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The model portfolio gained +12.3% since Apr 10, 26. The path was bumpy — a real drawdown of -34.8% from the peak in May, then a recovery. The past does not guarantee the future.

12 maintenance closes are excluded from these stats — they sat open far past their planned exit because of a bug and averaged +21.5% per trade. That's an infrastructure artifact, not a model result.

What you would actually keep

The figure above is in a vacuum, before costs. Commission is charged on both sides of a trade, and fixed fees bite hardest on small positions. Enter your own rates and position size to see what would be left.

Gross+12.3%
→
After fees-9.1%on $10,000 → $9,089
Round trip1.03%per trade (both sides)

Per trade: +0.6% gross → -0.4% after commission. The cumulative curve above is worth about 21 average trades, and every one of them pays a round trip.

This is why we don't sell signals as a way to make money: at today's costs and turnover the strategy doesn't pay for itself. We show this number rather than hide it — and charge for discipline, context and transparency, not for a promise of returns.

Charged the way you would pay it: one round-trip commission per closed position, at your rates. Fees are scaled to real turnover — a rebalance closes part of the book, not all of it. The share price defaults to the average across our own trades and can be changed. Slippage and the signal-to-execution gap are not included; with them the result would be worse still. Your broker app usually shows trade profit before commission — it is deducted separately and appears as its own line. Here it is already subtracted.

Cumulative return+12.3%model portfolio
Win rate49%289 trades
Profit factor1.29profit / loss
Avg ± per trade+5.3% / -3.9%win / loss
Max drawdown-34.8%peak → trough
Rolling Sharpe-0.38return / risk (10d)
Cumulative return of the model portfolio
equal weight by trading day, no reinvestment · since Apr 10, 26
+12.3%
+40%0%-15%
Apr 10, 26Sep 23, 26

What this means: the path is bumpy — in May the model fell to -34.8% from the peak, then recovered. The market can be harsh: don't put everything in one idea, and use stops.

Model confidence vs win rate
Confidence < 50%
43%37
50–59%
49%163
60–69%
51%89

What this means: the higher the model's confidence, the more often a trade is in profit (43% → 51%). The effect is modest — confidence is worth weighing, but it's not the only filter.

How trades closed
Model closed194
59% profitable+1.7% avg
Stop triggered75
9% profitable-5.3% avg
Target hit12
100% profitable+17.9% avg
Time expired8
88% profitable+3.5% avg

What this means: the model lets profits run (model and target exits are more often in profit) and cuts losses with stops — the low win rate on stops is offset by small loss size.

Equal-weighted track record (fixed stake per signal, no reinvestment or position sizing). Past results do not guarantee future ones. Not individual investment advice.

This is the open part of Finvectr

Model health and every closed trade are readable without an account — on purpose: you should be able to check us before you sign up. The daily brief, the signals and the exit plan open up after sign-in.