Falcon C: Free MT4 Expert Advisor

Overview

Falcon C relies on an external deep learning framework built in R to categorize current market regimes, such as normal or volatile bull and bear phases. Based on these categories, the robot switches between different sets of indicator periods and risk parameters. It includes volatility-based stop loss and take profit controls. The system requires an external connection to a decision support center for its advanced market recognition features.

Deep learning market regime recognition

Volatility-based stop loss and take profit

Dynamic parameter switching based on market type

Integration with external R-based decision support system

Details

Author

vzhomeexperiments on GitHub

Type

Trading robot

Platform

MetaTrader 4 (MQL4)

Strategy

Indicator crossover, AI / machine learning, Trend following

Markets

Any symbol

Timeframes

Any timeframe

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.

EA files

Falcon_C.mq4

Topics

deepdeeplearningh2omarket-recognitionmarket-statusfalconmarket

Source

github.com/vzhomeexperiments/FALCON_C

Input parameters

Read from Falcon_C.mq4. Defaults are the author's; change them in the EA's Inputs tab.

Name	Type	Default	Description
`Header15`	`string`	`----------EA General Settings-----------`
`MagicNumber`	`int`	`8134201`
`TerminalType`	`int`	`1`	0 mean slave, 1 mean master
`R_Management`	`bool`	`true`	R_Management true will enable Decision Support Centre (using R)
`Slippage`	`int`	`3`	In Pips
`IsECNbroker`	`bool`	`false`	Is your broker an ECN
`OnJournaling`	`bool`	`true`	Add EA updates in the Journal Tab
`Header1`	`string`	`----------Trading Rules Variables Standard-----------`
`FastMAPeriod`	`int`	`10`
`SlowMAPeriod`	`int`	`40`
`KeltnerPeriod`	`int`	`15`
`KeltnerMulti`	`int`	`3`

Show all 40 inputs

Name	Type	Default	Description
`use_market_type`	`bool`	`false`
`Header1_1`	`string`	`----------Trading Rules Variables Market Bull normal BUN----`
`FastMAPeriodBUN`	`int`	`10`
`SlowMAPeriodBUN`	`int`	`140`
`KeltnerPeriodBUN`	`int`	`160`
`KeltnerMultiBUN`	`int`	`5`
`VolBasedSLMultiplierBUN`	`double`	`4`	Stop Loss Amount in units of Volatility
`VolBasedTPMultiplierBUN`	`double`	`6`	Take Profit Amount in units of Volatility
`Header1_2`	`string`	`----------Trading Rules Variables Market Bull volatile BUV--`
`FastMAPeriodBUV`	`int`	`20`
`SlowMAPeriodBUV`	`int`	`180`
`KeltnerPeriodBUV`	`int`	`100`
`KeltnerMultiBUV`	`int`	`5`
`VolBasedSLMultiplierBUV`	`double`	`5`	Stop Loss Amount in units of Volatility
`VolBasedTPMultiplierBUV`	`double`	`7`	Take Profit Amount in units of Volatility
`Header1_3`	`string`	`----------Trading Rules Variables Market Bear normal BEN----`
`FastMAPeriodBEN`	`int`	`10`
`SlowMAPeriodBEN`	`int`	`140`
`KeltnerPeriodBEN`	`int`	`160`
`KeltnerMultiBEN`	`int`	`5`
`VolBasedSLMultiplierBEN`	`double`	`4`	Stop Loss Amount in units of Volatility
`VolBasedTPMultiplierBEN`	`double`	`6`	Take Profit Amount in units of Volatility
`Header1_4`	`string`	`----------Trading Rules Variables Market Bear volatile BEV--`
`FastMAPeriodBEV`	`int`	`20`
`SlowMAPeriodBEV`	`int`	`180`
`KeltnerPeriodBEV`	`int`	`100`
`KeltnerMultiBEV`	`int`	`5`
`VolBasedSLMultiplierBEV`	`double`	`5`	Stop Loss Amount in units of Volatility

How to install it

1Download the sourceUse "Download source (.zip)" above, or clone vzhomeexperiments/FALCON_C from GitHub, and unzip it.

2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL4/Experts.

3Copy the filesCopy the .mq4 file into Experts.

4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.

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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