scenario probabilities, and historical patterns. They are not investment advice. All investments involve risk.