Vexrate Ecosystem

Vexrate Ecosystem is a modular ATAS indicator suite that operates as a connected network of analytical components. The central Hub links indicators through a shared Hub Scope system, enabling structured data exchange between context, pattern and statistics modules.

Core Architecture

Vexrate Hub

The Hub serves as the central connectivity layer. Indicators sharing the same Hub Scope exchange data through explicit routing links, allowing users to build multi-layer analytical workflows across instruments, timeframes or analytical contexts. The Hub Scope system allows users to separate workflows by instrument, timeframe or analytical focus.

Context Indicators

Context indicators map the broader market environment by surfacing:

• Intraday levels and session levels
• VAH, VAL and POC
• Market structure references

These elements serve as the analytical backdrop against which pattern data is evaluated.

Pattern Indicators

Pattern indicators analyze candle, volume, delta, absorption and footprint data to surface behavioral patterns, including:

• Candle-based and price-action patterns
• Volume and delta patterns
• Absorption patterns
• Footprint-based patterns

Hub Statistics Module

The Hub Statistics module provides tools for researching pattern behavior:

• Pattern occurrence analysis
• Scenario simulation with configurable stop-loss, take-profit, costs, slippage, commissions and time filters
• MAE/MFE analysis
• Drawdown metrics
• Calendar-based breakdown
• Research analytics by direction, session, time of day or date range

Module Integration

Context indicators, pattern indicators and the Statistics module can be connected through Hub routing links. This allows users to build layered analytical workflows where structural context informs pattern evaluation, and pattern data feeds into the statistics and simulation layer.

Configuration Options

Users can configure the following across all modules:

• Hub: Hub Scope, routing links, enabled modules, data sources
• Context: session boundaries, trend sensitivity, level visibility, volume and profile settings
• Patterns: pattern logic, volume/delta/imbalance thresholds, alert behavior
• Statistics: simulation parameters including stop-loss, take-profit, costs, slippage, commissions, time filters and direction filters

Analytical Workflow Examples

• Layered analysis: Use context indicators to define the market structure map and pattern indicators to identify behavioral events at key zones.
• Pattern research: Connect pattern data to Hub Statistics to analyze pattern behavior by direction, session, time of day or date range.
• Confluence analysis: Combine intraday levels, market structure and footprint patterns to focus analysis on higher-confluence locations.
• Multi-instrument workflows: Separate analytical workflows by instrument or timeframe using different Hub Scopes.
• Condition-based research: Use simulation and statistics to research whether a pattern behaves differently during London, New York, RTH or specific market conditions.