Market Miner - expert pour MetaTrader 5

This Expert Advisor is a multi-strategy system broken into four independent trading subsystems (Cycle 1 to Cycle 4). Each cycle operates with its own Magic Number, indicators, entry triggers, and unique money management parameters.

1. Cycle 1 Logic: Multi-Indicator Confluence

Cycle 1 relies on a composite filter combining up to three Moving Averages (MA), a Relative Strength Index (RSI), and a Williams’ Percent Range (WPR).

Entry Triggers

A core variable c1_signal acts as a binary register to ensure indicators do not conflict. If indicator A gives a Buy signal, c1_signal becomes 1 . If indicator B then gives a Sell signal, c1_signal resets to 0 to invalidate the trade.

• Moving Average 1, 2, and 3:

  • Buy Condition: The previous bar closes above the MA, and the current bar opens above the MA ($Close[1] > MA$ and $Open[0] > MA$).

  • Sell Condition: The previous bar closes below the MA, and the current bar opens below the MA ($Close[1] < MA$ and $Open[0] < MA$).

• RSI Filter:

  • Buy Condition: RSI falls below the oversold threshold ( RSI_Buy_Level , e.g., 30).

  • Sell Condition: RSI rises above the overbought threshold ( RSI_Sell_Level , e.g., 70).

• WPR Filter:

  • Buy Condition: WPR drops below WPR_Buy_Level (e.g., -80).

  • Sell Condition: WPR rises above WPR_Sell_Level (e.g., -20).

Signal Processing

• Reverse Signals Rule: If Reverse_Signals = true , a final Buy signal ( 1 ) flips to a Sell signal ( 2 ), and vice versa.

• One Trade Per Bar Constraint: The EA checks if the current open price matches c1_open_price . If it does, a position has already been handled on this bar, and further executions are blocked until a new bar opens.

2. Cycle 2 Logic: Envelopes Trend Following

Cycle 2 uses a classic dual-band Envelopes indicator to map out structural market breakouts.

• Buy Trigger: The previous bar closes above the Upper Envelope band, and the current bar opens above it ($Close[1] > UpperBand$ and $Open[0] > UpperBand$). This assumes a strong bullish momentum breakout.

• Sell Trigger: The previous bar closes below the Lower Envelope band, and the current bar opens below it ($Close[1] < LowerBand$ and $Open[0] < LowerBand$), indicating a bearish breakdown.

• Signal Flips: If Reverse_Signals2 = true , it flips breakouts into fakeout traps (fades the breakdown/breakout).

3. Cycle 3 Logic: Envelopes Mean Reversion

Cycle 3 tracks identical parameters to Cycle 2 but reverses the default baseline execution logic to target mean reversion (fading extremes).

• Buy Trigger: The previous bar closes above the Upper Envelope band, and the current bar opens above it. Logic: The code assigns a Sell signal here because it assumes the asset is overextended and will pull back inside the bands.

• Sell Trigger: The previous bar closes below the Lower Envelope band, and the current bar opens below it. Logic: The code assigns a Buy signal here, betting on an immediate bounce from oversold territory.

4. Cycle 4 Logic: Envelopes Point-Distance Breakout

Cycle 4 introduces a hard volatility/pip distance constraint to the Envelopes indicator, acting as an aggressive breakout system.

• Buy Trigger: The distance between the lower envelope band and the previous close is greater than Distance in points, AND the distance between the lower envelope band and the current Bid price is also greater than Distance ($LowerBand - Close[1] > Distance$ and $LowerBand - Bid > Distance$).

• Sell Trigger: The distance between the previous close and the upper band, as well as the current Bid price and the upper band, both exceed Distance ($Close[1] - UpperBand > Distance$ and $Bid - UpperBand > Distance$).

5. Exit, Basket Closure & Risk Logic

The exit management architecture does not use standard per-position Stop Loss (SL) or Take Profit (TP) orders. Instead, it relies on a Global Account Equity Basket Tracking System mapped per cycle.

Milestone Capturing

When a cycle’s position count transitions from 0 to 1 (tracked via c1_Buycount == 0 or c1_Sellcount == 0 ), the EA benchmarks the exact baseline equity of the trading account at that moment:

Using this baseline, it maps static global targets for that specific trading direction:

• Take Profit Target: If target_amount is specified, it assigns $\text{Baseline} + \text{target\_amount}$. Otherwise, it uses a percentage formula:

  $$\text{Target Price} = \text{Baseline} + \left(\frac{\text{Baseline} \times \text{target\_percent}}{100}\right)$$

• Stop Loss Target: Uses a percentage drawdown constraint relative to the captured snapshot equity:

  $$\text{Risk Price} = \text{Baseline} - \left(\frac{\text{Baseline} \times \text{Account\_Risk\_percent}}{100}\right)$$

Dynamic Basket Verification

On every tick, the EA calculates the running total of real-time floating profit/loss, swaps, and commissions for all active positions matching that specific Cycle’s Magic Number and trade type ( MyAccountProfit_Buy or MyAccountProfit_Sell ).

Exit Execution

If $\text{Current Portfolio Value} \ge \text{Target Price}$ (Profit Target Hit) OR $\text{Current Portfolio Value} \le \text{Risk Price}$ (Max Risk Ceiling Breach):

1. The EA calls ClosePositions() .

2. It loops backward through all market positions, filtering by matching Magic Number and Position Type.

3. Every single correlated trade is instantly liquidated via a market order.

4. The direction’s cycle tracker is reset back to 0 , arming the EA to establish a completely fresh benchmark snapshot on the next structural indicator signal.

6. Sizing Logic (Money Management)

The volume calculations are performed dynamically by the getLots(int cycle) routine:

• Fixed Lotting: If AutoLots is false , it returns the baseline hardcoded lot size setting (e.g., LotSize = 0.01 ).

• Dynamic Risk Scaling: If AutoLots = true , the system automatically adjusts trade volume based on free margin:

  1. It queries the exact margin required to handle a standard 1.0 lot transaction on the current asset using OrderCalcMargin .

  2. It projects an affordable investment capacity using the formula:

     $$\text{Projected Volume} = \frac{\text{AccountFreeMargin} \times \left(\frac{\text{Lots\_Risk}}{100}\right)}{\text{Margin Per 1.0 Lot}}$$

  3. The final result is bounded against broker-enforced constraints using MathMin and MathMax to ensure it falls precisely within the valid range between SYMBOL_VOLUME_MIN and SYMBOL_VOLUME_MAX , rounded cleanly to the nearest exchange asset step size ( SYMBOL_VOLUME_STEP ).