FONFLO LAB

A research engine that re-validates working ES futures strategies against fresh market data every few hours. An edge that worked last month must keep working this month, or it gets killed. Survivors graduate to live signals; degraders are demoted; new candidates are tested only when the data demands it.

5530

Tested

Survivors

5487

Killed

Re-tested 24h

Live

99%

Kill Rate

The Pipeline

Re-validate, re-validate, re-validate.

The cheap thing here is compute — the expensive thing is paid Databento data. So the lab spends compute aggressively. Every working strategy gets re-tested against the latest market data on a continuous loop, and grade transitions are logged. Strategies prove their edge in the present, not just the past.

Continuous Re-Validation

Every Grade C+ strategy is re-run on the latest 370,000+ bars of ES 1-min Databento data on a free, all-day loop. Each run produces a fresh grade, logged to regrader_history.csv. Strategies that degrade get demoted automatically; strategies that strengthen are flagged for promotion. The grade you see is current, not stale.

Walk-Forward Backtest

370,000+ bars of ES 1-min OHLCV from Databento (CME-direct). Train on months 1-4, test on months 5-6 (strict out-of-sample). Entry: t+1 bar open (zero lookahead). Stops: checked intrabar on bar H/L, not close. Slippage: 0.25 pts per side. Commission: $4.50 RT. Minimum sample: 30 in-sample, 20 OOS.

Monte Carlo Random Entry Control

200 iterations of randomized entries on the same trading days with identical stop/target distances. Computes the full distribution of random P&L. If the signal doesn't beat random by 2x+ (Grade A) or 1x+ (Grade B), the apparent "edge" is just the payoff structure. This separates signal alpha from mechanical R:R.

VIX Regime Decomposition

Win rate and profit factor decomposed across VIX <16 (low vol), VIX 16-22 (normal), VIX >22 (elevated). Wilson score 95% confidence intervals on each bucket. A strategy that only works in one regime is a conditional bet, not a robust edge. We encode the optimal regime as a production filter.

Day-Type Classification

Every session is classified into one of six day types: Trend, Trend From Open, Balance Narrow, Balance Wide, Reversal, or Late Break. A mean reversion strategy that works on balance days will get destroyed on a trend day. We test every strategy across all six types and only deploy it on day types where it's proven. In production, the classifier runs in real-time — updating probabilities at 9:45, 10:30, 12:00, and 14:00 ET as the session develops.

Grade Assignment

A: Full PF >1.5, OOS PF >1.3, OOS WR >50% (Wilson CI), edge >2x random, n ≥ 30/20. B: Full PF >1.3, OOS PF >1.0, OOS WR >45%, edge >1x, n ≥ 25/15. F: No edge — killed, logged, fed back as a negative constraint.

Deep Analysis + Production

Survivors enter contextual enrichment — every trade tagged with opening type, IB classification, VIX regime, day of week, gap direction, session range percentile. Win rates decomposed across 7 dimensions. Top conditions extracted as production filters. Strategy only fires on days matching its proven edge. First 10 trades on probation — tighter kill threshold. Dormant after 15 days without firing. Audited daily, auto-killed if PF degrades.

Real-Time Context

The system knows what kind of day it is.

Most signal services treat every day the same. We don't. The day-type classifier runs in real-time, updating its read on the session at four checkpoints as data accumulates:

9:45 ET — Opening type classified. If it's a drive open, trend probability increases. If price opens inside prior range, balance probability increases.
10:30 ET — Initial balance set. Narrow IB + auction open = likely balance day. Wide IB + drive = likely trend. Probabilities sharpen.
12:00 ET — Has IB been broken? One side or both? How many VWAP crosses? By noon, most day types are identifiable with 70%+ confidence.
14:00 ET — If still in balance, late break probability rises. If trending, trend day confirmed. Classification at 85%+ confidence.

Mean reversion strategies are suppressed when trend probability exceeds 50%. Continuation strategies are boosted when trend probability exceeds 40%. The system doesn't fight the tape — it reads the tape and adapts.

Production Pipeline

Promotion is just the beginning.

Grade A/B strategies go straight to production — no waiting room. The first 10 trades are a probation period with a tighter kill threshold: PF drops below 1.0 after 5 trades and it's killed immediately. After probation, the normal audit applies — PF below 0.8 = degraded, below 0.6 after 30 = auto-killed. If a strategy goes 15 trading days without firing a single signal, it's flagged as DORMANT — the conditions it was built for may not exist in the current market.

VIEW PRODUCTION TRACKING →

Transparency

Every signal has a paper trail.

Trace any signal back through the pipeline — the AI hypothesis, the backtest, the random control, the regime it's optimized for, and the live trades since promotion. Nothing hidden. The kills are published alongside the wins.

Data Stack

What feeds the engine.

Primary: Databento — CME-direct 1-min OHLCV, full year continuous front-month ES, append-on-close daily. Live quotes: Schwab API for current price + DOM. Analysis: Cumulative delta, session VWAP, volume profile (VPOC/VAH/VAL), initial balance classification, opening type detection, regime detection via 10/30-bar ATR ratio. Spend posture: Databento is paid, so we hammer it — backtests run continuously, free of LLM cost. New-strategy invention runs at most once per day.

DASHBOARD

Live results feed, grades, strategy cards

SCOREBOARD

Full data table, regime heatmap, sorting

PRODUCTION

Live tracking, audit log, kill history