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this is the code im using: //@version=6 indicator(“BlackRock Institutional Alpha – Advanced SMC Engine”, shorttitle=”BR Alpha”, overlay=true, max_lines_count=500, max_labels_count=500, max_boxes_count=500, max_polylines_count=100) // ============================================================================ // INSTITUTIONAL PARAMETER MATRIX // ============================================================================ primary_tf = input.timeframe(“15”, “Primary Timeframe”, group=”🏦 Institutional Framework”) secondary_tf = input.timeframe(“60”, “Secondary Timeframe”, group=”🏦 Institutional Framework”) tertiary_tf = input.timeframe(“240”, “Tertiary Timeframe”, group=”🏦 Institutional Framework”) weekly_tf = input.timeframe(“1W”, “Weekly Structure”, group=”🏦 Institutional Framework”) enable_wyckoff = input.bool(true, “Enable Wyckoff Analysis”, group=”📊 Market Structure”) enable_auction_theory = input.bool(true, “Enable Auction Market Theory”, group=”📊 Market Structure”) enable_volume_profile = input.bool(true, “Enable Volume Profile Analysis”, group=”📊 Market Structure”) enable_fractal_geometry = input.bool(true, “Enable Fractal Market Geometry”, group=”📊 Market Structure”) institution_volume_threshold = input.float(2.5, “Institutional Volume Multiplier”, minval=1.0, maxval=10.0, group=”💼 Order Flow”) dark_pool_sensitivity = input.float(0.85, “Dark Pool Detection Sensitivity”, minval=0.1, maxval=1.0, group=”💼 Order Flow”) algo_trade_filter = input.bool(true, “Algorithmic Trade Filter”, group=”💼 Order Flow”) hft_noise_reduction = input.float(0.15, “HFT Noise Reduction”, minval=0.01, maxval=0.5, group=”💼 Order Flow”) confluence_threshold = input.float(0.75, “Confluence Threshold”, minval=0.1, maxval=1.0, group=”🔬 Confluence Engine”) smart_money_weight = input.float(0.4, “Smart Money Weight”, minval=0.1, maxval=0.9, group=”🔬 Confluence Engine”) technical_weight = input.float(0.35, “Technical Weight”, minval=0.1, maxval=0.9, group=”🔬 Confluence Engine”) sentiment_weight = input.float(0.25, “Sentiment Weight”, minval=0.1, maxval=0.9, group=”🔬 Confluence Engine”) dynamic_position_sizing = input.bool(true, “Dynamic Position Sizing”, group=”⚖️ Risk Management”) volatility_adjusted_stops = input.bool(true, “Volatility Adjusted Stops”, group=”⚖️ Risk Management”) correlation_filter = input.bool(true, “Cross-Asset Correlation Filter”, group=”⚖️ Risk Management”) max_drawdown_protection = input.float(15.0, “Max Drawdown Protection (%)”, minval=5.0, maxval=50.0, group=”⚖️ Risk Management”) starting_capital = input.float(100000, “Starting Capital”, minval=1000, group=”📈 Performance”) max_risk_per_trade = input.float(2.0, “Max Risk Per Trade (%)”, minval=0.1, maxval=10.0, group=”📈 Performance”) profit_scaling_factor = input.float(1.618, “Profit Scaling Factor”, minval=1.0, maxval=5.0, group=”📈 Performance”) show_institutional_levels = input.bool(true, “Show Institutional Levels”, group=”🎨 Visualization”) show_order_flow_heatmap = input.bool(true, “Show Order Flow Heatmap”, group=”🎨 Visualization”) show_confluence_zones = input.bool(true, “Show Confluence Zones”, group=”🎨 Visualization”) show_probability_bands = input.bool(true, “Show Probability Bands”, group=”🎨 Visualization”) // ============================================================================ // ADVANCED MATHEMATICAL FRAMEWORK // ============================================================================ atr_length = 21 atr_multiplier = 2.618 volatility_index = ta.atr(atr_length) / ta.sma(close, 200) market_regime = volatility_index > ta.sma(volatility_index, 50) ? 1 : -1 volume_ma = ta.sma(volume, 20) volume_std = ta.stdev(volume, 20) institutional_volume = volume > (volume_ma + volume_std * institution_volume_threshold) price_momentum = (close – close[21]) / close[21] * 100 price_acceleration = ta.roc(price_momentum, 5) market_pressure = (high – low) / ta.atr(14) fractal_high = high[2] > high[1] and high[2] > high[3] and high[1] > high[0] and high[3] > high[4] fractal_low = low[2] < low[1] and low[2] < low[3] and low[1] < low[0] and low[3] < low[4] // ============================================================================ // CANDLE ANALYSIS (MISSING FROM ORIGINAL) // ============================================================================ is_bullish_candle = close > open is_bearish_candle = close < open body_size = math.abs(close – open) candle_range = high – low body_ratio = candle_range > 0 ? body_size / candle_range : 0 // ============================================================================ // MULTI-TIMEFRAME STRUCTURE ANALYSIS // ============================================================================ htf_close = request.security(syminfo.tickerid, secondary_tf, close) htf_high = request.security(syminfo.tickerid, secondary_tf, high) htf_low = request.security(syminfo.tickerid, secondary_tf, low) htf_volume = request.security(syminfo.tickerid, secondary_tf, volume) ttf_close = request.security(syminfo.tickerid, tertiary_tf, close) ttf_high = request.security(syminfo.tickerid, tertiary_tf, high) ttf_low = request.security(syminfo.tickerid, tertiary_tf, low) weekly_close = request.security(syminfo.tickerid, weekly_tf, close) weekly_high = request.security(syminfo.tickerid, weekly_tf, high[1]) weekly_low = request.security(syminfo.tickerid, weekly_tf, low[1]) // ============================================================================ // INSTITUTIONAL ORDER BLOCK DETECTION // ============================================================================ institutional_bear_ob = is_bearish_candle[2] and body_ratio[2] > 0.6 and institutional_volume[2] and close > high[2] and close[1] > close[2] institutional_bull_ob = is_bullish_candle[2] and body_ratio[2] > 0.6 and institutional_volume[2] and close < low[2] and close[1] < close[2] htf_structure_bullish = htf_close > htf_close[1] and htf_close > ta.ema(htf_close, 21) htf_structure_bearish = htf_close < htf_close[1] and htf_close < ta.ema(htf_close, 21) // ============================================================================ // ADVANCED FAIR VALUE GAP ANALYSIS // ============================================================================ bull_fvg = low > high[2] and is_bullish_candle and institutional_volume bear_fvg = high < low[2] and is_bearish_candle and institutional_volume fvg_strength = (bull_fvg or bear_fvg) ? (high – low) / ta.atr(14) : 0 strong_fvg = fvg_strength > 0.5 medium_fvg = fvg_strength > 0.3 and fvg_strength <= 0.5 weak_fvg = fvg_strength > 0.1 and fvg_strength <= 0.3 // ============================================================================ // WYCKOFF ACCUMULATION/DISTRIBUTION ANALYSIS // ============================================================================ wyckoff_volume_spread = enable_wyckoff ? (volume / volume_ma) * (high – low) : 0 wyckoff_accumulation = wyckoff_volume_spread > 1.5 and close > (high + low) / 2 wyckoff_distribution = wyckoff_volume_spread > 1.5 and close < (high + low) / 2 phase_a = wyckoff_distribution and market_pressure > 1.2 phase_b = wyckoff_volume_spread < 1.0 and market_pressure < 0.8 phase_c = wyckoff_accumulation and market_pressure > 1.0 // ============================================================================ // AUCTION MARKET THEORY IMPLEMENTATION // ============================================================================ value_area_high = ta.highest(high, 20) value_area_low = ta.lowest(low, 20) value_area_mid = (value_area_high + value_area_low) / 2 auction_imbalance_up = enable_auction_theory and close > value_area_high and volume > volume_ma * 1.3 auction_imbalance_down = enable_auction_theory and close < value_area_low and volume > volume_ma * 1.3 initial_balance_high = ta.highest(high, 4) initial_balance_low = ta.lowest(low, 4) balance_extension = close > initial_balance_high or close < initial_balance_low // ============================================================================ // CONFLUENCE SCORING SYSTEM // ============================================================================ technical_score = 0.0 technical_score += (institutional_bull_ob and htf_structure_bullish) ? 0.25 : 0 technical_score += (institutional_bear_ob and htf_structure_bearish) ? 0.25 : 0 technical_score += strong_fvg ? 0.2 : medium_fvg ? 0.1 : 0 technical_score += (fractal_high or fractal_low) ? 0.15 : 0 technical_score += market_pressure > 1.0 ? 0.15 : 0 smart_money_score = 0.0 smart_money_score += institutional_volume ? 0.3 : 0 smart_money_score += (wyckoff_accumulation or wyckoff_distribution) ? 0.25 : 0 smart_money_score += (auction_imbalance_up or auction_imbalance_down) ? 0.2 : 0 smart_money_score += balance_extension ? 0.15 : 0 smart_money_score += math.abs(price_acceleration) > 2.0 ? 0.1 : 0 sentiment_score = 0.0 sentiment_score += market_regime > 0 ? 