Analytics & Risk

The Analytics tab covers the questions Overview doesn’t have room for:

Sub-tab	What it shows
Performance	Historical portfolio value, benchmark comparison, drawdown
Risk	Volatility, beta, and risk decomposition across holdings
Exposure	Sector tilt, concentration, and how “diversified” your portfolio actually is
Signals	Aggregated verdict and confidence spectrum across all holdings
Market Context	Regime classification and how it’s shaping the rest of the analytics

Charts are rendered with Chart.js and loaded lazily, so the Analytics tab doesn’t cost anything until you actually open it.

Research-only tickers stay outside invested-position analytics. With no owned positions, the growth card hides its personalized dollar scenarios and shows only the S&P 500 as an indexed reference (100 = start) — never a fabricated $100,000 portfolio.

Reading the confidence spectrum

Verdicts aren’t binary. A “Hold” with high confidence and a “Hold” with low confidence mean different things — the confidence spectrum view is where that distinction actually becomes visible instead of getting flattened into one label.

Reading exposure

Exposure analytics exist specifically to answer the “is this actually diversified” question. A portfolio can look balanced by position count and still be one sector-wide bet — this is the view that will tell you if that’s what’s happening.

What your funds cost you

Every fund charges a fee whether or not you ever notice it. The fee view turns each fund’s expense ratio into the number that actually matters: dollars per year, at your position size, plus what that compounds to over a longer horizon — including the growth those fees never got to earn.

Two honesty rules apply:

• The long-horizon figure is a projection under a stated growth assumption, not a forecast. The assumption is printed next to the number.
• A fund whose expense ratio can’t be read is listed as fee unknown, never charged $0. Individual stocks don’t carry an expense ratio at all, so they’re left out of the fee math rather than counted as free.

Do your ETFs own the same thing?

Holding three funds isn’t diversification if they hold the same companies. The overlap view compares each pair of your ETFs and shows what they share.

It compares each fund’s top 10 published holdings — that’s what’s freely available, and the view says so rather than implying it has seen the full book. Two S&P-heavy funds will show a high overlap; that reading is real, but it’s a floor, not the whole picture.

What your holdings pay you

The income view is the other side of holding: not what your positions are worth, but what they pay you. It turns each holding’s forward dividend rate into annual cash at your position size, totals it, and shows the blended yield across the holdings that actually pay.

Holdings that pay nothing are named, never counted as $0 income padding the coverage. Each payer shows its yield on today’s price, and an ex-dividend heads-up appears when a payment’s cutoff date is near — the date by which you need to own the shares to collect the next one. A per-share dividend larger than the share price is rejected as bad data rather than trusted.

When your dividends land

Below the income rows, a twelve-month strip shows which months pay you. Dividend income is lumpy — three quiet months and then three payers at once — and an annual total hides that entirely.

The schedule is read from each holding’s real trailing ex-dates, not an assumed quarterly rhythm, so a monthly payer shows twelve bars and a quarterly payer shows four, each in its own months. The amounts come from the same forward dividend rate as the rows above, which means a recently raised dividend projects at the new rate on the established schedule.

Two things the strip is careful about. The months are ex-dividend months — the cutoffs to own each payer — not pay dates; the cash itself usually arrives days to weeks later, and the card says so rather than implying money in hand. And a payer whose schedule can’t be read from history is listed as unscheduled with its annual amount, rather than spread across months that were never actually observed.