This repository provides a collection of Expert Advisors for MetaTrader 5 and Python trading scripts developed for an educational YouTube series. It features various technical indicator-based strategies, including MACD, Relative Strength Index, Stochastic, and Bollinger Bands. The included MQL5 files implement multi-ti
Collection · MT5
Pato Novo MQL5 Collection
This repository contains a collection of MetaTrader 5 expert advisors, primarily featuring the Pato Novo robot.
GitHub stars2
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Last update7 years ago26 Mar 2019
LicenceNone stated
Overview
Pato Novo utilizes moving average signals for trade entries and manages risk with fixed lot sizing, stop loss, and take profit parameters. It includes logic to limit the number of consecutive winning or losing trades to protect account equity. The collection also features specialized tools like a market pressure meter and a robot for the Brazilian Mini Dollar market. Since the repository lacks a README, configuration relies on interpreting the provided input parameters and source code.
- Moving average crossover signal logic
- Daily trade count limits for gains and losses
- Brazilian Mini Dollar specific trading modules
- Market and order book execution modes
- Custom sound notifications for trade events
Details
Author
Zanguient on GitHub
Type
Collection
Platform
MetaTrader 5 (MQL5)
Strategy
Indicator crossover, Trend following
Markets
Forex, Indices
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
- Experts/Pato Novo/PatoNovo/PatoNovo.mq5
- Experts/MedidorPressao/MedidorPressão1.4.mq5
- Experts/MedidorPressao/MedidorPressão1.3.mq5
- Experts/Freelance/Robô Simples para Mini Dólar - BMF/EaWdo.mq5
- Experts/Examples/MACD/MACD Sample.mq5
- Experts/Examples/ChartInChart/ChartInChart.mq5
- Experts/MedidorPressao/MedidorPressao 1.1.mq5
- Experts/MedidorPressao/MedidorPressao2.0.mq5
- Experts/EA_Pessoal/Rico_Estrategia.mq5
- Experts/AjustaStopLossTakeProfit.mq5
About 20 expert advisors in this repository. See them all on GitHub.
Input parameters
Read from PatoNovo.mq5. Defaults are the author's; change them in the EA's Inputs tab.
| Name | Type | Default | Description |
|---|---|---|---|
Signal_MA_PeriodMA | int | 66 | Period of averaging |
Signal_MA_Shift | int | 0 | Time shift |
Signal_MA_Method | ENUM_MA_METHOD | MODE_EMA | Method of averaging |
Signal_MA_Applied | ENUM_APPLIED_PRICE | PRICE_CLOSE | Prices series |
Signal_MA_Weight | double | 1.0 | Weight [0...1.0] |
Money_FixLot_Percent | double | 10.0 | Percent |
Money_FixLot_Lots | double | 1.0 | Fixed volume |
StopLossIni | double | 2.5 | Stop Loss Maximum |
TakeProfitIni | double | 5.0 | Take Profit Maximum |
CandlesStart | int | 12 | Number candles for Start operations |
Rangestart | double | 1.0 | Margin for Start operations |
SoundGun | bool | true | sound of shot |
Show all 17 inputs
| Name | Type | Default | Description |
|---|---|---|---|
Negotiate | bool | true | Allow Perform Trading |
ValidateLoss | bool | true | Allow Validate Limit Loss |
NumberLoss | int | 3 | Max operatinos with Loss |
NumberGain | int | 3 | Max operatinos with Gain |
OrderBook | bool | true | If true = Place book Order; false = Order with Market |
How to install it
- 1Download the sourceUse "Download source (.zip)" above, or clone Zanguient/MQL5 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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