Vexrate Ecosystem

Modular trading ecosystem / order-flow, market-context, pattern-detection and statistics suite.

Key Features

• Central Vexrate Hub for connecting indicators and routing data between modules
• Context indicators for intraday levels, session levels, VAH/VAL/POC and market structure
• Pattern indicators for candle, volume, absorption and footprint-based setup detection
• Hub Statistics module for pattern analysis, trade simulation, MAE/MFE, drawdown, calendar and research analytics
• Optional integration between context, patterns, statistics and bot logic
• Flexible Hub Scope system for separating workflows by instrument, timeframe or strategy

Overview

Vexrate Ecosystem works as a connected network of ATAS indicators. The Hub acts as the central connectivity layer: indicators that share the same Hub Scope can publish and receive data through explicit routing links. Context indicators define market structure, session levels and key price zones, while pattern indicators detect relevant setups based on price action, volume, delta, absorption and footprint behavior. This data can then be routed into the Statistics module for realistic trade simulation, filtering, performance analysis and strategy research.

Users can configure Hub Scope, routing links, enabled modules, pattern sources, market context filters, session boundaries, trend sensitivity, level visibility, volume/profile settings, pattern logic, alert behavior, and statistics simulation parameters such as stop-loss, take-profit, costs, slippage, commissions, time filters and trade direction filters.

How Traders Use It

• Build a complete discretionary trading workflow where context indicators define the market map and pattern indicators detect entry-level patterns for independent trader analysis
• Route Pattern Builder data into Hub Statistics to evaluate performance by setup, direction, session, time of day or date range
• Combine intraday levels, market structure and footprint patterns to filter weak setups and focus only on high-confluence configurations
• Separate workflows by instrument or timeframe using different Hub Scopes
• Use statistics and simulation to research whether a pattern performs better during London, New York, RTH or specific market conditions