Edelweiss EA: Free MT4 Expert Advisor

Overview

Edelweiss EA combines exponential moving averages, stochastic oscillators, the awesome oscillator, ADX, and Bollinger Bands to identify market entries. Trade management includes dynamic ATR-based stop loss and take profit levels, along with trailing stops and risk-based lot sizing. Users can filter noise by requiring multiple consecutive signals before execution. While the repository includes a PyTorch LSTM implementation for research, the EA operates as a rule-based technical system.

Multi-indicator signal logic

ATR-based dynamic stop-loss and take-profit

Risk-based position sizing and trailing stops

Configurable signal filters for noise reduction

Details

Author

Attornado on GitHub

Type

Trading robot

Platform

MetaTrader 4 (MQL4)

Strategy

Indicator crossover, Mean reversion, Trend following, Multi-strategy

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

Experts/EdelweissExpert.mq4

Source

github.com/Attornado/EdelweissEA

Input parameters

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

Name	Type	Default	Description
`optimize_lot`	`bool`	`true`
`lot`	`double`	`0.1`	lots to Trade
`lot_decrease_factor`	`double`	`3.0`
`price_slippage`	`int`	`3`
`max_risk`	`double`	`0.01`	max balance risk
`default_trailing_stop`	`int`	`30`	to compute default stop-loss
`default_take_profit`	`int`	`50`	default take profit
`buy_signals_t`	`int`	`1`
`sell_signals_t`	`int`	`1`
`use_ma_signals`	`bool`	`true`
`ma_window_slow`	`int`	`50`	may also try 21
`ma_window_fast`	`int`	`20`	may also try 7

Show all 40 inputs

Name	Type	Default	Description
`ma_shift`	`int`	`0`
`ma_method`	`ENUM_MA_METHOD`	`MODE_EMA`
`ma_price_type`	`ENUM_APPLIED_PRICE`	`PRICE_CLOSE`
`use_atr_sl_tp`	`bool`	`true`
`atr_stop_loss_factor`	`double`	`2.0`
`atr_take_profit_factor`	`double`	`4.0`
`atr_window`	`int`	`14`
`atr_normalized_volatility_t`	`double`	`0.1`
`use_stochastic_signals`	`bool`	`true`
`stochastic_k_period`	`int`	`14`
`stochastic_d_period`	`int`	`3`
`stochastic_slowing`	`int`	`3`
`stochastic_ma_method`	`ENUM_MA_METHOD`	`MODE_SMA`
`stochastic_price_field`	`int`	`0`	type of price type used to compute stochastic oscillator 0=Low/High or 1=Close/Close
`stochastic_over_bought_t`	`double`	`80`	stochastic overbought
`stochastic_over_sold_t`	`double`	`20`	stochastic oversold
`stochastic_use_atr_volatility_signal`	`bool`	`true`	whether to use the ATR-based volatility signal in stochastic oscillator
`use_awesome_signals`	`bool`	`true`
`awesome_saucers_bar_number`	`int`	`3`	number of consecutive bars to evaluate with the awesome oscillator saucers strategy
`awesome_check_stochastic`	`bool`	`true`	combine signals with oversold/overbought signals by stochastic oscillator
`use_adx_signals`	`bool`	`true`
`adx_use_parabolic_signal`	`bool`	`true`
`adx_period`	`int`	`14`
`adx_price_type`	`ENUM_APPLIED_PRICE`	`PRICE_CLOSE`
`adx_min_market_trending_t`	`double`	`20.0`
`parabolic_step`	`double`	`0.02`
`parabolic_max_step`	`double`	`0.2`
`use_bollinger_signals`	`bool`	`true`

How to install it

1Download the sourceUse "Download source (.zip)" above, or clone Attornado/EdelweissEA 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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