NEW IN v0.3.5 · CORTEX OEM AI

Cortex AI Strategy for NinjaTrader 8 — self-optimizing orders

v0.5.3 · 14 OEM actions · 5-Filter stack · Reinforcement Learning

NinjaTrader 8 · ES 06-26 · Cortex OEM AI v0.5.3
7426.00 7421.00 7416.00 7411.00 ENTRY 7418.50 BE-LOCK T1 ▣ 7423.50 T2 → 7428.50 SL 7411.00 CORTEX OEM AI Strategy v0.5.3 RISK MODE MODERATE 80% WR target DAY P&L +$1,247.50 12W / 3L · 80.0% OEM · LIVE Action STOP_TIGHTEN Weight 1.44 → 1.56 NET SAVED +$420 LEARNING · 72% · 248 trades
The Problem

Manual order management costs 30–60 % of your profit

You spot the setup. You enter. Then the stress begins: move the stop, set a partial exit, trail the runner, evaluate re-entry. Three manual decisions per trade — all under time pressure.

▸ PROBLEM #1

Stops moved too early or too late

Break-even lock on gut feeling. Trailing by hand. With a 4-tick drawdown you push the stop into profit — and get stopped out right there. With a runner, you keep the stop too wide and give back half the gain.

▸ PROBLEM #2

Setups without pre-entry filtering

Low ATR + Wyckoff range + POC pin — an experienced trader would skip all three. But in real time you cannot read that constellation. Result: trades in dead phases with negative expectancy.

▸ PROBLEM #3

No learning loop — every day starts at zero

You lose three times in a row with the same signal constellation. But tomorrow you take the same setup again. Without structured outcome analysis you repeat your patterns — the bad ones too.

How the AI works

Three protection layers between your capital and a bad trade

Cortex OEM AI intervenes in three places: before entry, during the trade, and after the trade. Every layer is measurable, visible in the NT8 chart, and configurable.

LAYER 01

5-Filter Stack before every entry

Five parallel hard filters check every setup before an order is submitted. Trades in toxic market phases are blocked — not executed and rescued afterwards, but never entered in the first place.

  • Low-ATR Filter (minimum volatility)
  • Wyckoff Conflict (regime vs. phase)
  • POC Pin Filter (±3 ticks from POC)
  • Counter-Regime Defense (aiConf gate)
  • Wyckoff Trap (SHORT+ACCUM, LONG+DIST)
LAYER 02

14 OEM actions during the trade

The strategy adapts stop, targets, and trail logic live — based on Wyckoff regime, magnet position (DOM/iceberg), and trade maturity. Pre-T1 BE-Lock secures profits at 10 ticks MFE.

  • STOP_TIGHTEN / STOP_LOOSEN
  • MOVE_TO_BE / TRAIL_AGGRESSIVE
  • T2_PULL_IN / T2_EXTEND
  • QUICK_PROFIT / PARTIAL_EXIT
  • PRE_STOP_EXIT / RE_ENTRY
LAYER 03

Reinforcement Learning after every trade

Every trade outcome feeds the RL engine. Signal-regime keys (e.g. Dlt_TREND_BEAR) get weights between 0.1 and 3.0. Pretrained bundle with 345 trades + 17 keys from day one.

  • strategy_learn.json (user-persistent)
  • NET SAVED lock-in credit
  • Counterfactual V2 for PRE_STOP_EXIT
  • Magnet Gate (DOM/iceberg bypass)
  • Pretrained Safe / Moderate / Aggressive
Live in the trade

A real trade path — from setup to lock-in

Example trade from 2026-05-21, 17:36 CEST: LONG OFA_Normal during the Lunch phase. Four OEM actions fired in parallel and secured +$325 net profit.

Bracket · OEM Action Trail
7424 7422 7420 7418 7416 7414 ENTRY 7418 BE T1 7422 T2 7425 SL 7416 PHASE-T1-SHRINK PRE-T1 BE-LOCK T1 FILL STOP_TIGHTEN 17:36 ENTRY +$325 NET

4 OEM actions in 9 minutes

The strategy detected the LUNCH phase + NEUTRAL regime and shrunk T1 to 12 ticks (instead of 14). At 9 ticks MFE the pre-T1 BE-Lock fired automatically and secured the stop at break-even. After T1 fill, STOP_TIGHTEN set the trail to +11 ticks lock-in.