0.4 : 0 sentiment_score += price_momentum > 0 ? 0.3 : price_momentum < 0 ? -0.3 : 0 sentiment_score += volatility_index > 0.02 ? 0.3 : 0 final_confluence = technical_score * technical_weight + smart_money_score * smart_money_weight + sentiment_score * sentiment_weight // ============================================================================ // SIGNAL GENERATION ENGINE // ============================================================================ ema_21 = ta.ema(close, 21) long_confluence = final_confluence > confluence_threshold and final_confluence > 0 long_structure = institutional_bull_ob and htf_structure_bullish long_confirmation = bull_fvg and wyckoff_accumulation and auction_imbalance_up short_confluence = final_confluence > confluence_threshold and final_confluence < 0 short_structure = institutional_bear_ob and htf_structure_bearish short_confirmation = bear_fvg and wyckoff_distribution and auction_imbalance_down institutional_long_signal = ( long_confluence and long_structure and long_confirmation and close > ema_21 and weekly_close > weekly_low ) institutional_short_signal = ( short_confluence and short_structure and short_confirmation and close < ema_21 and weekly_close < weekly_high ) // ============================================================================ // DYNAMIC POSITION SIZING & RISK MANAGEMENT // ============================================================================ volatility_multiplier = volatility_adjusted_stops ? (1 + volatility_index) : 1 base_position_size = starting_capital * (max_risk_per_trade / 100) dynamic_size = dynamic_position_sizing ? base_position_size * volatility_multiplier : base_position_size base_atr = ta.atr(atr_length) adaptive_stop_multiplier = volatility_adjusted_stops ? (volatility_index > 0.02 ? atr_multiplier * 1.5 : atr_multiplier * 0.8) : atr_multiplier fib_618 = 1.618 fib_1618 = 2.618 fib_2618 = 3.618 // ============================================================================ // TRADE EXECUTION LOGIC // ============================================================================ var bool in_position = false var float entry_price = na var float stop_loss = na var float tp1 = na var float tp2 = na var float tp3 = na var bool is_long = false if institutional_long_signal and not in_position entry_price := close stop_loss := close – (base_atr * adaptive_stop_multiplier) risk_amount = entry_price – stop_loss tp1 := entry_price + (risk_amount * fib_618) tp2 := entry_price + (risk_amount * fib_1618) tp3 := entry_price + (risk_amount * fib_2618) is_long := true in_position := true if institutional_short_signal and not in_position entry_price := close stop_loss := close + (base_atr * adaptive_stop_multiplier) risk_amount = stop_loss – entry_price tp1 := entry_price – (risk_amount * fib_618) tp2 := entry_price – (risk_amount * fib_1618) tp3 := entry_price – (risk_amount * fib_2618) is_long := false in_position := true if in_position if is_long if low <= stop_loss or high >= tp3 in_position := false else if high >= stop_loss or low <= tp3 in_position := false // ============================================================================ // ADVANCED VISUALIZATION // ============================================================================ if show_institutional_levels and institutional_bull_ob box.new( x1 = bar_index[2], y1 = low[2], x2 = bar_index, y2 = high[2], border_color = color.new(#00ff88, 0), bgcolor = color.new(#00ff88, 85), border_width = 2, text = “BULL OBn” + str.tostring(final_confluence, “#.##”), text_color = color.white, text_size = size.small ) if show_institutional_levels and institutional_bear_ob box.new( x1 = bar_index[2], y1 = low[2], x2 = bar_index, y2 = high[2], border_color = color.new(#ff0044, 0), bgcolor = color.new(#ff0044, 85), border_width = 2, text = “BEAR OBn” + str.tostring(final_confluence, “#.##”), text_color = color.white, text_size = size.small ) if show_confluence_zones and final_confluence > confluence_threshold bgcolor( color.new(final_confluence > 0 ? #00ff88 : #ff0044, 95), title=”Confluence Zone” ) if show_probability_bands upper_band = ema_21 + (base_atr * 2) lower_band = ema_21 – (base_atr * 2) plot(upper_band, “Upper Probability Band”, color=color.new(#ffaa00, 50)) plot(lower_band, “Lower Probability Band”, color=color.new(#ffaa00, 50)) if institutional_long_signal label.new( x=bar_index, y=low, text=”🚀 INSTITUTIONAL LONGnConfluence: ” + str.tostring(final_confluence, “#.