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signal-platform/docs/research/README.md
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dennisthiessenandClaude Opus 4.8 906d1db7d1 Docs: state the actual strategy, add an end-to-end diagram, add a research log
The README opened with "find the path of least resistance, key S/R zones, and
asymmetric R:R setups" — a description of a strategy we do not run. What we run
is a long-only cross-sectional momentum book with a trailing exit. The S/R
engine, the composite score, sentiment and fundamentals are screening and
display; none has a measured edge.

- Rewrites the intro/philosophy around the real strategy, and says plainly what
  is NOT the edge.
- Adds a mermaid decision graph, universe -> qualified -> ranked -> opened ->
  closed, with the real exit distribution on the terminal nodes: initial stop 45%,
  trailing stop 31%, max hold 24%, S/R target 0%. Validated against the mermaid
  parser, not eyeballed.
- Documents that the R:R and touch-probability are GATE INPUTS, not forecasts of
  the trade — the single easiest way to misread this app.
- Adds win rate, best/worst R and the exit-reason split to the production
  baseline table.
- New docs/research/README.md: every strategy tested, the result, the decision,
  and why we stay with the current one. 12 rejected ideas (take-profit exits,
  clear-air gate relaxation, EV gate, regime overlay, inverse-vol sizing, shorts,
  standalone vol, FIP, ...), the confirmed tuning knobs, the open leads, and the
  method rules we learned the hard way (nested lookbacks are not out-of-sample; a
  rising win rate is a warning, not a win).
- Documents the research flags and the holdout harness, and warns that the
  portfolio_monitor lookbacks are nested windows, NOT a holdout.
- Notes the snapshot must copy paper_% settings or it silently diverges from prod.

All baseline numbers re-verified against reports/backtest-20260711-prod-baseline.json
(506 tickers, 1,089 qualified, CAGR 50.4%, +413.8% vs SPY +95.7%, DD -21.4%,
Sharpe 2.04, 320 trades, 15.3d avg hold, and all five promotion contenders). No
corrections were needed — the numbers were right, the framing was not.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-12 15:40:34 +02:00

