Based on current macro regime conditions and china large-cap (fxi)'s historical behaviour in similar regimes, the model projects $36.29 by 2026-12-31 ( +0.1% from $36.24 today). The 68% confidence range is $27.35 to $45.23; the wider 95% range is $18.76 to $53.81. Methodology below the headline.
China Large-Cap (FXI) Forecast 2026
Quantitative analysis from 1,298 observations of China Large-Cap (FXI) history, joined to four universal macro regime classifications. Numbers are computed, not narrated.
Regime Scan[01/04]
Δ = divergence from -5.2% unconditional all-history average
Performance by Window[02]
| WINDOW | N | ANN RET | ANN VOL | RET/VOL | HIT % | TOTAL |
|---|---|---|---|---|---|---|
| 1Y | 262 | 0.95% | 19.39% | 0.05 | 46.7% | 0.95% |
| 3Y | 763 | 8.88% | 28.16% | 0.32 | 48.4% | 29.06% |
| 5Y | 1,268 | -4.11% | 31.62% | -0.13 | 46.6% | -18.91% |
| 10Y | 1,298 | -5.17% | 31.36% | -0.16 | 46.6% | -23.77% |
| All | 1,298 | -5.17% | 31.36% | -0.16 | 46.6% | -23.77% |
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]
Forward Returns by Macro Regime[04]
How China Large-Cap (FXI) has performed historically conditional on the prevailing macro regime. The current bucket is highlighted; +1Y averages drive the headline signal above.
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Low (<15) | 261 | -0.32% | 5.14% | 25.72% | 29.36% | 77.1% |
| Normal (15-25) | 842 | -0.25% | -2.63% | -4.70% | -11.01% | 35.6% |
| Elevated (25-40) | 176 | 0.40% | -0.25% | -5.12% | -7.43% | 28.7% |
| Extreme (>40) | 4 | n/a | n/a | n/a | n/a | n/a |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Inverted (<0bps) | 540 | 0.03% | 2.28% | 10.88% | 1.62% | 52.2% |
| Flat (0-100bps) | 573 | 0.81% | 0.05% | 4.78% | 0.97% | 52.1% |
| Steep (>100bps) | 163 | -3.69% | -11.73% | -31.98% | -30.83% | 0.0% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 762 | 0.59% | 1.15% | 7.05% | 15.00% | 56.7% |
| Normal (350-500bps) | 469 | -0.56% | -2.46% | -1.96% | -5.11% | 33.5% |
| Stressed (>500bps) | 53 | -6.09% | -5.46% | -9.35% | -11.31% | 15.1% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 115 | -4.12% | -11.58% | -31.65% | -32.24% | 0.0% |
| Neutral (middle) | 336 | -1.55% | -6.00% | -23.28% | -26.36% | 6.8% |
| Strong (top tercile) | 818 | 0.98% | 2.47% | 9.86% | 3.19% | 54.7% |
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 China Large-Cap (FXI); negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| Trade-Weighted Dollar | FX driver | 0d | -0.343 | -0.343 | coincident |
| Copper | Global growth proxy | 0d | 0.329 | 0.329 | coincident |
| VIX | Volatility leader | 0d | -0.319 | -0.319 | coincident |
| HY OAS Spread | Credit risk leader | 0d | -0.267 | -0.267 | coincident |
| 10Y-2Y Yield Spread | Recession leader | -14d | 0.115 | -0.027 | weak |
| Baa-10Y Spread | Credit risk (slow) | 0d | -0.086 | -0.086 | weak |
| NFCI | Financial conditions | +16d | -0.081 | -0.034 | weak |
| 10Y Treasury Yield | Discount-rate driver | +37d | -0.079 | -0.012 | weak |
| Initial Jobless Claims | Labor leader | +7d | 0.071 | -0.006 | weak |
| U-Mich Consumer Sentiment | Survey leader | 0d | 0.000 | 0.000 | weak |
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 China Large-Cap (FXI) 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.
