Income Strategy
Covered call ETF portfolio · Monthly distribution
Data as of — previous close
INCOME MODE
Annual fee drag (avg 0.65% expense ratio)
-$0
Portfolio growth trajectory
Allocation breakdown
ETF Universe
Screened candidates · Strategy-matched · Live yield data via Polygon.io
Data as of · ↻ Refresh
| Ticker | Strategy type | Index scope | Dist. yield | NAV drift | True return | Payout freq. | 2yr total return | Fit score | Status |
|---|
Yield vs. 2-year total return — ETF universe
Factor Exposure Analysis — 5-factor portfolio loading vs. individual ETFs
Portfolio factor loadings computed from dynamic allocation weights. Covered-call overlay structurally caps Momentum and amplifies Low-Volatility — this is why CC portfolios underperform in strong bull runs but protect capital in volatile regimes.
ETF Correlation Matrix — pairwise 24-month approximated correlations
−1.0 (inverse)
+1.0 (perfect)
Correlations estimated from underlying index relationships and historical co-movement. SVOL (short-VIX) shows structural negative correlation with all equity ETFs — a natural hedge.
Portfolio concentration risk: most income ETFs share >0.80 correlation via their underlying equity indices.
Distribution consistency reality
No covered-call ETF maintains ±1% month-over-month stability. Option premium varies with VIX. A 3–6 month cash buffer and trailing-average self-pay is the professional solution.
ROC tax deferral advantage
NEOS funds classify significant portions as Return of Capital — reducing current-year taxable income. Final character set at year-end. Effective tax drag often 5–15% lower than headline rate suggests.
Section 1256 benefit (NEOS)
Index options held by SPYI/QQQI qualify for 60/40 long/short treatment, improving after-tax efficiency. Wash-sale rules do not apply to Sec. 1256 contracts.
Covered-call upside cap
Selling calls structurally limits price appreciation. In strong bull markets, covered-call ETFs underperform their underlying index on total return — income is the trade-off for capped growth.
Scenario Matrix
Click any cell to auto-fill inputs and recalculate
Years to goal — contribution vs. annual return (your tax drag applied)
What-if sensitivity — how changing contribution or return affects years to goal
Income at horizon — contribution sensitivity
Tax drag impact on required capital
Historical Backtest
Simulated 24-month income stability using the 40/25/20/15 allocation
Monthly income — trailing 24 months (simulated)
Cumulative income received
Monthly income variance
Compare to Benchmark
QET allocation vs. plain index income at your settings
Monthly income — QET allocation vs SPY-only vs QQQ-only
| Metric | QET Portfolio | SPY Only | QQQ Only | 60/40 Traditional |
|---|
Strategy Intelligence
QET Agility Serv · Personalized to your inputs
Risk Lab
Institutional risk metrics · Sharpe / Sortino / Calmar · Sequence of Returns Stress Test
Risk-Adjusted Return Ratios — computed from 300-path Monte Carlo simulation
Sequence of Returns Risk (SoRR) — forced drawdown stress test
Configure a market shock at a specific year in your horizon. The SoRR path shows how a poorly timed drawdown — even if the portfolio later recovers in magnitude — permanently impairs income generation and retirement timeline.
Shock year
Year 1
When does the crash hit? Earlier = more damaging to long-term outcome.
Drawdown magnitude
−30%
Portfolio drops this % in one month. 2008 peak-to-trough: −57%. 2020 COVID: −34%.
Why SoRR matters: Two portfolios with identical 20-year average returns can have radically different outcomes if one experiences losses early vs. late.
Early losses force selling at depressed prices to meet income needs, compounding the damage permanently — unlike a salaried worker who can simply wait for recovery.
VIX Regime Analysis — how market volatility changes your income
Covered-call ETFs collect option premium to generate distributions. That premium rises and falls with implied volatility (VIX). Understanding your regime means understanding what your portfolio actually earns — not what the model assumes.
