# Entry Assessment — Implementation Plan (29.10)

## Tier 1: Immediate Optimizations (enable a working EA first)

### 1.1 Complete missing strategy implementations
Priority: CRITICAL • Impact: Enable 3 additional entry modes

- [ ] A) Mean Reversion Strategy (`EntrySystem_Optimised.mqh:1027-1039`)
- Check RSI < 30 (oversold) or RSI > 70 (overbought)
- Verify Bollinger Band touches (price beyond bands)
- Confirm market is RANGING or QUIET
- Enter on reversion to mean (BB middle or key MA)
- Tight stops at extreme, targets at mean

- [ ] B) MA Pullback Strategy (`EntrySystem_Optimised.mqh:1015-1024`)
- Identify primary trend (MA 50 > MA 200)
- Wait for price pullback to MA 20/50
- Confirm momentum resumption (MACD or RSI turn)
- Enter in trend direction with tight stop below pullback low

- [ ] C) Contrarian Strategy (`EntrySystem_Optimised.mqh:1042-1051`)
- Detect extreme readings (RSI < 20 or > 80)
- Stochastic oversold/overbought
- Volume climax detection
- Divergence confirmation (price vs RSI)
- Counter-trend entry with wider stops

### 1.2 Optimize existing strategy parameters
Priority: HIGH • Impact: Increase signal frequency 2–3x without quality loss

| Parameter               | Current | Scalping (M1–M5) | Intraday (M15–H1) | Daily (H4–D1) |
|-------------------------|---------|------------------|-------------------|---------------|
| MinTimeBetweenTrades    | 60 min  | 5–15 min         | 30–60 min         | 120–240 min   |
| MA Fast                 | EMA 20  | EMA 8–12         | EMA 20            | EMA 50        |
| MA Slow                 | EMA 50  | EMA 21–34        | EMA 50            | EMA 200       |
| RSI Period              | 14      | 7–9              | 14                | 21            |
| ADX Threshold           | 25      | 20               | 25                | 30            |
| BB Period               | 20      | 10–15            | 20                | 30            |
| ATR Multiplier (SL)     | 2.0     | 1.5              | 2.0               | 2.5–3.0       |
| Signal Threshold        | 60%     | 70%              | 65%               | 60%           |

### 1.3 Add adaptive timeframe logic
Priority: HIGH • File: `EntrySystem_Optimised.mqh`

```cpp
// ADD NEW METHOD:
void CEntrySystem::AdaptParametersToTimeframe()
{
    int current_period = Period();

    // Scalping timeframes (M1-M5)
    if(current_period <= PERIOD_M5)
    {
        m_config.min_time_between = 10;   // 10 minutes
        m_config.signal_threshold = 70;   // Higher quality required
        // Recreate indicators with faster periods
    }
    // Intraday timeframes (M15-H1)
    else if(current_period <= PERIOD_H1)
    {
        m_config.min_time_between = 30;
        m_config.signal_threshold = 65;
    }
    // Daily timeframes (H4+)
    else
    {
        m_config.min_time_between = 120;
        m_config.signal_threshold = 60;
    }
}
```

## Tier 2: Enhanced signal generation

### 2.1 Enable intra-bar scanning for breakout mode
Priority: MEDIUM • Impact: 3–5x more breakout signals • File: `EntrySystem_Optimised.mqh:296-300`

```cpp
// MODIFY:
// Only check on new bar for most strategies (except breakout)
if(!m_new_bar && m_config.entry_mode != ENTRY_BREAKOUT &&
   m_config.entry_mode != ENTRY_MOMENTUM)  // Add momentum for scalping
{
    return signal;
}
```

### 2.2 Multi-timeframe signal confirmation
Priority: MEDIUM • Impact: Higher quality signals, better win rate

```cpp
bool CEntrySystem::ConfirmWithHigherTimeframe(ENUM_SIGNAL_TYPE signal_type)
{
    // Check 1-2 timeframes higher for trend alignment
    ENUM_TIMEFRAMES htf = GetHigherTimeframe(PERIOD_CURRENT);

    // Simple MA trend check on HTF
    double ma_fast_htf[], ma_slow_htf[];
    // Copy and compare

    if(signal_type == SIGNAL_BUY)
        return (ma_fast_htf[0] > ma_slow_htf[0]);  // HTF uptrend
    else
        return (ma_fast_htf[0] < ma_slow_htf[0]);  // HTF downtrend
}
```

Integration:
- Add HTF filter to `ValidateSignal()`
- Optional bonus to confidence score if HTF aligned