##”), color=color.new(#00ff88, 0), textcolor=color.white, style=label.style_label_up, size=size.normal ) if institutional_short_signal label.new( x=bar_index, y=high, text=”🔻 INSTITUTIONAL SHORTnConfluence: ” + str.tostring(final_confluence, “#.##”), color=color.new(#ff0044, 0), textcolor=color.white, style=label.style_label_down, size=size.normal ) if in_position line.new(bar_index, entry_price, bar_index + 1, entry_price, color=color.yellow, width=3, extend=extend.right) line.new(bar_index, stop_loss, bar_index + 1, stop_loss, color=color.red, width=2, style=line.style_dashed, extend=extend.right) line.new(bar_index, tp1, bar_index + 1, tp1, color=color.green, width=1, extend=extend.right) line.new(bar_index, tp2, bar_index + 1, tp2, color=color.green, width=1, extend=extend.right) line.new(bar_index, tp3, bar_index + 1, tp3, color=color.green, width=1, extend=extend.right) // ============================================================================ // PERFORMANCE ANALYTICS TABLE // ============================================================================ var table performance_table = table.new(position.top_right, 2, 8, bgcolor=color.new(color.black, 80), border_width=1) if barstate.islast table.cell(performance_table, 0, 0, “BlackRock Alpha Engine”, bgcolor=color.new(#1a1a1a, 0), text_color=color.white, text_size=size.small) table.cell(performance_table, 1, 0, “INSTITUTIONAL GRADE”, bgcolor=color.new(#1a1a1a, 0), text_color=#00ff88, text_size=size.small) table.cell(performance_table, 0, 1, “Confluence Score”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 1, str.tostring(final_confluence, “#.###”), text_color= final_confluence > 0 ? #00ff88 : #ff0044, text_size=size.tiny) table.cell(performance_table, 0, 2, “Market Regime”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 2, market_regime > 0 ? “VOLATILE” : “STABLE”, text_color= market_regime > 0 ? #ffaa00 : #88aaff, text_size=size.tiny) table.cell(performance_table, 0, 3, “Volatility Index”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 3, str.tostring(volatility_index * 100, “#.##”) + “%”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 0, 4, “Position Status”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 4, in_position ? (is_long ? “LONG” : “SHORT”) : “STANDBY”, text_color=in_position ? (is_long ? #00ff88 : #ff0044) : #ffaa00, text_size=size.tiny) table.cell(performance_table, 0, 5, “Technical Score”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 5, str.tostring(technical_score, “#.##”), text_color=color.white, text_size=size.tiny) table.cell(performance_table, 0, 6, “Smart Money Score”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 6, str.tostring(smart_money_score, “#.##”), text_color=color.white, text_size=size.tiny) table.cell(performance_table, 0, 7, “Sentiment Score”, text_color=color.white, text_size=size.tiny) table.cell(performance_table, 1, 7, str.tostring(sentiment_score, “#.##”), text_color=color.white, text_size=size.tiny) // ============================================================================ // ADVANCED ALERT SYSTEM // ============================================================================ alertcondition(institutional_long_signal, title=”🚀 Institutional Long Signal”, message=”BlackRock Alpha: INSTITUTIONAL LONG SIGNALnConfluence: {{plot_0}}nPrice: {{close}}nSymbol: {{ticker}}”) alertcondition(institutional_short_signal, title=”🔻 Institutional Short Signal”, message=”BlackRock Alpha: INSTITUTIONAL SHORT SIGNALnConfluence: {{plot_0}}nPrice: {{close}}nSymbol: {{ticker}}”) alertcondition(final_confluence > 0.9, title=”⚡ Maximum Confluence Alert”, message=”BlackRock Alpha: MAXIMUM CONFLUENCE DETECTEDnScore: {{plot_0}}nPrice: {{close}}nSymbol: {{ticker}}”) // ============================================================================ // PROPRIETARY EDGE CALCULATIONS // ============================================================================ microstructure_edge = ( (institutional_volume ? 0.3 : 0) + (strong_fvg ? 0.25: 0) + ((wyckoff_accumulation or wyckoff_distribution) ? 0.2 : 0) + ((auction_imbalance_up or auction_imbalance_down) ? 0.15: 0) + (balance_extension ? 0.1 : 0) ) plot(microstructure_edge, “Microstructure Edge”, color=color.new(#ff6600, 0), display=display.data_window) plot(final_confluence, “Final Confluence”, color=color.new(#00ffff, 0), display=display.data_window) submitted by /u/International-Ad9710 to r/pinescript |