Every rule is published. Every fill is logged. Two variants run head-to-head as a live A/B test so you can see which momentum definition actually holds up — not a backtest, a forward record starting 2026-08-09.
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Both books opened at $100,000 on 2026-08-09. Paper, marked to the last close. Variant B never changes — it's the control. Any rule change goes to A only, is logged with a dated hypothesis, and is judged on at least two weeks of relative equity before adoption.
That's the whole thing. The stops and the 200dma filter are mechanical — the point of publishing them is that I can't quietly move them when a position goes against me.
| # | Ticker | Last | 6m | Score A |
|---|---|---|---|---|
| 1 | MU | 861.00 | 118.3% | 2.55 |
| 2 | SNOW | 334.70 | 98.7% | 2.32 |
| 3 | PANW | 385.04 | 141.7% | 2.25 |
| 4 | UNH | 408.74 | 49.8% | 1.76 |
| 5 | XBI | 158.03 | 26.0% | 1.62 |
| 6 | CRWD | 225.16 | 127.7% | 1.50 |
| 7 | AMD | 469.56 | 125.3% | 1.39 |
| 8 | LLY | 1,231.94 | 16.8% | 1.26 |
| 9 | IWM | 299.98 | 13.7% | 1.20 |
| 10 | MRK | 130.92 | 8.9% | 1.16 |
Top 10 of ~65 shown, generated 2026-08-11. The paid file has the full scored universe as CSV, plus the weekly top-5 with entry levels and stop levels already computed.
The scoring logic isn't the secret — discipline is. Score any universe yourself:
import yfinance as yf, numpy as np
def score(tickers):
px = yf.download(tickers, period="2y")["Close"]
out = {}
for t in tickers:
s = px[t].dropna()
if len(s) < 260 or s.iloc[-1] < s.rolling(200).mean().iloc[-1]:
continue # 200dma absolute filter
r3 = s.iloc[-1]/s.iloc[-63] - 1
r6 = s.iloc[-1]/s.iloc[-126] - 1
r12 = s.iloc[-21]/s.iloc[-252] - 1 # 12-1: skip last month
vol = max(np.std(np.diff(np.log(s[-21:])))*np.sqrt(252), 0.05)
out[t] = ((r3 + r6 + r12)/3) / vol # variant A score
return sorted(out.items(), key=lambda kv: -kv[1])
Run that and you have variant A. What $9 buys is not the formula — it's the packaged one-file engine (screen / rebalance / mark / status with the paper book and stop tracking wired in), the full scored universe every week, and the signal file so you don't have to remember to run it.
run.py — the full engine, one file, no dependencies beyond yfinance/pandas/numpy.rules.md — the exact mechanical ruleset above.latest_signals.csv — all ~65 names scored and ranked.SIGNALS_<date>.md — the clean weekly top-5 plus watchlist.After paying you land on a receipt page — your download is at smeltworks.com/momentumedge/get. Bookmark it; it is also printed on the checkout page.