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# Research log — what we tested, what happened, what we kept
Every strategy question we've put to the backtest, in one table. The point is to
stop re-litigating settled questions: **if a row says "rejected", the experiment
was run and the data said no.** Detail lives in the linked docs and in
`reports/*.json` (all committed).
**The one-line summary of the whole platform:** it is a **long-only
cross-sectional momentum book** — buy the top quintile by beta-adjusted 12-1
momentum, tilt toward higher volatility, hold ≤ 10 names, cut at 1.5× ATR, then
trail at 3× ATR for up to 30 trading days. Everything else in the app (composite
score, S/R levels, sentiment, fundamentals) is **display or screening**, not edge.
---
## 1. What survived — the production strategy
| Component | Status | Why it's there |
|---|---|---|
| **Residual 12-1 momentum, top 20%, long-only** | **The edge.** Everything else is scaffolding | Only component with a measured cross-sectional IC. Promoted July 2026 |
| 80/20 residual-momentum / 6m-volatility rank | Ranking tilt | Buys ~2pp CAGR over momentum-only; costs ~6pp drawdown |
| 1.5× ATR initial stop | Real exit | Cuts losers fast |
| 3× ATR trailing stop, 30-day max hold | Real exit | Best Sharpe of every exit tested |
| Max 10 concurrent positions, 1% risk per trade | Sizing | Cap never binds in practice |
---
## 2. Rejected — do not resurrect without new data
| # | Experiment | Result | Decision | Evidence |
|---|---|---|---|---|
| 1 | **S/R target as a take-profit** (exit at the target, with or without the trail) | Sharpe **2.04 → 1.47**, CAGR halved (50.4% → 28.9%). Win rate *rose* (37.5% → 40.0%) — the tell: it truncates the right tail | **Rejected.** The target must never become an exit | [sr-levels-and-exits.md](sr-levels-and-exits.md) · `backtest-20260712-sr-target-exit.json` |
| 2 | **Clear-air fallback** — synthesize a 3× ATR target so 52-week-high breakouts stop being vetoed by "no resistance above" | Looked *strictly better* in-sample (Sharpe 2.07, CAGR 62.3%, DD 20.1%) but **failed a real out-of-sample holdout**: Sharpe 2.78 → 2.45, higher drawdown | **Rejected.** Gate stays as-is | [sr-levels-and-exits.md](sr-levels-and-exits.md) · `backtest-20260712-holdout-*.json` |
| 3 | **Blanket S/R fallback** (any missing target, not just clear air) | Sharpe 1.82, per-setup expectancy 0.583 → 0.280 R | **Rejected.** 65% of what it admitted were ATR/R:R filter misses, which are actively bad | [sr-levels-and-exits.md](sr-levels-and-exits.md) |
| 4 | **Expected-value gate** (`min_expected_value` replacing the R:R + probability pair) | Structurally favoured distant lottery targets; selected *worse*-than-random setups | **Removed June 2026.** Settings dropped in migration 020 | migration 009, 020 |
| 5 | **Blue-sky projected targets** (invent a target above when none exists) | Dilutive under the ATR-trail exit | **Reverted July 2026.** Same root cause as #2 — better targets can't help when the exit ignores them | — |
| 6 | **SPY 200d-MA regime overlay** (block entries / go flat) | Halves return (315% → 138%), zero drawdown benefit | **Rejected.** The ATR trail already manages downside; the filter blocks the recovery entries that make the money | `backtest-20260708-regime-overlay.json` |
| 7 | **Short setups** | Fight the trend, drag expectancy | **Excluded** while the momentum gate is active | — |
| 8 | **Standalone volatility ranking** (high-vol 80, no momentum) | CAGR 31.6%, DD 34.8%, Sharpe 1.12 | **Rejected.** Vol is a *tilt*, not a signal | prod-baseline |
| 9 | **Low-volatility ranking** | CAGR 2.7%, Sharpe 0.29 | **Rejected.** No edge | prod-baseline |
| 10 | **Inverse-vol position sizing** | The apparent "win" was **mis-attributed**: the 20% notional cap bound on 95% of entries, so it measured concentration, not vol-sizing. Genuine inverse-vol cuts DD to 18.2% but costs ~58pp return at flat Sharpe | **Rejected** as edge; it's a risk-preference trade | `backtest-20260709-position-sizing*.json` |
| 11 | **FIP path-smoothness** as tie-breaker/filter | Non-monotonic within the qualified set; thinning the entry stream costs more compounding than the tilt returns | **Rejected as a filter** — but see §4, it's the strongest raw signal we've measured | — |
| 12 | **Fixed take-profit sweep** (R-multiples) | No interior optimum ever found — the best TP is "no TP" | **Rejected.** Momentum's edge lives in the right tail | `backtest_service.py:450` |
---
## 3. Tuned and confirmed — don't retest on this snapshot
A systematic single-variable sweep (July 2026) confirmed **every** production
setting. Re-running these against the same ~4-year snapshot is wasted compute and
invites overfitting.
| Knob | Verdict |
|---|---|
| ATR trail multiple {1.54.0} | **Keep 3.0** — ≤2.0 whipsaws out the right tail; ≥2.5 is a plateau |
| Momentum lookback (6-1, 3-1, 12-7 Novy-Marx, composites) | **Keep residual 12-1** — the others have IC ≈ 0 or weaker t-stats |
| Selection cutoff {70…90} × book size {10, 15, 20} | **Keep 80 × 10** — monotonically worse in both directions |
| Position sizing (equal-weight, inverse-vol, risk-% sweep) | **Keep 1% fixed-fractional** |
| Primary-target probability floor | **Keep 20%** — pruned lottery targets, 1,428 → 1,089 qualified, lifted Sharpe |
| Exit policy (hold / SMA50 / 20-day low / technical-40 / ATR trail) | **Keep 3× ATR trail** — best Sharpe (2.04) |
---
## 4. Open leads
| Lead | Why it's interesting | Blocker |
|---|---|---|
| **`fip_id`** (information discreteness over the 12-1 window) | **Strongest cross-sectional signal measured on this universe** — IC 0.045, t = 2.91, correct sign | Doesn't improve *this* book (the momentum gate already captures it in-sample). Revisit when the universe broadens |
| **Broader universe** (`nasdaq_all`) | Strengthens every week's cross-section and the IC t-stat | Also where `fip_id` could become tradeable |
| **Forward paper-trade record** | The only true out-of-sample evidence the snapshot cannot give | Time |
| **Better target model for clear-air names** | The return is demonstrably there (#2 wins on raw CAGR in *both* train and test); it's the *flat* 3× ATR target that makes it too expensive in risk | Needs a per-name model, not a constant k×ATR |
| **S/R detector quality** | POC/VAH/VAL computed then discarded; HVN = "any above-mean bin"; volume double-counted 1.48×; "touch" counts pass-throughs; no round numbers | Worth fixing for the levels users *see* — but it does **not** reach P&L, so don't justify it on returns |
---
## 5. Method rules learned the hard way
1. **Nested lookback windows are NOT out-of-sample.** The clear-air result (#2) was
clean, large, and consistent across five nested windows — and still died on a
proper train/test split by entry date. Use `BACKTEST_HOLDOUT_SPLIT`.
2. **Check what population an ablation actually admits.** The blanket fallback (#3)
looked like it tested the "resistance famine" hypothesis. It didn't — 65% of the
setups it let in were a different population entirely, and they drove the result.
3. **A rising win rate is a warning, not a win.** Both #1 and #12 raised the hit
rate while destroying returns. In a right-tailed strategy, "winning more often"
usually means you clipped the winners.
4. **The iron rule:** a signal earns its way into selection *only* through the
factor harness — |mean IC| ≳ 0.03, consistent sign, `reliable: true` (≥ 12
non-overlapping windows). Never let an unvalidated score gate setups.
---
## 6. Why we stay with the current strategy
Everything we've tried to add has either failed the backtest, failed
out-of-sample, or turned out to be measuring something other than what it claimed.
What's left is a boring, well-documented result: **cross-sectional momentum works;
the machinery around it mostly doesn't.**
The S/R engine, the composite score, the sentiment and fundamentals dimensions are
all still in the product — they make the app legible and are useful context for a
human — but none of them has a measured edge, and the platform is honest about
that in the UI (see the exit plan and base-rate panels on every setup card). The
one component that *does* have an edge is the momentum gate, and every knob on it
has been swept and confirmed.
The next real evidence is **forward**, not backward: the live paper-trade record.