AetherFlow AI DataBridge v1.05: Complete Feature Guide

AetherFlow AI DataBridge

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AetherFlow AI DataBridge v1.05: Complete Feature Guide

A comprehensive walkthrough of every module and feature in AetherFlow AI DataBridge for MetaTrader 5 — your complete data mining solution for Machine Learning and AI integration.

Introduction

Building effective Machine Learning models for trading requires high-quality, multi-dimensional data. Manually collecting technical indicators, price action metrics, and market structure data across multiple assets and timeframes is extremely time-consuming and error-prone.

AetherFlow AI DataBridge solves this challenge by automating the entire data collection process. This Expert Advisor mines comprehensive market data from multiple assets simultaneously, calculates advanced technical indicators, and exports everything to clean CSV files ready for your AI/ML pipelines. It does NOT execute trades — it is purely a data mining and export tool designed for quantitative analysts, algo developers, and AI researchers.

This guide covers every feature in detail, helping you configure the tool for your specific data requirements and trading research needs.

Part 1: Getting Started

Installation:

• Copy AetherFlow_AI_DataBridge.ex5 to your MQL5/Experts folder
• Restart MT5 or click "Refresh" in Navigator panel
• Drag the EA onto any chart
• Enable "Allow Algo Trading" in MT5 settings
• Configure your symbol list and export settings

Important Note: This EA does not execute any trades. It only collects and exports market data for external analysis.

Output Location:

By default, CSV files are saved to the MT5 Common Folder. You can find this folder by clicking File → Open Data Folder → MQL5 → Files, or if UseCommonFolder is enabled, the files go to the terminal's common files directory accessible by all MT5 installations.

Output File	Description
AetherFlow_YYYY-MM-DD.csv	Main data export file with all metrics
AetherFlow_AI_Prompt.txt	AI prompt template for data interpretation
AetherFlow_YYYY-MM-DD_snapshot_N.csv	Time Lapse archive files (when enabled)

Part 2: Symbol Configuration

Multi-Asset Data Mining

AetherFlow can simultaneously collect data from multiple trading instruments. You can analyze forex pairs, commodities, indices, and cryptocurrencies in a single export.

SymbolsList — Enter your desired symbols separated by commas. The EA automatically detects and adapts to your broker's symbol naming convention (suffixes like .p, m, +, etc.).

UseChartSymbolOnly — Set to true if you only want to collect data for the chart's current symbol. Useful for focused single-asset analysis.

Broker Symbol Auto-Detection:

The EA intelligently detects your broker's symbol format. If your broker uses EURUSD.p or EURUSDm instead of EURUSD, the EA automatically maps standard symbol names to your broker's format.

Part 3: Timing Configuration

Export Scheduling

Control how frequently data is collected and exported to CSV files.

ExportIntervalMinutes — Sets the interval between data exports in minutes. For example, setting 15 means data is exported every 15 minutes. Shorter intervals provide more granular data but larger file sizes.

ExportOnInit — When enabled, the EA immediately exports data when first attached to the chart, giving you instant data without waiting for the next scheduled interval.

Part 4: OCM - Omni-Currency Matrix (Currency Strength)

Currency Strength Analysis

The OCM module calculates relative strength for major currencies (USD, EUR, GBP, JPY, AUD, NZD, CAD, CHF) by analyzing their performance across multiple pairs.

OCM_Period — Number of bars used for strength calculation. Higher values provide smoother, more stable readings; lower values are more responsive to recent changes.

OCM_ScalingFactor — Adjusts the output scale. With normalization enabled, values are scaled to 0-100 range.

OCM_UseNormalization — When true, normalizes all currency strength values to a 0-100 scale for easier comparison and ML model training.

Output Columns: The CSV includes strength values for each major currency (OCM_USD, OCM_EUR, OCM_GBP, etc.) plus the strength values for base and quote currencies of each analyzed pair.

Part 5: IVC - Intrinsic Velocity Core (Momentum)

Momentum Analysis

The IVC module measures price momentum relative to a baseline moving average, normalized by volatility (ATR).

IVC_MA_Period — Period for the Linear Weighted Moving Average (LWMA) baseline. This serves as the reference point for momentum calculation.

IVC_ATR_Period — Period for ATR calculation used in volatility normalization.

IVC_K_Factor — Sensitivity multiplier. Higher values reduce sensitivity; lower values increase it.

IVC_Smooth_Period — EMA smoothing period applied to the final IVC output to reduce noise.

Output Range: IVC values are clamped between -5.0 and +5.0, where positive values indicate bullish momentum and negative values indicate bearish momentum.

Part 6: Volume and Sentiment Analysis

Volume-Based Metrics

This module analyzes tick volume patterns to identify accumulation, distribution, and volume anomalies.

EnableVolumeSentiment — Toggle volume analysis on/off.

Volume_MA_Period — Period for calculating average volume baseline.

Volume_Spike_Threshold — Multiplier to identify volume spikes. A value of 2.0 means volume must be 2x the average to be flagged as a spike.

Volume_Trend_Period — Lookback period for determining if volume is trending up or down.

Volume_Sentiment_Period — Period for calculating buying vs selling pressure sentiment.

Output Columns: Volume_Ratio, Volume_Spike (0/1), Volume_Trend (-1/0/1), Sentiment (-100 to +100).

Part 7: Stochastic and CCI Indicators

Oscillator Analysis

Standard oscillators included for overbought/oversold detection and momentum confirmation.