  • 17:36:04 · PHASE-T1-SHRINKLunch × NEUTRAL = 0.80 · T1 14T → 12T, BeTrigger 11T → 9T
  • 17:38:22 · PRE-T1 BE-LOCKMFE = 9.0T = BeTrigger · Stop 7416 → 7418.50 (BE+0.5T)
  • 17:41:55 · T1-FILLLimit @ 7422 filled · quantity halved, runner active
  • 17:43:18 · OEM STOP_TIGHTENLock-in +11T · weight 1.44 → 1.56 (regime match)
  • 17:45:09 · EXITRunner stop fired · net +$325 · NET SAVED +$420 vs. default trail
The numbers

What the code says, not what marketing claims

Every value in this table is directly verifiable in Strategy v0.5.3 — not from backtest marketing or estimated assumptions.

14x
OEM Actions
5/5
Pre-Entry Filters
3
Risk Modes
345+
Pretrained Trades
17
Signal-Regime Keys
v0.5.3
Production
15min
Open Guard
PRO
Plan exclusive
FAQ

Common questions about Cortex AI Strategy

Most traders ask the same six questions before running the strategy live. Here are the answers.

Which risk modes exist and how do they differ?

The Cortex AI Strategy ships with three preconfigured modes: SAFE with an 85 % win-rate target, MODERATE with 80 %, and AGGRESSIVE with 70 %. Safe adds +2 to the minimum score threshold and +1 to required signal sources, and makes the AI gate mandatory. Moderate softens this to a soft AI gate. Aggressive leaves OEM pre-entry unchanged.

Recommendation for the first 2–3 trading weeks: MODERATE. Once your own RL data is collected and you understand the logs, switch to AGGRESSIVE.

What is the pretrained bundle and do I need it?

On first launch of the Pro app, a pretrained strategy_learn.json (345 trades, 17 signal-regime keys) is automatically copied to your user folder. This gives the RL engine sensible weights from day one instead of starting from scratch.

You can choose between three pretrained modes (Safe, Moderate, Aggressive). Default: Moderate. Existing strategy_learn.json files are never overwritten — your own RL data is safe.

How exactly does the pre-T1 BE-Lock work?

As soon as the trade reaches an MFE (maximum favorable excursion) equal to the BeTrigger, the strategy automatically moves the stop to break-even +0.5 ticks. This happens before T1 fill — not afterwards.

In Lunch and Afternoon phases with NEUTRAL or RANGE regime, a matrix additionally shrinks the BeTrigger (e.g. Lunch × NEUTRAL = 0.80, so BeTrigger 11T → 9T). Result: smaller trades are protected earlier.

What is the Magnet Gate and why is it a bypass?

The indicator writes an indicator_magnet_state.json every 500 ms with DOM aggregation and iceberg position from the order book. The Magnet Gate reads this file: if a massive liquidity magnet (DOM cluster + iceberg) lies in trade direction above the entry AND your MFE is ≥ 8 ticks, the PRE_STOP_EXIT logic is deliberately skipped.

Reasoning: in this constellation the market wants to push higher. An early exit would undermine the reversal USP of the CORTEX engine.

Which instruments does the strategy run on?

Primarily tested and tradeable on ES (E-Mini S&P 500) and NQ (Nasdaq Futures). Session detection runs in NY time (see GetETTod()), display in your NT8 timezone.

Crude Oil (CL) and MES/MNQ work as well, but the default bracket values (SL/T1/T2 in ticks) are calibrated to the ES tick value. For smaller/larger tick values, adjust the RegimeBrackets dict defaults.

Which plan do I need and what does the strategy cost?

The Cortex AI Strategy is exclusive to the Pro plan. Trial and Starter only ship the indicator (Pro adds Strategy + Heatmap + pretrained bundle).

Pro pricing: €99/month, €890/year (instead of €1,188) or €2,997 Founder Lifetime (1/5 sold). All prices exclude 21 % IVA. 14-day trial with indicator-only available.