US ETF Flow & Sector Breadth Analysis

Overview

Track capital flows through US ETFs to identify institutional positioning, sector rotation trends, and risk appetite shifts. ETF flows are a real-time proxy for institutional capital allocation — unlike 13F filings (45-day lag), ETF creation/redemption data is available daily.

Core Concepts

1. ETF Flow Mechanics

Creation / Redemption process:

• Inflows (creation): Authorized Participants (APs) deliver baskets of underlying securities to the ETF issuer → receive new ETF shares → sell on exchange. This happens when ETF trades at a premium to NAV.
• Outflows (redemption): APs buy ETF shares on exchange → redeem with issuer for underlying securities → sell securities. This happens when ETF trades at a discount to NAV.
• Signal interpretation: sustained large inflows = institutional demand; sustained large outflows = institutional liquidation.

Key distinction:

• ETF price movement ≠ ETF flow. Price can rise on low volume (momentum). Flows require actual capital commitment.
• Flows are a quantity signal (how much money is moving), not a price signal.

2. Major ETF Flow Categories

Broad Market ETFs

ETF	Tracking Index	AUM	Flow Signal
SPY	S&P 500	~$500B	Broadest equity risk appetite
IVV	S&P 500	~$400B	Long-term institutional allocation
VOO	S&P 500	~$400B	Retail + advisor allocation
QQQ	Nasdaq 100	~$250B	Tech / growth appetite
IWM	Russell 2000	~$60B	Small-cap risk appetite
DIA	Dow Jones 30	~$30B	Value / blue-chip sentiment

Interpretation rules:

# Broad market flow signals
if spy_flow > 0 and iwm_flow > 0:
    signal = "risk_on"  # Both large and small cap getting inflows
elif spy_flow > 0 and iwm_flow < 0:
    signal = "quality_flight"  # Money rotating to large-cap safety
elif spy_flow < 0 and iwm_flow < 0:
    signal = "risk_off"  # Broad equity outflows
elif spy_flow < 0 and iwm_flow > 0:
    signal = "risk_seeking"  # Rotation from large to small (rare, usually early cycle)

Sector ETFs (SPDR Select Sector)

ETF	Sector	Economic Sensitivity	Cycle Phase
XLK	Technology	Growth / late cycle	Expansion
XLF	Financials	Rate sensitive	Early recovery
XLE	Energy	Commodity linked	Late cycle / inflation
XLV	Healthcare	Defensive	Recession
XLY	Consumer Discretionary	Cyclical	Recovery
XLP	Consumer Staples	Defensive	Recession
XLI	Industrials	Cyclical	Early expansion
XLU	Utilities	Defensive / rate sensitive	Late cycle / recession
XLB	Materials	Commodity linked	Early cycle
XLRE	Real Estate	Rate sensitive	Rate-cut cycle
XLC	Communication Services	Growth (META, GOOGL)	Expansion

Style & Factor ETFs

ETF	Factor	Signal
IVW / SPYG	S&P 500 Growth	Growth appetite
IVE / SPYV	S&P 500 Value	Value rotation
MTUM	MSCI USA Momentum	Trend following
QUAL	MSCI USA Quality	Quality flight
USMV / SPLV	Min Volatility	Defensive positioning
SIZE	MSCI USA Size	Small-cap factor

Fixed Income ETFs

ETF	Segment	Signal
TLT	20+ Year Treasury	Duration / rate expectations
IEF	7-10 Year Treasury	Intermediate rate view
SHY	1-3 Year Treasury	Cash proxy / safe haven
LQD	Investment Grade Corp	Credit appetite
HYG / JNK	High Yield Corp	Risk appetite / credit cycle
TIP	TIPS	Inflation expectations
EMB	EM Sovereign Debt	EM risk appetite

3. Sector Rotation Signals

Sector breadth analysis:

# Sector breadth = number of sectors with positive flows / total sectors
sector_flows = {
    "XLK": +500,  # $500M inflow
    "XLF": +200,
    "XLE": -100,
    "XLV": +50,
    "XLY": -300,
    "XLP": +100,
    "XLI": +150,
    "XLU": -50,
    "XLB": +80,
    "XLRE": -200,
    "XLC": +300,
}

positive_sectors = sum(1 for v in sector_flows.values() if v > 0)
breadth = positive_sectors / len(sector_flows)

# Interpretation
# breadth > 0.7: broad-based inflows → healthy bull market
# breadth 0.4-0.7: selective rotation → stock/sector picker's market
# breadth < 0.4: broad outflows → risk-off environment

Cyclical vs Defensive ratio:

cyclical = ["XLK", "XLY", "XLI", "XLF", "XLB"]
defensive = ["XLV", "XLP", "XLU", "XLRE"]

cyclical_flow = sum(sector_flows[s] for s in cyclical)
defensive_flow = sum(sector_flows[s] for s in defensive)

ratio = cyclical_flow / (cyclical_flow + defensive_flow + 1e-10)

# ratio > 0.65: strong risk-on, cyclical leadership
# ratio 0.4-0.65: balanced
# ratio < 0.4: defensive rotation, risk-off

4. Thematic ETF Flows

Growth / innovation themes:

Theme	Key ETFs	What It Tracks
AI / Semiconductors	SMH, SOXX, BOTZ	AI capex cycle
Clean Energy	ICLN, TAN, QCLN	Energy transition spend
Biotech	XBI, IBB	Pharma pipeline / M&A cycle
Cybersecurity	CIBR, HACK	Security spending cycle
China Internet	KWEB, FXI	China tech sentiment
India	INDA, SMIN	India growth allocation
Emerging Markets	EEM, VWO	EM risk appetite
Gold Miners	GDX, GDXJ	Gold price leverage play
Bitcoin	IBIT, FBTC	Crypto institutional adoption

Thematic flow interpretation:

• Sustained 4-week+ inflows into a theme = institutional conviction, not just hot money
• Sudden large outflows from a theme that was trending = crowded trade unwind risk
• Divergence between thematic ETF flow and underlying asset price = potential inflection

5. Flow-Based Trading Signals

Signal construction:

def etf_flow_signal(ticker, lookback_days=20):
    """
    Generate trading signal from ETF flow data.
    """
    # Cumulative flow over lookback period
    cum_flow = sum(daily_flows[ticker][-lookback_days:])

    # Flow as % of AUM (normalized)
    flow_pct = cum_flow / aum[ticker]

    # Flow momentum: recent 5-day vs prior 15-day
    recent = sum(daily_flows[ticker][-5:])
    prior = sum(daily_flows[ticker][-20:-5])
    momentum = recent - prior

    # Signal
    if flow_pct > 0.02 and momentum > 0:
        return "strong_inflow"   # Sustained and accelerating
    elif flow_pct > 0.01:
        return "mild_inflow"     # Positive but not accelerating
    elif flow_pct < -0.02 and momentum < 0:
        return "strong_outflow"  # Sustained and accelerating outflows
    elif flow_pct < -0.01:
        return "mild_outflow"
    else:
        return "neutral"

Contrarian vs momentum flow signals:

• Momentum (follow the flow): works best for broad market ETFs (SPY, QQQ) during trending markets
• Contrarian (fade extreme flows): works best for sector/thematic ETFs at extreme levels
• Rule of thumb: 3-standard-deviation flow events in sector ETFs tend to mean-revert within 2-4 weeks

Data Access

Via yfinance

import yfinance as yf

# ETF price and volume data
etf = yf.download("SPY", start="2025-01-01", end="2026-03-30", progress=False)

# ETF info (AUM, expense ratio, holdings)
spy = yf.Ticker("SPY")
info = spy.info
print(f"AUM: {info.get('totalAssets')}")
print(f"Expense ratio: {info.get('annualReportExpenseRatio')}")

# Sector weights (for sector ETFs)
# Not directly available via yfinance; use web scraping or manual input

Flow Data Sources

Source	Access	Coverage	Latency
ETF.com	Free (web)	US ETFs	T+1
Bloomberg Terminal	Paid	Global ETFs	Real-time
ICI (Investment Company Institute)	Free (weekly)	US mutual fund + ETF aggregate	T+7
ETF Database (etfdb.com)	Free (web)	US ETFs	T+1
VettaFi	Free (web)	US ETFs	T+1

Output Format

## ETF Flow Analysis — [Date Range]

### Broad Market Flows
- **SPY**: [+/- $X.XB over N days] — [risk-on / risk-off signal]
- **QQQ**: [+/- $X.XB] — [tech appetite]
- **IWM**: [+/- $X.XB] — [small-cap sentiment]
- **Overall**: [risk-on / selective / risk-off]

### Sector Rotation
- **Inflow leaders**: [sector1 +$XM, sector2 +$XM]
- **Outflow leaders**: [sector1 -$XM, sector2 -$XM]
- **Breadth**: X/11 sectors with positive flows
- **Cyclical/Defensive ratio**: X.XX [risk-on / balanced / defensive]

### Style Factor Flows
- **Growth vs Value**: [growth leading / value leading / balanced]
- **Momentum**: [inflow / outflow]
- **Quality/MinVol**: [inflow = defensive, outflow = risk-on]

### Fixed Income Flows
- **Duration signal**: TLT [inflow/outflow] → [rate cut expectations / rate concern]
- **Credit signal**: HYG [inflow/outflow] → [credit cycle expansion / contraction]
- **Inflation signal**: TIP [inflow/outflow] → [rising / falling inflation expectations]

### Thematic Highlights
- [Theme1 ETF]: [flow trend and implication]
- [Theme2 ETF]: [flow trend and implication]

### Composite Signal
| Dimension | Signal | Basis |
|-----------|--------|-------|
| Risk appetite | [on/off] | SPY+QQQ flows, C/D ratio |
| Sector rotation | [early/mid/late cycle] | Sector flow pattern |
| Rate expectations | [cuts/hold/hikes] | TLT + TIP flows |

### Investment Implication
- **Positioning**: [overweight equities / neutral / underweight]
- **Sector tilts**: [overweight X, underweight Y]
- **Risk level**: [high / moderate / low]

Notes

• ETF flows are a proxy for institutional behavior, not a standalone signal; combine with price action and fundamentals
• Large single-day flows can be rebalancing-driven (quarter-end, index reconstitution) rather than directional
• Options-related ETF activity (hedging via SPY puts) can distort flow signals
• International ETF flows (EEM, FXI, INDA) are useful for global macro positioning
• This framework is for research purposes only and does not constitute investment advice