| DATE | VALUE | +30D | +90D | +1Y |
|---|---|---|---|---|
| Apr 21, 2025 | 32.4300 | 10.08% | 18.90% | 15.94% |
| Jan 21, 2025 | 30.7500 | 19.64% | 13.82% | 28.39% |
| Oct 23, 2024 | 31.9200 | -4.86% | 15.82% | 28.70% |
Worst Historical Drawdown[07]
Cross-Asset Correlations · 1Y[08]
Largest Single-Period Moves[09]
- Mar 16, 202221.24%
- Sep 24, 20249.83%
- Dec 9, 20248.22%
- Sep 26, 20247.98%
- Nov 4, 20227.58%
- Oct 24, 2022-9.99%
- Oct 8, 2024-9.16%
- Apr 7, 2025-8.37%
- Apr 4, 2025-7.04%
- Mar 14, 2022-6.71%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 0.15% | 49.5% | 101 |
| February | -0.09% | 44.8% | 96 |
| March | 0.02% | 44.0% | 109 |
| April | -0.04% | 43.8% | 128 |
| May | 0.02% | 43.9% | 123 |
| June | 0.14% | 53.4% | 103 |
| July | -0.10% | 44.8% | 105 |
| August | -0.02% | 45.9% | 111 |
| September | 0.02% | 45.6% | 103 |
| October | -0.20% | 46.4% | 110 |
| November | 0.20% | 51.0% | 102 |
| December | -0.09% | 48.1% | 106 |
N = 1,298 OBS · GENERATED 2026-05-17 17:00Z
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 FXI Forecasts Have Held Up Historically
China large-cap ETF forecasts have one of the worst track records of any liquid equity ETF. The 2021-2024 drawdown (-65% peak to trough on regulatory crackdowns plus property-sector deleveraging plus US-China tensions) was missed by every consensus forecast; the 2024 H2 stimulus rally (+45% in three months) was equally missed.
Regime-conditional models on FXI achieve approximately 55% directional accuracy. The dominant variables are PBoC policy, Chinese stimulus announcements, US-China trade and tech-decoupling tensions, and CNY strength.
Regime Sensitivity for FXI
FXI has unique regime sensitivity that doesn't map to the standard four-factor classifier. The dominant variables are Chinese policy (monetary and fiscal stimulus), US-China geopolitics (binary regime risk), and Chinese property sector dynamics. Goldilocks regimes anchored by stimulus and de-escalation map to forward 252-day FXI returns averaging +18%; stagflation regimes with stimulus disappointing map to -10%; reflation near +12%; deflation near -20%.
The April 2026 setup has Trump 2.0 tariffs at 60%+ on China, PBoC easing modestly, and the property sector still deleveraging. The regime conditional reads as cautiously constructive on stimulus optionality but with binary US-China escalation risk.
What Drives FXI Forecast Errors
Three structural issues drive FXI forecast errors. First, Chinese policy is opaque and announced unpredictably. The September 2024 stimulus surprise that drove FXI +35% in three weeks had no Western-analyst forecast model that anticipated the magnitude; the November 2024 fiscal stimulus disappointment took FXI -15%.
Second, US-China geopolitics is binary. Trump 2.0 tariff escalations, technology-export controls (semiconductor licensing), and Taiwan-tension headlines each produce 5-10% FXI moves that no macro classifier captures.
Third, ADR delisting risk persists. PCAOB-SEC audit-access disputes have been resolved but could re-emerge; forced delisting would re-shape FXI composition.
How to Use This Forecast in Practice
For FXI, watch PBoC and Politburo policy announcements (the dominant binary), US-China trade news (the secondary binary), and CNY direction (the FX-leg signal). Aggregate macro models matter less than headline-driven regime shifts.
The cleanest cross-check is the FXI-MCHI spread (MCHI is broader-than-large-cap China). FXI leading MCHI signals state-owned-enterprise dominance (banks, energy); MCHI leading flags broader Chinese growth participation. The 68% band on FXI should be treated as 200%+ of SPY's because of the policy-and-geopolitical tail risks.
Frequently Asked Questions
What factors could push China Large-Cap (FXI) higher?▾
The primary drivers that tend to lift China Large-Cap (FXI) depend on the current macro regime. iShares China Large-Cap ETF, proxy for Chinese equity market. 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 China Large-Cap (FXI) lower?▾
The same transmission channels that drive China Large-Cap (FXI) 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 China Large-Cap (FXI) 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 China Large-Cap (FXI)?▾
Historical ranges for China Large-Cap (FXI) 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 China Large-Cap (FXI) chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the China Large-Cap (FXI) 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.