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Indicators to Strategy Blueprint

This Elliott Wave analysis script is a sophisticated piece of pattern recognition software, but its current form as an indicator makes it a tool for discretionary analysis, not automated execution. To bridge the gap from chart signals to live order fills, we must re-architect it into a robust strategy with a professional-grade execution engine.

The core challenge is transforming its “repaint-on-last-bar” logic into a causal, bar-by-bar decision framework that can be realistically backtested and deployed.

1. Execution Triggers (Entry & Direction)

The original script identifies several potential signals. We will codify the highest-probability setups—the Wave 3 entry and the Wave C reversal—into precise, non-repainting execution triggers.

2. Multi-Tiered Exit Logic

A professional strategy never relies on a single exit condition. We will implement a multi-layered exit framework to manage risk, secure profits, and adapt to market behavior.

3. Capital Allocation & Risk Management

Position sizing is the most critical factor in long-term viability. We will move from the default fixed-quantity contracts to a dynamic, risk-based model.

4. Implementation Snippet (Pine Logic)

This snippet demonstrates the conversion of the indicator into a strategy, focusing on the execution engine. The complex wave detection functions are assumed to be present and are called by this new logic. The barstate.islast wrappers around the core logic have been removed.

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Elliott Wave Advanced v3 - Execution Framework

//@version=6
// 1. STRATEGY DECLARATION - Professional Grade
strategy("Elliott Wave Execution Framework", "EW Exec", overlay=true,
     pyramiding=0, // One trade at a time
     initial_capital=100000,
     default_qty_type=strategy.fixed, // We will calculate size manually
     default_qty_value=1, // Placeholder, size is dynamic
     commission_type=strategy.commission.percent,
     commission_value=0.075, // Realistic commission for crypto/futures
     slippage=2) // Realistic slippage in ticks

// ============================================================================
// INPUTS - STRATEGY CONTROLS
// ============================================================================
riskMgmtGroup = "Risk Management"
riskPercent = input.float(1.5, "Risk per Trade (%)", minval=0.1, maxval=5.0, step=0.1, group=riskMgmtGroup)
atrLen = input.int(14, "ATR Length (for Stops)", group=riskMgmtGroup)
atrStopMultiplier = input.float(1.5, "ATR Stop Multiplier", group=riskMgmtGroup)
confidenceThreshold = input.float(0.50, "Min Pattern Confidence", minval=0.35, maxval=1.0, group=riskMgmtGroup)
tp1Extension = input.float(1.0, "Take Profit 1 (Fib Extension)", group=riskMgmtGroup)

// [ ... All original Elliott Wave functions and types (Pivot, ElliottWave, etc.) go here ... ]
// CRITICAL: Remove all `barstate.islast` wrappers from core calculation functions.
// The pivot detection, pattern matching, and context updates must run on every bar.

// ============================================================================
// MAIN EXECUTION LOGIC (runs on every bar)
// ============================================================================

// --- Recalculate pivots and patterns on every bar ---
// This part is now outside of any `barstate.islast` block.
// (The original pivot detection logic is assumed to be here)
// ...
// Reset context for fresh detection on each bar's new info
confirmedCtx.confirmedPattern := "none"
confirmedCtx.confidence := 0.0
WavePattern bestPattern = drawValidatedWaveLabels(primaryPivots, secondaryPivots) // This function now just returns the pattern, not draws it
// ...

// --- Signal Generation ---
var bool longCondition = false
var bool shortCondition = false

if array.size(primaryPivots) >= 3
    Pivot lastP = array.get(primaryPivots, array.size(primaryPivots) - 1)
    bool isW3Setup = detectWave3Entry(primaryPivots)
    bool hasConfidence = confirmedCtx.confidence >= confidenceThreshold

    // Long Conditions
    isW3Long = isW3Setup and hasConfidence and not lastP.isHigh
    isCReversalLong = signalWCReversal and confirmedCtx.confirmedPhase == "corrective" and not confirmedCtx.isBullish and not lastP.isHigh
    longCondition := isW3Long or isCReversalLong

