Code To Cash utilizes a ZeroMQ bridge to receive real-time market predictions from an external Python backend. The system enters trades using BuyStop or SellStop orders at recent price extremes when the neural network confirms a directional bias. It includes comprehensive risk controls such as stop loss placement at recent highs or lows, take profit targets based on risk-to-reward ratios, and dynamic position sizing. An integrated telemetry component streams account data to a FastAPI dashboard.
Neural network market forecasting via ZeroMQ bridge
Breakout-based entry logic for 4-hour timeframes
Dynamic risk-based position sizing and money management
Automated telemetry streaming to external web backends
Read from MT5Streamer.mq5. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
DaysBackHistory
int
365
StreamEquityTicks
bool
true
MaxOrdersToPrint
int
200
BackendBaseUrl
string
http://127.0.0.1:8000
BackendApiKey
string
dev-key
HttpTimeoutMs
int
5000
MirrorToLog
bool
true
ResendAccountEverySecs
int
300
periodic account refresh
NeedsCheckIntervalSecs
int
30
timer cadence
How to install it
1Download the sourceUse "Download source (.zip)" above, or clone LUBANGAKENE/Code-to-Cash from GitHub, and unzip it.
2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
3Copy the filesCopy the .mq5 file into Experts, and any .mqh files into the Include folder the code expects.
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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