REAL BACKTEST DATA · NOT A SIMULATION OF HOPE

The Lab

Every chart below is generated from the live engine on real market data — the validated config (1-hour, ≥50% confluence, 1.5-ATR stop, 3R target, 0.25-ATR limit-retrace maker entry) across the top crypto majors and a basket of commission-free stocks. We show risk as loudly as return, because that is the only honest way to show an edge.

net expectancy / trade (last 300)
win rate (3R asymmetric)
avg stop size (% of price)
trades in the sample

$100 over 300 trades — sizing is everything

The exact same 300 trades, with the exact same positive edge. The only thing that changes is how much you bet per trade. At 10× full notional, a winning system still wipes the account out — variance ruins you before the edge can pay. Note the log scale.

10× leverage is a cap, not a bet size. To risk ~2% of the account with a ~1.4% stop you use roughly 1.4× your equity in position — not 10×. On crypto we'd run 1% risk per trade; the drawdowns are real even then.

Long AND short — the system trades both sides

The engine takes longs and shorts (whichever way confluence points). Here's every trade split by direction, each as its own $100 equity curve at 1% risk. Over this window shorts carried it — crypto was weak — but that's the point: a two‑sided system adapts to the regime instead of betting the market only goes up.

LONG trades — expectancy
SHORT trades — expectancy
BOTH combined — expectancy
Don't assume shorts always win — it's regime‑dependent. In a bull window longs carry it. Trading both sides is what kept this green while the assets themselves fell.

First target vs full target — TP1 / TP2 hit rates

How often price reaches each reward multiple before the stop. This is just counting, so it's rock-solid. The first target (1.5R) prints about twice as often as the full 3R target — which is why "take something off the table" is a real option (it raises your win rate, at the cost of some expectancy).

Partial profit-taking is a psychology tool, not an edge booster: letting the full position run to 3R keeps the highest expectancy, but banking half at TP1 smooths the ride.

The edge is fee-sensitive — this is the whole game

Mean expectancy per trade at different round-trip costs. The edge is real at maker fees (0–0.04%) and nearly dies at taker fees (0.20%). This is why the entry is a limit/maker order and why low-fee venues matter more than any indicator setting.

Trade as a maker, or don't trade this edge at all. Commission-free stocks and 0%-maker crypto venues are where it lives.

Pick your exchange — watch the edge move

Because the edge lives and dies on fees, the venue matters more than any setting. Choose a venue and see the per‑trade expectancy it leaves you (round‑trip maker cost, interpolated from the measured curve). These are approximate published fees — always confirm and forward‑test.

Same strategy, same trades — only the venue changed. A 0%‑maker venue keeps the whole edge; a 0.20%+ taker venue erases it.

Double-top / double-bottom — the neckline break

Trading the classic M/W pattern honestly: fading the equal highs/lows barely beats random, but waiting for the neckline break (a confirmed close through structure) is a genuine, if secondary, edge — tested with the same maker execution.

mean expectancy / trade
of assets positive
universe tested
Confirms the project's core lesson: trade the break, not the touch. The confirmation is the edge.

Position‑size calculator — find your "right amount"

This is the lesson from the $100 test, made usable. Put in your account size, the risk you'll take per trade, and your stop distance — it tells you the exact position, the real dollars at risk, and whether you'd need leverage. Remember: to survive, risk stays small and leverage stays at or below 1×.

Rule of thumb from the data: 1% risk, and if the calculator shows leverage above ~1.5× you're either risking too much or your stop is too tight — back off, don't borrow.

Your forward track record — live, no cherry‑picking

This is the honest scoreboard: the actual resolved paper trades from the live journal, plotted as a running equity curve in R. It's empty or thin until enough trades resolve — that's the point. A backtest is a promise; this is the receipt.

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BOT edge (resolved, R)
YOUR reads (resolved, R)
Your discretionary reads (logged with read-add) are scored separately from the bot — so we find out whose edge is whose, honestly.

Live book exposure — your two‑sided risk guard

You can hold a 1h long and a 5m short on the same coin at once — but two trades mean two risks. This reads your live journal and shows the combined long+short risk per coin, so running both sides can't quietly over‑expose you. Gross = worst case if everything loses; net = your true directional bet.

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The engine blocks a new trade if it would push a coin's gross risk past your cap (default 2%). This panel is the eyeball version of that seatbelt.

Read this. These are backtests and forward paper results, not a track record of real money. The edge is modest, regime-dependent, and execution-gated — it survives only at maker fees and only with disciplined position sizing. Drawdowns of 40–65% appear even in the "good" sizing. Past performance does not predict future results. Nothing here is financial advice. Markets do not offer high return at low risk, and anyone who tells you otherwise is selling something.

Generated from live data on · Kudbee Quant engine · the honesty layer is the product.