Risk Management EA for FTMO and to pass the challenge - Control external EAs to not break the FTMO rules

Please explain all the details, including the entry and exit conditions . Refine signal trigger execution . Optimize live chart performance . Ensure stable and clean code structure : Stable and clean code is important . Otherwise its a mess . Apply with as much accurate structure you foresee . requests for details of the project will be ignored

99.99% signal accuracy 10-15 trades distribution all currency trade and meta AI assistance on loss[advice] stop and start robot cyber security firewall protection activation code: 20060605TLP20 Please create a trading bot with any logo with the name elevation

Refine signal trigger execution . Optimize live chart performance . Ensure stable and clean code structure : Stable and clean code is important . Otherwise its a mess . Apply with as much accurate structure you foresee

This post is subject to developers response . Edit the post as you like . May be with me you can make a come back . So , , , Shift calculations . More to the calculation then you can comprehend is known . What else comes to your mind

All other Necessary filters already coded , Mostly it is referring to another expert copy pasting . Live Chart Optimization . Optimization from Signal Trigger Point . Apply to stay ahead . While applying please explain the correct trailing stop loss for value gap entries

1️⃣ System Architecture An AI robot typically consists of the following subsystems: 🔹 1. Perception Layer Collects environmental data using: RGB / Depth cameras LiDAR Ultrasonic sensors IMUs (Inertial Measurement Units) Microphones Data is processed using: Computer Vision (e.g., object detection, SLAM) Signal processing Sensor fusion algorithms 🔹 2. Cognition / Intelligence Layer Implements AI models such as

Trailing Stop Based on Thresholds . Other Necessary Filters already Coded . Live Chart Only . The strategy already coded - needs a fresh new draft . To Start from Signal Trigger

The trading bot is an automated software system designed to monitor financial markets, execute trades, and manage risk based on predefined strategies. The bot aims to maximize profits while minimizing human intervention and emotional decision-making. Scope: Supports automated trading on selected exchanges (e.g., Binance, Bitget, Coinbase). Executes trades based on technical indicators, signals, or AI models. Provides

I need help in modifying an amibroker AFL indicator the indicator already works but I need per symbol static variable isolation, parameters persistence per symbol after restart, non declining trailing stop logic, parameter auto restore when switching symbols and a global reset function for static variables. For better understanding As discussed, this is the official offer for restructuring my RAD Chandelier stop loss

mport pandas as pd import numpy as np def detecter_tendance(data): # Code pour détecter la tendance pass def identifier_niveaux(data): # Code pour identifier les niveaux de support et de résistance pass def calculer_stop_loss(tendance, support, resistance): # Code pour calculer les stop loss pass def calculer_profils(tendance, support, resistance): # Code pour calculer les profils mport pandas as pd