Per-ETF income under current VIX regime
Per-ETF risk-adjusted scores — Sharpe proxy (true return ÷ index volatility)
Tax-Lot Optimizer
Loss harvesting · ROC basis tracking · Wash-sale checker · After-tax income modeling
Add tax lots — enter your actual holdings
Your tax lots
No lots added yet — use the form above or click ⚡ Load Sample Lots
Tax-Loss Harvesting Opportunities
Return of Capital — adjusted cost basis tracker
ROC distributions reduce your cost basis each year — deferred, not eliminated. When you sell, your taxable gain is larger. NEOS funds (SPYI, QQQI) typically classify 50–70% of distributions as ROC.
AI Portfolio Analyst
Powered by Claude · Institutional-grade analysis · Trade recommendations · Risk flags
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Anthropic API Key
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Ready to analyze your portfolio
Enter your Anthropic API key above and click Analyze Portfolio.
Claude will receive your full portfolio state — strategy, allocation, Monte Carlo results, risk metrics, VIX regime, and factor exposures — and return an institutional-grade analysis.
Claude will receive your full portfolio state — strategy, allocation, Monte Carlo results, risk metrics, VIX regime, and factor exposures — and return an institutional-grade analysis.
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Analysis History — Session
Previous analyses from this session. Cleared on page refresh.
Alerts & Income Tracker
Actual vs projected distributions · Yield deviation alerts · Portfolio health score · Income digest
Active Alerts
No alerts yet — log actual distributions or click ⚡ to load sample data.
Log Actual Distributions — Monthly Income
Select a month, enter what you actually received per ETF (after-tax, in dollars). Expected values are computed from your portfolio size and ETF yields.
| Ticker | Expected (model) | Actual received ($) | Variance | Status |
|---|
Actual vs Projected Income — Trailing 12 Months
Teal bars = actual income received · Muted bars = model projection · Line = variance (over/under)
ETF Performance vs Model — Yield Accuracy Tracker
Compares your logged distributions to model yield expectations across all tracked months.
| Ticker | Model Yield | Months Logged | Avg Actual vs Expected | Trend | Alert |
|---|
Income Digest — Copy-Ready Summary
Plain-text summary of your portfolio income performance. Click 📋 Copy Email Digest above to copy to clipboard.
Generate by logging income data or loading sample data.
Portfolio Rebalancing Engine
Drift detection · Buy/sell trade list · Tax-aware contribution offset · Threshold vs calendar rebalancing
Current Holdings vs Target Allocation — Drift Analysis
Enter your actual dollar holdings per ETF (or leave 0). Target weights are loaded from your selected strategy. Drift = actual % − target %.
| Ticker | Target % | Actual Holdings ($) | Actual % | Drift | Status |
|---|
Rebalancing Trade List
Withdrawal Rate Planner
Decumulation engine · Guyton-Klinger guardrails · Floor+Upside · Monte Carlo depletion analysis
📐 Fixed Withdrawal (4% Rule)
Withdraw a fixed dollar amount each year, adjusted for inflation. Simple but ignores portfolio performance. Historically ~95% success over 30 years with diversified equity.
⚙️ Guyton-Klinger Guardrails
Dynamic spending: increase when portfolio outperforms, cut 10% when it drops 20% below trend. Balances higher initial withdrawal with market-adaptive guardrails.
🏠 Floor + Upside
Separate guaranteed floor (covered-call income only — no selling) from discretionary upside. Portfolio rarely depletes because distributions cover baseline needs.
Portfolio Value — Monte Carlo Fan (400 paths)
Shaded band = P10–P90 range · Center line = median (P50)
Guyton-Klinger Guardrail Rules
Prosperity Rule ↑
When portfolio exceeds trend by +20%, increase annual withdrawal by 10% (up to inflation-adjusted cap).
Capital Preservation ↓
When portfolio falls −20% below trend, cut annual withdrawal by 10% (floor: 75% of initial).
Withdrawal Floor Rule
Never make nominal pay cuts in good years. Withdrawals only rise when performance warrants and never fall below the 75% hard floor.
Distribution Reliability — Per-ETF Coverage Score
Coverage score = how much of your annual withdrawal each ETF's distribution income covers per $1M invested. Higher yield + stable NAV = better decumulation asset.
| Ticker | Annual Yield | NAV Drift | Coverage per $1M | Reliability Score | Grade |
|---|