Stochastic Parameters — Standard stochastic oscillator configuration. %K and %D values are exported for each symbol.

CCI Parameters — Commodity Channel Index settings. CCI values help identify cyclical trends and extreme conditions.

Output Columns: Stoch_K, Stoch_D, CCI for each symbol.

Part 8: Auto Support/Resistance Detection

Fractal-Based S/R Levels

Automatically detects significant support and resistance levels using fractal analysis.

Fractal_Period — Number of bars on each side required to confirm a fractal point.

SR_Lookback — How many bars back to search for S/R levels.

SR_Max_Levels — Maximum number of support and resistance levels to detect (each side).

SR_Zone_ATR_Multi — Defines the zone width around each level as a multiple of ATR.

SR_Min_Touches — Minimum number of price touches required to confirm a level.

Output Columns: Support_1, Support_2, Support_3, Resistance_1, Resistance_2, Resistance_3, plus distance-to-level metrics.

Part 9: Bid/Ask Spread Analysis

Spread Monitoring

Captures real-time bid and ask prices separately for spread analysis.

When enabled, the CSV includes separate columns for Bid price, Ask price, and calculated Spread. This data is valuable for analyzing execution costs and liquidity conditions.

Part 10: Volatility Score Analysis

Volatility Regime Detection

Classifies current volatility relative to historical norms using percentile rankings.

Volatility_ATR_Period — ATR period for current volatility measurement.

Volatility_Lookback — Historical bars to compare against for percentile calculation.

Volatility_High_Pct / Volatility_Low_Pct — Threshold percentiles for classifying volatility as High, Normal, or Low.

Output Columns: Volatility_Score (percentile 0-100), Volatility_Regime (High/Normal/Low).

Part 11: Time Lapse Archive Mode

Historical Snapshot Recording

Creates periodic snapshots of all data for building historical datasets.

EnableTimeLapse — Activates time lapse archiving mode.

TimeLapse_Interval — Timeframe interval for snapshots (M1, M5, M15, H1, H4, D1).

TimeLapse_SeparateFiles — When true, creates individual files for each snapshot; when false, appends to a single file.

TimeLapse_Suffix — Custom suffix added to snapshot filenames for organization.

Part 12: SMC Liquidity Analysis

Smart Money Concepts Integration

Identifies swing highs/lows that represent potential liquidity pools.

SMC_Lookback — Number of bars to search for swing points.

SMC_SwingStrength — Bars required on each side to confirm a swing high or low.

Output Columns: Swing_High, Swing_Low, Distance_to_Swing_High, Distance_to_Swing_Low (in pips).

Part 13: Multi-Timeframe Technical Indicators

MTF Data Collection

Collects indicator values across multiple timeframes for each symbol.

Standard Indicator Parameters:

Output Columns: For each enabled timeframe, the CSV includes RSI, MACD (main/signal/histogram), Bollinger Band position, ADX, Supertrend direction, Ichimoku signals, and trend direction.

Part 14: Trend Analysis

Trend Direction Detection

Trend_Lookback — Number of bars for trend calculation.

Trend_MA_Method — Moving average method (SMA, EMA, SMMA, LWMA).

Output: Trend direction values (-1 = Bearish, 0 = Neutral, 1 = Bullish) for each timeframe.

Part 15: Output Configuration

File Naming and Format

CSV_FilePrefix — Prefix for output files. Date is automatically appended.

Prompt_FileName — Filename for the AI prompt template that helps interpret the data.

UseCommonFolder — Save to MT5 common folder (accessible by all terminals) or local data folder.

WriteHeader — Include column headers in the first row of CSV files.

CSV_Delimiter — Character separating values (comma, semicolon, tab).

Part 16: File Rotation and Cleanup

Automatic File Management

EnableDailyRotation — Creates a new file each day with date-stamped filename.

MaxDaysToKeep — Automatically deletes files older than this many days. Set to 0 for unlimited retention.

AutoCleanupOnStart — Runs cleanup routine when EA is initialized.

Part 17: Configuration Examples

Machine Learning Training Setup

Real-Time AI Feed Setup

Currency Strength Research Setup

Part 18: Data Column Reference

Core Columns (Always Included):

Column	Description
Timestamp	Export datetime
Symbol	Trading instrument
Bid / Ask / Spread	Current prices and spread
OCM_[Currency]	Currency strength values
IVC	Momentum value
RSI_[TF]	RSI per timeframe
MACD_[TF]	MACD values per timeframe
Trend_[TF]	Trend direction per timeframe
Volatility_Score	Percentile ranking
Support_N / Resistance_N	Detected S/R levels
Swing_High / Swing_Low	SMC liquidity levels

Conclusion

AetherFlow AI DataBridge provides professional-grade data mining capabilities for quantitative traders and AI researchers:

• Multi-Asset Coverage — Simultaneously collect data from forex, commodities, indices, and crypto
• Comprehensive Metrics — Currency strength, momentum, volume, volatility, and technical indicators
• Multi-Timeframe Analysis — M5 to D1 data in a single export
• SMC Integration — Swing highs/lows and liquidity pool detection
• AI-Ready Output — Clean CSV format with consistent column structure
• Automatic Management — Daily rotation and cleanup keep your data organized

The key to success is matching your configuration to your research goals. Start with the default settings, verify data quality in your ML pipeline, then customize parameters as you refine your models.

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