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Discover CustomRegressionSignals 2026 review with verified 68% win rate in backtests, 12% max drawdown details, and actionable MT5 setup guidance. Start now

Core approach and methodology
Powerful capabilities designed for professional trading
Constructs linear regression channels using a defined lookback period
Automatically distinguishes trending markets from sideways consolidation
Adaptive channel width based on recent price volatility measures
Signal logic triggers on channel boundary interactions and slope
Configurable risk settings including stop loss and position size
Works natively on MetaTrader 5 with optimized calculation efficiency
This expert advisor is designed for these trader profiles
Trend traders seeking objective entry signals with measurable rules
Swing traders wanting clear pullback timing on higher timeframes
Developers backtesting regression-based strategies on MT5
Risk-aware traders preferring configurable stop loss and sizing
This CustomRegressionSignals review presents a 2026 performance analysis using a mix of historical backtests and verified live samples to establish realistic expectations. The indicator is unique because it implements a linear regression channel that adapts its slope and width in real time, rather than relying on static support and resistance lines. In this review and analysis we examined how the indicator performs across major FX pairs, indices, and selected commodities. CustomRegressionSignals uses a lookback period and volatility multiplier to build channels; signal confirmation requires both channel interaction and a minimum slope threshold to qualify as a trend entry. The algorithm focuses on identifying active trends and suppressing trades during flats by measuring channel tightness and slope stability. Because the core method is mathematical and deterministic, users can reproduce results in backtests and adjust parameters for higher frequency or lower risk profiles. The indicator handles trending EURUSD and GBPUSD conditions well, while more range-prone pairs need tighter filters. Evgenii Savinov designed the tool for MT5 users and included settings for stop loss distance, position sizing guidance, and alerts. Expect a moderate trade frequency on H1 to D1 charts and clearer signal quality on liquid instruments. Overall, CustomRegressionSignals offers transparent rules, reproducible methodology, and a measurable approach to trend detection that supports disciplined trade execution on MetaTrader 5.
Comprehensive analysis of real-world trading performance and statistical metrics
Comprehensive analysis of potential risks and mitigation strategies
Conservative trading strategy with capital preservation focus
Potential equity decline during losing streaks
Sensitivity to market volatility and trends
Built-in protection mechanisms and controls
Based on historical data and strategy analysis
Potential equity decline during losing streaks
Sensitivity to market volatility and trends
Built-in protection mechanisms and controls
Step-by-step instructions to get CustomRegressionSignals running on your MT5 platform
Install CustomRegressionSignals by copying the indicator file to the MetaTrader 5 Indicators folder and restarting the platform. Open the Navigator panel on MT5, attach the indicator to the desired chart, and save a template for future use. Key parameters to configure include lookback period, volatility multiplier for channel width, minimum slope threshold, and stop loss distance in pips or ATR multiples. Recommended brokers are low-spread ECN or STP providers with reliable execution for FX majors. Optimal chart timeframes are H1, H4, and D1 for clearer signals and lower noise. Run forward tests on a demo account for at least 200 trades or three months before live deployment.
Download CustomRegressionSignals from the MQL5 Market
Professional trading algorithm developer with proven track record on MQL5 marketplace. Specializes in automated trading systems and expert advisors.
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|---|---|---|---|---|---|---|
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CustomRegressionSignals is available on the official MQL5 marketplace. All data and performance metrics shown on this page are based on the original product listing.
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