# 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 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 = ["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

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"

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

## 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]