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AetherFlow AI DataBridge

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AetherFlow AI DataBridge v1.05: Full Function Information

A complete walkthrough of each module and have in AetherFlow AI DataBridge for MetaTrader 5 — your full information mining answer for Machine Studying and AI integration.

Introduction

Constructing efficient Machine Studying fashions for buying and selling requires high-quality, multi-dimensional information. Manually gathering technical indicators, worth motion metrics, and market construction information throughout a number of belongings and timeframes is extraordinarily time-consuming and error-prone.

AetherFlow AI DataBridge solves this problem by automating the complete information assortment course of. This Knowledgeable Advisor mines complete market information from a number of belongings concurrently, calculates superior technical indicators, and exports every thing to wash CSV information prepared on your AI/ML pipelines. It does NOT execute trades — it’s purely a knowledge mining and export device designed for quantitative analysts, algo builders, and AI researchers.

This information covers each function intimately, serving to you configure the device on your particular information necessities and buying and selling analysis wants.

Half 1: Getting Began

Set up:

• Copy AetherFlow_AI_DataBridge.ex5 to your MQL5/Consultants folder
• Restart MT5 or click on “Refresh” in Navigator panel
• Drag the EA onto any chart
• Allow “Enable Algo Buying and selling” in MT5 settings
• Configure your image record and export settings

Essential Be aware: This EA doesn’t execute any trades. It solely collects and exports market information for exterior evaluation.

Output Location:

By default, CSV information are saved to the MT5 Frequent Folder. You could find this folder by clicking File → Open Knowledge Folder → MQL5 → Information, or if UseCommonFolder is enabled, the information go to the terminal’s frequent information listing accessible by all MT5 installations.

Half 2: Image Configuration

Multi-Asset Knowledge Mining

AetherFlow can concurrently acquire information from a number of buying and selling devices. You may analyze foreign exchange pairs, commodities, indices, and cryptocurrencies in a single export.

SymbolsList — Enter your required symbols separated by commas. The EA mechanically detects and adapts to your dealer’s image naming conference (suffixes like .p, m, +, and many others.).

UseChartSymbolOnly — Set to true when you solely wish to acquire information for the chart’s present image. Helpful for targeted single-asset evaluation.

Dealer Image Auto-Detection:

The EA intelligently detects your dealer’s image format. In case your dealer makes use of EURUSD.p or EURUSDm as a substitute of EURUSD, the EA mechanically maps commonplace image names to your dealer’s format.

Half 3: Timing Configuration

Export Scheduling

Management how incessantly information is collected and exported to CSV information.

ExportIntervalMinutes — Units the interval between information exports in minutes. For instance, setting 15 means information is exported each quarter-hour. Shorter intervals present extra granular information however bigger file sizes.

ExportOnInit — When enabled, the EA instantly exports information when first hooked up to the chart, supplying you with prompt information with out ready for the subsequent scheduled interval.

Half 4: OCM – Omni-Foreign money Matrix (Foreign money Power)

Foreign money Power Evaluation

The OCM module calculates relative energy for main currencies (USD, EUR, GBP, JPY, AUD, NZD, CAD, CHF) by analyzing their efficiency throughout a number of pairs.

OCM_Period — Variety of bars used for energy calculation. Greater values present smoother, extra secure readings; decrease values are extra conscious of latest adjustments.

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

OCM_UseNormalization — When true, normalizes all forex energy values to a 0-100 scale for simpler comparability and ML mannequin coaching.

Output Columns: The CSV consists of energy values for every main forex (OCM_USD, OCM_EUR, OCM_GBP, and many others.) plus the energy values for base and quote currencies of every analyzed pair.

Half 5: IVC – Intrinsic Velocity Core (Momentum)

Momentum Evaluation

The IVC module measures worth momentum relative to a baseline shifting common, normalized by volatility (ATR).

IVC_MA_Period — Interval for the Linear Weighted Transferring Common (LWMA) baseline. This serves because the reference level for momentum calculation.

IVC_ATR_Period — Interval for ATR calculation utilized in volatility normalization.

IVC_K_Factor — Sensitivity multiplier. Greater values cut back sensitivity; decrease values improve it.

IVC_Smooth_Period — EMA smoothing interval utilized to the ultimate IVC output to cut back noise.

Output Vary: IVC values are clamped between -5.0 and +5.0, the place optimistic values point out bullish momentum and adverse values point out bearish momentum.

Half 6: Quantity and Sentiment Evaluation

Quantity-Based mostly Metrics

This module analyzes tick quantity patterns to establish accumulation, distribution, and quantity anomalies.

EnableVolumeSentiment — Toggle quantity evaluation on/off.

Volume_MA_Period — Interval for calculating common quantity baseline.

Volume_Spike_Threshold — Multiplier to establish quantity spikes. A price of two.0 means quantity should be 2x the typical to be flagged as a spike.

Volume_Trend_Period — Lookback interval for figuring out if quantity is trending up or down.