### 2.3 Add market session awareness
Priority: MEDIUM • Impact: Better signal timing, avoid low-liquidity periods

```cpp
enum ENUM_SESSION
{
    SESSION_ASIAN,     // 00:00-09:00 GMT
    SESSION_LONDON,    // 08:00-17:00 GMT
    SESSION_NY,        // 13:00-22:00 GMT
    SESSION_OVERLAP    // London/NY overlap
};
```

Session-driven strategy selection:
- Breakout strategies during overlaps (high volatility)
- Mean reversion during Asian session (low volatility)
- Momentum during London/NY sessions

## Tier 3: Advanced enhancements

### 3.1 Volume profile integration
Priority: LOW • Impact: Identify high-probability zones (Technical Analysis)
- Volume-weighted price zones
- POC (Point of Control) levels
- Value Area High/Low
- Entry at VA boundaries

### 3.2 Smart order flow detection
Priority: LOW • Impact: Institutional trade detection
- Large order detection (volume spikes)
- Bid/Ask imbalance analysis
- Absorption/exhaustion patterns
- Hidden liquidity detection

### 3.3 Correlation-based signal filtering
Priority: MEDIUM • Impact: Avoid correlated entries

```cpp
// Before opening new position:
// 1. Check correlation of new symbol with existing positions
// 2. If correlation > 0.7, reduce position size or skip
// 3. Track symbol pair correlations dynamically
```

## Implementation roadmap

### Phase 1: Foundation (Week 1–2)
- [x] Complete Mean Reversion strategy
- [x] Complete MA Pullback strategy
- [x] Complete Contrarian strategy
- [x] Add adaptive timeframe parameter logic
- [] Test all strategies on M15/H1 independently

### Phase 2: Optimization (Week 3–4)
- [] Implement intra-bar scanning for selected strategies
- [] Add multi-timeframe confirmation system
- [] Optimize parameters per timeframe
- [] Backtest across all timeframes
- [] Compare signal frequency and quality metrics

### Phase 3: Advanced features (Week 5–6)
- [ ] Add market session logic
- [ ] Implement correlation filtering
- [ ] Volume profile analysis (optional)
- [ ] Final optimization and stress testing

## Expected outcomes

### Signal frequency improvements

| Timeframe              | Current  | After Phase 1 | After Phase 2 |
|------------------------|----------|---------------|----------------|
| M1–M5 (Scalping)       | 0.5–2/day| 5–10/day      | 10–20/day      |
| M15–M30 (Intraday)     | 2–8/day  | 6–12/day      | 8–15/day       |
| H1–H4 (Swing)          | 1–5/day  | 3–8/day       | 4–10/day       |
| D1 (Position)          | 1–5/week | 2–7/week      | 3–10/week      |

### Quality metrics targets
- Win Rate: 45–55% (maintain or improve)
- Profit Factor: > 1.5 (target 1.8–2.2)
- Sharpe Ratio: > 1.2
- Max Drawdown: < 20%
- Avg R:R: > 1:1.5 (target 1:2)

## Update TODOs
- [ ] Assess EA signal generation for scalping timeframes
- [ ] Assess EA signal generation for intraday timeframes
- [ ] Assess EA signal generation for daily timeframes
- [ ] Evaluate robustness and filtering mechanisms
- [ ] Create improvement plan document

## Summary & recommendations

### Current state assessment
Your ERMT 7.1 EA is institutionally robust with excellent risk management, but signal generation is optimized primarily for intraday trading (M15–H1).

Strengths:
- Exceptional modular architecture
- Multiple entry strategies with consensus capability
- Sophisticated risk and trade management
- Multi-symbol external trade handling

Weaknesses:
- 3 strategies have incomplete implementations
- Fixed parameters don't adapt to timeframe
- New-bar requirement limits scalping potential
- Conservative time restrictions reduce signal frequency

### Priority recommendation
START WITH TIER 1 (Phase 1):
- Complete the 3 incomplete strategies first
- Add adaptive parameter logic based on timeframe
- Test each strategy independently on M15/H1 (your sweet spot)
- Once working reliably, expand to other timeframes

This approach follows your learning point: "Rework and optimize existing code and modules first enabling a working EA before advancing to new architecture."

### Next steps
- [ ] Implement the missing strategy completions (Mean Reversion, MA Pullback, Contrarian)
- [ ] Add the adaptive timeframe logic to automatically adjust parameters
- [ ] Create a testing framework to evaluate signal frequency and quality
- [ ] Proceed with any other specific improvement from the plan