QUANT EA
QUANT EA is a multi-timeframe quantitative trading system that combines multiple technical indicators across different timeframes to generate entry and exit signals. It uses a statistical approach to evaluate trend strength and momentum before opening positions, with built-in risk management features. The EA aims to capture trending moves while filtering out noise through multi-timeframe confluence analysis.
Open the interactive view (equity curve, symbol switch)Key facts
Backtest results (H1, about 1 year)
Not backtested yet — this EA could not be converted automatically.
Strategy analysis
QUANT EA's core strategy is multi-timeframe confluence quantitative analysis, calculating technical indicator signals across multiple timeframes simultaneously and only entering when signals align across different periods. Entry conditions are typically based on fast and slow moving average crossovers, combined with RSI overbought/oversold filtering and MACD direction confirmation, requiring at least two timeframes to agree on trend direction before opening a position. Exit conditions include fixed take-profit and stop-loss levels, trailing stops, and active position closing when signals reverse. Position sizing uses either fixed lot sizes or dynamic calculation based on account balance percentage. Money management features maximum position limits and daily maximum loss controls, without implementing martingale or grid strategies. The overall strategy logic leans toward trend following, but may generate consecutive false signals during ranging markets leading to drawdowns.
Strengths
- Multi-timeframe confluence analysis effectively filters false signals and improves entry quality
- Built-in risk controls including trailing stops and daily maximum loss limits provide sound risk management
- Systematic quantitative logic is clear with good parameter adjustability for optimization across different market conditions
Weaknesses
- Multi-timeframe analysis tends to generate repeated conflicting signals in ranging markets leading to consecutive losses
- Lacks spread filtering mechanism, making it vulnerable to high-spread environments where trading costs significantly impact profitability
- Fixed stop-loss and take-profit don't account for market volatility changes (ATR), potentially causing unstable performance across varying volatility regimes
Possible improvements
- Add ATR-based dynamic stop-loss and take-profit to automatically adjust risk parameters based on market volatility
- Implement spread filtering and trading session filtering to avoid high-cost and low-liquidity trading periods
Risk assessment
Overall risk: Medium
- Lack of spread filtering may cause additional slippage losses in high-spread environments
- Fixed stop-loss not adapted to volatility may be too wide in low volatility and too narrow in high volatility
- Multi-timeframe signals may lag during market regime transitions causing chase-in entries
Evaluation scores
Parameters
| Parameter | Default | Description |
|---|---|---|
LotSize | 0.1 | Fixed lot size |
StopLoss | 50 | Stop loss in points |
TakeProfit | 100 | Take profit in points |
TrailingStop | 30 | Trailing stop in points |
FastMA_Period | 10 | Fast MA period |
SlowMA_Period | 50 | Slow MA period |
RSI_Period | 14 | RSI indicator period |
RSI_Overbought | 70 | RSI overbought threshold |
RSI_Oversold | 30 | RSI oversold threshold |
MACD_Fast | 12 | MACD fast EMA period |
MACD_Slow | 26 | MACD slow EMA period |
MACD_Signal | 9 | MACD signal line period |
Timeframe1 | H1 | First analysis timeframe |
Timeframe2 | H4 | Second analysis timeframe |
MaxPositions | 3 | Maximum simultaneous positions |
MaxDailyLoss | 5 | Maximum daily loss percentage |
MagicNumber | 49770 | EA magic number for order identification |
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Backtests are historical simulations and do not guarantee future results. Not financial advice.