Five holdings, 2.6 effective positions —
with 69% of measured risk in a single name.
On the statement, this portfolio holds an employer stock position and four funds. Measured over two years of daily price history, most of its variance came from one issuer — the same issuer that pays the client's salary — while the three equity funds moved nearly in lockstep with one another. This diagnostic quantifies where measured risk was concentrated, how the portfolio behaved on its worst realized days, and how sensitive the risk profile is to allocation. Every figure matches the attached calculation summary; the estimator behind each figure is named in the provenance section.
- Historical six-month outcome ranges, in dollars (two lenses)
- Capital allocation vs. measured risk contribution
- Fund overlap — co-movement of the equity sleeve
- Realized stress behavior — event attribution
- Allocation sensitivity — same holdings, minimum-volatility weights
- Expense analysis
- Advisor-completed sections (client data required)
- Limitations
SECTION 1 — HISTORICAL OUTCOME RANGES What six months looked like for this exact mix, in dollars
Two lenses on the same holdings over the measured window — one empirical, one a Gaussian reference model. They are shown together because neither alone is the truth: the empirical lens is limited to what happened; the model lens assumes normality this portfolio's returns do not fully satisfy (see Limitations).
The framing question for the advisor: are outcomes of this magnitude, in either direction, consistent with this client's documented risk profile — given that the client's employment income depends on the portfolio's dominant issuer?
SECTION 2 — CAPITAL vs. MEASURED RISK CONTRIBUTION Capital allocation and variance contribution diverge materially
| Holding | Weight | Variance contribution | Capital (muted) vs. contribution (violet) |
|---|---|---|---|
| MSFT employer stock + RSUs | 55% | 69.4% | |
| QQQ | 15% | 13.4% | |
| SPY | 15% | 10.3% | |
| VTI | 10% | 6.8% | |
| BND | 5% | 0.1% |
SECTION 3 — FUND OVERLAP The equity fund sleeve moved close to a single position
QQQ, SPY and VTI moved with an average pairwise correlation of 0.966 over the window (SPY–VTI: 0.996 — displays elsewhere as 1.00 due to rounding). Together they represent 40% of capital and 30% of measured variance. Because MSFT is also a top constituent of all three funds, the fund sleeve adds to the single-name exposure through look-through overlap rather than offsetting it.
SECTION 4 — REALIZED STRESS BEHAVIOR The window's three worst days, attributed
| Date | Portfolio | In dollars (current-value equivalent) | What the data shows |
|---|---|---|---|
| 2026-01-29 | −5.6% | −$69,900 | MSFT −10.0% on earnings while SPY moved −0.2%. An idiosyncratic single-name event at a 55% weight dominated the day; the funds' small declines did little to offset it. |
| 2025-04-04 | −4.3% | −$53,900 | Broad tariff-shock selloff: QQQ −6.2%, SPY −5.9%, VTI −5.9% — the three funds declined in unison, consistent with their 0.966 average pairwise correlation. |
| 2024-10-31 | −4.2% | −$51,900 | MSFT −6.1% on guidance; the fund sleeve declined concurrently. Idiosyncratic and systematic risk realized together. |
SECTION 5 — ALLOCATION SENSITIVITY How much of the measured risk is allocation, not selection
As a diagnostic, the same five holdings were re-weighted to the in-sample minimum-volatility allocation (selected under the engine's 180-day EWMA covariance with 5–40% bounds; scored under sample covariance — see provenance) (MSFT 13.7% · QQQ 13.4% · SPY 20.1% · VTI 19.9% · BND 32.9%). This is a hindsight computation on the identical window — it is shown to isolate how much of the portfolio's measured risk came from allocation, and is not a proposed portfolio, a recommendation, or an expectation of future results. In-sample return and Sharpe figures are deliberately excluded: weights selected with hindsight on a window cannot be fairly scored on that window.
| Current weights | Min-volatility weights (in-sample diagnostic) | |
|---|---|---|
| Annualized volatility (sample) | 19.8% | 12.4% (−37%) |
| Largest single-name variance contribution | MSFT 69.4% | SPY 26.6% |
| Effective variance-contribution positions | 2.6 | 4.4 |
| Maximum drawdown in window (different episodes — see note) | −23.3% | −13.8% |
| Gaussian reference 126-day range | −$315k / +$365k | −$158k / +$269k |
Note: the two drawdowns occurred in different episodes (current: Oct 2025 → Mar 2026; re-weighted: Dec 2024 → Apr 2025). Each figure is that portfolio's own worst stretch within the same overall window — not the same dates.
SECTION 6 — EXPENSE ANALYSIS Costs are not the primary risk driver here
| Holding | Weight | Expense ratio (sponsor-disclosed, as of 2026-07-11) |
|---|---|---|
| MSFT (direct stock) | 55% | 0.000% |
| QQQ | 15% | 0.180% |
| SPY | 15% | 0.0945% |
| VTI | 10% | 0.030% |
| BND | 5% | 0.030% |
| Weighted total | 100% | 0.046% (≈ $570/yr on current value; ≈ $5,700 over 10 years, assuming static value, weights and fees — a simplification) |
Many portfolio reviews lead with fee savings. This portfolio's weighted fund expenses are already very low — which is itself the finding: the measured risk here is structural, not expense-driven. Fee optimization cannot address a 69% single-name variance contribution; this report states that plainly rather than manufacturing a fee argument.
SECTION 7 — ADVISOR-COMPLETED SECTIONS Decisions belong to the advisor; these sections hold them
Corrly supplies diagnostics. Any recommendation, product decision, or plan change is authored by the advisor, using client data the advisor holds. When provided, we format these into the same evidence-linked layout — content authored and approved by the advisor:
SECTION 8 — LIMITATIONS What this analysis does not establish
Data: Financial Modeling Prep daily adjusted closes · window 2024-07-08 → 2026-07-10 (504 trading days, 503 daily returns) · market-data cutoff 2026-07-10 US close · snapshot SHA-256(16): 0a1ea644f957f02f. Re-pulls from the provider may shift adjusted closes at the margin; the snapshot hash detects divergence.
Estimators (per figure): sample covariance of daily simple returns, annualized ×252, for ALL variance, contribution, correlation, volatility and range figures · risk contribution = Euler (wᵢ·(Σw)ᵢ / wᵀΣw) · effective positions = entropy effective number of variance-contribution bets (not the Choueifaty diversification ratio) · 126-day Gaussian reference = sample mean ± 1.96σ scaled √126 · empirical range = rolling 126-day compounded returns (378 windows) · dollar figures are current-value equivalents (pct outcomes of a daily-rebalanced constant-weight backcast × illustrative value), not a dated holdings path · min-vol weights: TWO-STAGE — selected by the engine under 180-day EWMA covariance (bounds 5–40% per asset, L2 γ=0.1), then scored under sample covariance like every displayed metric; the 12.4% is a sample-covariance score of EWMA-selected weights, not the sample-covariance minimum (exact unrounded weights in the summary).
Expense ratios: sponsor disclosures as of 2026-07-11 (QQQ 0.18% per Invesco, effective 2025-12-22; SPY 0.0945%; VTI/BND 0.03%).
Engine: Corrly deterministic analysis engine v1. No generative model produced any figure in this report. Corrections policy: any error found is corrected and disclosed to the receiving advisor.
This sample uses a fictional client with real market data, to
illustrate the report format. Corrly reports are portfolio diagnostics prepared for
use by financial professionals — historical measurement, not a forecast, not
investment advice, and not a recommendation to buy, sell, or reallocate any
security. The advisor is solely responsible for any recommendation and for
suitability determinations.
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