    // Short Conditions
    isW3Short = isW3Setup and hasConfidence and lastP.isHigh
    isCReversalShort = signalWCReversal and confirmedCtx.confirmedPhase == "corrective" and confirmedCtx.isBullish and lastP.isHigh
    shortCondition := isW3Short or isCReversalShort

// --- Execution ---
if strategy.opentrades == 0 // Only look for new entries if flat
    float atrValue = ta.atr(atrLen)
    float stopLossLevel = na
    float takeProfitLevel = na
    float entryPrice = ta.valuewhen(longCondition or shortCondition, close, 0)

    if longCondition
        // Stop Loss is below the Wave 2 or Wave C low
        Pivot setupPivot = array.get(primaryPivots, array.size(primaryPivots) - 1)
        stopLossLevel := setupPivot.price - (atrValue * atrStopMultiplier)
        
        // Take Profit based on Wave 1 extension
        Pivot w1_start = array.get(primaryPivots, array.size(primaryPivots) - 3)
        Pivot w1_end = array.get(primaryPivots, array.size(primaryPivots) - 2)
        float w1_len = w1_end.price - w1_start.price
        takeProfitLevel := setupPivot.price + (w1_len * tp1Extension)

        // Risk-based Position Sizing
        float riskDistance = entryPrice - stopLossLevel
        float dollarRisk = strategy.equity * (riskPercent / 100)
        float positionSize = dollarRisk / riskDistance
        
        strategy.entry("EW_Long", strategy.long, qty=positionSize)
        strategy.exit("Exit_L", "EW_Long", stop=stopLossLevel, limit=takeProfitLevel, qty_percent=50) // Exit 50% at SL or TP1
        strategy.exit("Exit_L_BE", "EW_Long", stop=stopLossLevel) // Manages the other 50%

    if shortCondition
        // Stop Loss is above the Wave 2 or Wave C high
        Pivot setupPivot = array.get(primaryPivots, array.size(primaryPivots) - 1)
        stopLossLevel := setupPivot.price + (atrValue * atrStopMultiplier)

        // Take Profit based on Wave 1 extension
        Pivot w1_start = array.get(primaryPivots, array.size(primaryPivots) - 3)
        Pivot w1_end = array.get(primaryPivots, array.size(primaryPivots) - 2)
        float w1_len = w1_start.price - w1_end.price
        takeProfitLevel := setupPivot.price - (w1_len * tp1Extension)

        // Risk-based Position Sizing
        float riskDistance = stopLossLevel - entryPrice
        float dollarRisk = strategy.equity * (riskPercent / 100)
        float positionSize = dollarRisk / riskDistance

        strategy.entry("EW_Short", strategy.short, qty=positionSize)
        strategy.exit("Exit_S", "EW_Short", stop=stopLossLevel, limit=takeProfitLevel, qty_percent=50)
        strategy.exit("Exit_S_BE", "EW_Short", stop=stopLossLevel)

// --- Dynamic Trade Management ---
// Move stop to breakeven after TP1 is hit
if strategy.opentrades > 0 and strategy.opentrades[1] > strategy.opentrades
    if strategy.position_avg_price != 0
        // A partial exit just occurred, move stop for remaining position to breakeven
        if strategy.position_is_long
            strategy.exit("Exit_L_BE", "EW_Long", stop=strategy.position_avg_price)
        if strategy.position_is_short
            strategy.exit("Exit_S_BE", "EW_Short", stop=strategy.position_avg_price)

// Final Wave 5 Exit Signal
bool wave5ExitSignal = signalW5Exit and confirmedCtx.confirmedPattern == "impulse" // Simplified from original
if wave5ExitSignal
    strategy.close_all(comment="Wave 5 Exit")

// --- Drawing and UI (can remain in barstate.islast for performance) ---
if barstate.islast
    // All original drawing functions (drawWavePattern, drawForecastProjection, infoPanel, etc.) go here
    // They will use the `bestPattern` and `confirmedCtx` calculated on the final bar.
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