Trading robot · MT5

GGTH AI Modules

by syngyn

This collection of MetaTrader 5 expert advisors integrates external machine learning models via a local HTTP daemon for trade execution.

GitHub stars2
Forks0
Last update1 year ago8 Sep 2025
LicenceNone stated

Overview

The core system, GGTH-SR, utilizes sophisticated position sizing based on the Kelly Criterion with confidence-based scaling and smoothing. It includes an adaptive scalping module with pip thresholds and time-based exits. Risk management is handled through ATR-based or static stop loss and take profit orders. The software also features configurable trading hours and news avoidance filters to control market exposure.

Details

Author

syngyn on GitHub

Type

Trading robot

Platform

MetaTrader 5 (MQL5)

Strategy

AI / machine learning, Scalping

Markets

Any symbol

Timeframes

M1-M5, M15-H1

Risk profile

No grid, martingale or hedging logic was found in its code or README. That says nothing about how it performs: backtest it first.

Input parameters

Read from GGTH-SR.mq5. Defaults are the author's; change them in the EA's Inputs tab.

NameTypeDefaultDescription
DaemonHoststring127.0.0.1Daemon server host
DaemonPortint8888Daemon server port
HttpTimeoutMsint15000HTTP request timeout (ms)
MaxRetryAttemptsint3Max retry attempts for failed requests
RetryDelayMsint1000Delay between retries (ms)
EnableHttpLoggingbooltrueEnable detailed HTTP logging
TestDaemonOnStartboolfalseTest daemon communication on startup
EnableKellyCriterionbooltrueEnable Kelly Criterion position sizing
MaxKellyFractiondouble0.25Maximum Kelly fraction (25% recommended)
MinKellyFractiondouble0.01Minimum Kelly fraction (1% minimum)
KellyLookbackTradesint30Number of recent trades for Kelly calculation
KellyMultiplierdouble0.5Kelly fraction multiplier (0.5 = Half-Kelly)
Show all 40 inputs
NameTypeDefaultDescription
UseConfidenceScalingbooltrueScale Kelly by prediction confidence
BaseRiskWhenNoHistorydouble2.0Risk % when insufficient trade history
EnableKellySmoothingbooltrueSmooth Kelly changes to prevent whipsawing
KellySmoothingFactordouble0.3Smoothing factor (0.1-0.5 recommended)
EnableTradingHoursboolfalseEnable/disable trading hours filter
TradingStartHourint8Start trading hour (0-23)
TradingEndHourint18End trading hour (0-23)
TradingMondaybooltrueTrade on Monday
TradingTuesdaybooltrueTrade on Tuesday
TradingWednesdaybooltrueTrade on Wednesday
TradingThursdaybooltrueTrade on Thursday
TradingFridaybooltrueTrade on Friday
TradingSaturdayboolfalseTrade on Saturday
TradingSundaybooltrueTrade on Sunday
AvoidNewsHoursboolfalseAvoid major news hours
NewsAvoidanceHoursstring14:30-15:30Hours to avoid (format: HH:MM-HH:MM)
ClosePositionsOutsideHoursboolfalseClose positions when outside trading hours
EnableScalpingStrategybooltrueEnable/disable scalping
BaseScalpingPipsdouble10.0Base pip threshold for scalping
ScalpingTimeoutBarsint3Bars to hold scalping position
ScalpingRiskPercentdouble1Risk % for scalping (separate from main)
AdaptiveScalpingThresholdbooltrueMake pip threshold adaptive
MinScalpingAccuracydouble0Minimum accuracy required for scalping
ScalpingOverridesMainboolfalseIf true, scalping replaces main strategy
AdaptiveLearningModeENUM_ADAPTIVE_MODEADAPTIVE_CONSERVATIVE
EnableDynamicConfidencebooltrue
EnableAdaptivePositionSizingbooltrue
EnableStepWeightingbooltrue

How to install it

  1. 1Download the sourceUse "Download source (.zip)" above, or clone syngyn/mql5-ai-modules from GitHub, and unzip it.
  2. 2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
  3. 3Copy the filesCopy the .mq5 file into Experts, and any .mqh files into the Include folder the code expects.
  4. 4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
  5. 5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.

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