Volume_Sentiment_Period — Interval for calculating shopping for vs promoting strain sentiment.

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

Half 7: Stochastic and CCI Indicators

Oscillator Evaluation

Commonplace oscillators included for overbought/oversold detection and momentum affirmation.

Stochastic Parameters — Commonplace stochastic oscillator configuration. %Ok and %D values are exported for every image.

CCI Parameters — Commodity Channel Index settings. CCI values assist establish cyclical traits and excessive situations.

Output Columns: Stoch_K, Stoch_D, CCI for every image.

Half 8: Auto Help/Resistance Detection

Fractal-Based mostly S/R Ranges

Mechanically detects vital help and resistance ranges utilizing fractal evaluation.

Fractal_Period — Variety of bars on all sides required to verify a fractal level.

SR_Lookback — What number of bars again to seek for S/R ranges.

SR_Max_Levels — Most variety of help and resistance ranges to detect (all sides).

SR_Zone_ATR_Multi — Defines the zone width round every degree as a a number of of ATR.

SR_Min_Touches — Minimal variety of worth touches required to verify a degree.

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

Half 9: Bid/Ask Unfold Evaluation

Unfold Monitoring

Captures real-time bid and ask costs individually for unfold evaluation.

When enabled, the CSV consists of separate columns for Bid worth, Ask worth, and calculated Unfold. This information is efficacious for analyzing execution prices and liquidity situations.

Half 10: Volatility Rating Evaluation

Volatility Regime Detection

Classifies present volatility relative to historic norms utilizing percentile rankings.

Volatility_ATR_Period — ATR interval for present volatility measurement.

Volatility_Lookback — Historic bars to check in opposition to for percentile calculation.

Volatility_High_Pct / Volatility_Low_Pct — Threshold percentiles for classifying volatility as Excessive, Regular, or Low.

Output Columns: Volatility_Score (percentile 0-100), Volatility_Regime (Excessive/Regular/Low).

Half 11: Time Lapse Archive Mode

Historic Snapshot Recording

Creates periodic snapshots of all information for constructing historic datasets.

EnableTimeLapse — Prompts time lapse archiving mode.

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

TimeLapse_SeparateFiles — When true, creates particular person information for every snapshot; when false, appends to a single file.

TimeLapse_Suffix — Customized suffix added to snapshot filenames for group.

Half 12: SMC Liquidity Evaluation

Good Cash Ideas Integration

Identifies swing highs/lows that signify potential liquidity swimming pools.

SMC_Lookback — Variety of bars to seek for swing factors.

SMC_SwingStrength — Bars required on all sides to verify a swing excessive or low.

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

Half 13: Multi-Timeframe Technical Indicators

MTF Knowledge Assortment

Collects indicator values throughout a number of timeframes for every image.

Commonplace Indicator Parameters:

Output Columns: For every enabled timeframe, the CSV consists of RSI, MACD (predominant/sign/histogram), Bollinger Band place, ADX, Supertrend course, Ichimoku alerts, and pattern course.

Half 14: Development Evaluation

Development Route Detection

Trend_Lookback — Variety of bars for pattern calculation.

Trend_MA_Method — Transferring common technique (SMA, EMA, SMMA, LWMA).

Output: Development course values (-1 = Bearish, 0 = Impartial, 1 = Bullish) for every timeframe.

Half 15: Output Configuration

File Naming and Format

CSV_FilePrefix — Prefix for output information. Date is mechanically appended.

Prompt_FileName — Filename for the AI immediate template that helps interpret the info.

UseCommonFolder — Save to MT5 frequent folder (accessible by all terminals) or native information folder.

WriteHeader — Embrace column headers within the first row of CSV information.

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

Half 16: File Rotation and Cleanup

Automated File Administration

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

MaxDaysToKeep — Mechanically deletes information older than this many days. Set to 0 for limitless retention.

AutoCleanupOnStart — Runs cleanup routine when EA is initialized.

Half 17: Configuration Examples

Machine Studying Coaching Setup

Actual-Time AI Feed Setup

Foreign money Power Analysis Setup

Half 18: Knowledge Column Reference

Core Columns (At all times Included):

Conclusion

AetherFlow AI DataBridge gives professional-grade information mining capabilities for quantitative merchants and AI researchers:

• Multi-Asset Protection — Concurrently acquire information from foreign exchange, commodities, indices, and crypto
• Complete Metrics — Foreign money energy, momentum, quantity, volatility, and technical indicators
• Multi-Timeframe Evaluation — M5 to D1 information in a single export
• SMC Integration — Swing highs/lows and liquidity pool detection
• AI-Prepared Output — Clear CSV format with constant column construction
• Automated Administration — Every day rotation and cleanup maintain your information organized

The important thing to success is matching your configuration to your analysis objectives. Begin with the default settings, confirm information high quality in your ML pipeline, then customise parameters as you refine your fashions.

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