Логотип продукта "LSBotPro"
сиБот
Версия 1.0, Sep 2025
Windows, Mac, Mobile, Web
Загруженное изображение продукта "LSBotPro"
Загруженное изображение продукта "LSBotPro"
С 26/08/2025

LSBotPro (Lean Price Action) is an automated trading robot built for cTrader/cAlgo that scans price action, qualifies trades using layered “gates,” sizes positions using structured risk rules, manages open trades with profit-protection logic, and continuously records outcomes to improve selectivity over time.

1) Core Strategy: Price-Action Pattern Trading

LSBotPro’s entries are driven by candlestick structure and controlled execution logic. It detects and scores:

  • Pin Bars (wick/body ratio + close position quality)
  • Engulfing patterns (body dominance + direction)
  • Inside Bars (strict containment + optional breakout confirmation)

It supports two entry styles:

  • Next-Open entry (enter after a confirmed closed candle pattern)
  • Breakout mode (enter only when price closes beyond the Inside-Bar “mother bar” range, with optional intrabar logic)

2) Market Filters (Trade Qualification Gates)

Before any order is placed, LSBotPro applies multiple filters designed to avoid low-quality conditions:

  • ATR volatility bounds (min/max ATR in pips) to avoid dead or chaotic markets
  • Spread gate (blocks trades when spread exceeds the defined threshold)
  • EMA confluence filter (optional): checks trend side, EMA slope, and distance from EMA with a configurable minimum score
  • Multi-timeframe bias (optional): confirms direction using H4/D1 EMA or candle bias
  • Session & rollover controls: avoids weekends, Friday close, Sunday open, and optionally the rollover window
  • Setup freshness + one-trade-per-setup lock to reduce duplicates and overtrading

3) Risk Management & Exposure Control

LSBotPro’s risk engine is designed to control drawdowns and limit account exposure:

  • Risk-percent sizing (position size derived from risk %, SL distance, pip value)
  • Risk budget caps: maximum open risk % (sum of conceptual risks across positions)
  • Daily loss limit + daily trade cap (hard block on new entries when exceeded)
  • Concurrency limits: max positions per symbol/account, plus direction caps
  • Volatility regime scaling: adjusts risk and RR dynamically using ATR / ATR-SMA50 (low-vol vs high-vol regimes)
  • Equity-curve filter: tracks recent R-multiples and blocks trading if performance deteriorates beyond a configured threshold

4) Stop-Loss Safety Model (Current Build)

This build has a very specific safety posture:

  • Broker stop-loss is disabled (the bot intentionally does not send SL to the broker and clears existing SLs).
  • TP is still used (take-profit is placed in pips).
  • If TP-Only Mode = true:
    • The bot will not auto-close losing trades under any condition.
    • Only manual actions can close losers; auto-flatten closes winners only.
  • If TP-Only Mode = false:
    • The bot can optionally manage exits locally with virtual stop / trailing concepts (still no broker SL), plus break-even/trailing/chandelier logic when enabled.

This design makes the bot heavily reliant on discipline, monitoring, and correct configuration, especially when TP-only is active.

5) Trade Management (Profit Protection & Exit Intelligence)

For open positions (when not in TP-only and while in profit), LSBotPro runs structured exit logic:

  • Profit milestone alerts (sound notifications):
    • first closed bar into profit
    • first time price reaches ≥50% progress toward TP
  • Progress-drop / giveback logic (“profit maximiser”): arms after strong progress toward TP, then exits on stall + meaningful giveback + weakness confirmation
  • Cortex exit engine (“neurons”) that votes on exit using:
    • Progress/giveback behaviour
    • Structure breaks
    • Momentum shifts
    • Trend slope invalidation (veto-capable)
    • Recall-based exit pressure

6) Memory / Recall (Learning From Similar Trades)

LSBotPro includes a trade memory + recall gate:

  • Stores trade “snapshots” (features at entry + outcomes) and retrieves similar historical trades
  • Uses historical similarity to compute:
    • win-rate confidence
    • expected edge (pips)
    • similar trade count
  • Can block trades if recall confidence/edge is weak (after warm-up), or fail-open during early learning.
  • Memory can run file-based (JSONL) if file access is allowed; otherwise it runs in RAM.

7) Telemetry & Observability (UI/Monitoring Ready)

LSBotPro can publish telemetry to an external observer service (local or remote), including:

  • Bot status + last decision (ALLOW/REJECT) and reasons
  • Current positions snapshots (pips, money, risk pips, side, symbol)
  • Trade lifecycle events (open/close)
  • Learning summary metrics (e.g., best pattern, worst context, total learned trades)

8) Manual Operator Controls

The bot supports operator intervention without recompiling:

  • Pause/resume entries (manual or auto-pause)
  • Close newest, close one, or close all
  • Hotkeys (when running with a chart)
  • Shadow logs for diagnostic reasons (why trades were blocked/rejected)


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