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SMC Structures and FVGสวัสดีครับ! ผมจะอธิบายอินดิเคเตอร์ "SMC Structures and FVG + MACD" ที่คุณให้มาอย่างละเอียดในแต่ละส่วน เพื่อให้คุณเข้าใจการทำงานของมันอย่างถ่องแท้ครับ อินดิเคเตอร์นี้เป็นการผสมผสานแนวคิดของ Smart Money Concept (SMC) ซึ่งเน้นการวิเคราะห์โครงสร้างตลาด (Market Structure) และ Fair Value Gap (FVG) เข้ากับอินดิเคเตอร์ MACD เพื่อใช้เป็นตัวกรองหรือตัวยืนยันสัญญาณ Choch/BoS (Change of Character / Break of Structure) 1. ภาพรวมอินดิเคเตอร์ (Overall Purpose) อินดิเคเตอร์นี้มีจุดประสงค์หลักคือ: ระบุโครงสร้างตลาด: ตีเส้นและป้ายกำกับ Choch (Change of Character) และ BoS (Break of Structure) บนกราฟโดยอัตโนมัติ ผสานการยืนยันด้วย MACD: สัญญาณ Choch/BoS จะถูกพิจารณาก็ต่อเมื่อ MACD Histogram เกิดการตัดขึ้นหรือลง (Zero Cross) ในทิศทางที่สอดคล้องกัน แสดง Fair Value Gap (FVG): หากเปิดใช้งาน จะมีการตีกล่อง FVG บนกราฟ แสดงระดับ Fibonacci: คำนวณและแสดงระดับ Fibonacci ที่สำคัญตามโครงสร้างตลาดปัจจุบัน ปรับตาม Timeframe: การคำนวณและการแสดงผลทั้งหมดจะปรับตาม Timeframe ที่คุณกำลังใช้งานอยู่โดยอัตโนมัติ 2. ส่วนประกอบหลักของโค้ด (Code Breakdown) โค้ดนี้สามารถแบ่งออกเป็นส่วนหลัก ๆ ได้ดังนี้: 2.1 Inputs (การตั้งค่า) ส่วนนี้คือตัวแปรที่คุณสามารถปรับแต่งได้ในหน้าต่างการตั้งค่าของอินดิเคเตอร์ (คลิกที่รูปฟันเฟืองข้างชื่ออินดิเคเตอร์บนกราฟ) MACD Settings (ตั้งค่า MACD): fast_len: ความยาวของ Fast EMA สำหรับ MACD (ค่าเริ่มต้น 12) slow_len: ความยาวของ Slow EMA สำหรับ MACD (ค่าเริ่มต้น 26) signal_len: ความยาวของ Signal Line สำหรับ MACD (ค่าเริ่มต้น 9) = ta.macd(close, fast_len, slow_len, signal_len): คำนวณค่า MACD Line, Signal Line และ Histogram โดยใช้ราคาปิด (close) และค่าความยาวที่กำหนด is_bullish_macd_cross: ตรวจสอบว่า MACD Histogram ตัดขึ้นเหนือเส้น 0 (จากค่าลบเป็นบวก) is_bearish_macd_cross: ตรวจสอบว่า MACD Histogram ตัดลงใต้เส้น 0 (จากค่าบวกเป็นลบ) Fear Value Gap (FVG) Settings: isFvgToShow: (Boolean) เปิด/ปิดการแสดง FVG บนกราฟ bullishFvgColor: สีสำหรับ Bullish FVG bearishFvgColor: สีสำหรับ Bearish FVG mitigatedFvgColor: สีสำหรับ FVG ที่ถูก Mitigate (ลดทอน) แล้ว fvgHistoryNbr: จำนวน FVG ย้อนหลังที่จะแสดง isMitigatedFvgToReduce: (Boolean) เปิด/ปิดการลดขนาด FVG เมื่อถูก Mitigate Structures (โครงสร้างตลาด) Settings: isStructBodyCandleBreak: (Boolean) หากเป็น true การ Break จะต้องเกิดขึ้นด้วย เนื้อเทียน ที่ปิดเหนือ/ใต้ Swing High/Low หากเป็น false แค่ไส้เทียนทะลุก็ถือว่า Break isCurrentStructToShow: (Boolean) เปิด/ปิดการแสดงเส้นโครงสร้างตลาดปัจจุบัน (เส้นสีน้ำเงินในภาพตัวอย่าง) pivot_len: ความยาวของแท่งเทียนที่ใช้ในการมองหาจุด Pivot (Swing High/Low) ยิ่งค่าน้อยยิ่งจับ Swing เล็กๆ ได้, ยิ่งค่ามากยิ่งจับ Swing ใหญ่ๆ ได้ bullishBosColor, bearishBosColor: สีสำหรับเส้นและป้าย BOS ขาขึ้น/ขาลง bosLineStyleOption, bosLineWidth: สไตล์ (Solid, Dotted, Dashed) และความหนาของเส้น BOS bullishChochColor, bearishChochColor: สีสำหรับเส้นและป้าย CHoCH ขาขึ้น/ขาลง chochLineStyleOption, chochLineWidth: สไตล์ (Solid, Dotted, Dashed) และความหนาของเส้น CHoCH currentStructColor, currentStructLineStyleOption, currentStructLineWidth: สี, สไตล์ และความหนาของเส้นโครงสร้างตลาดปัจจุบัน structHistoryNbr: จำนวนการ Break (Choch/BoS) ย้อนหลังที่จะแสดง Structure Fibonacci (จากโค้ดต้นฉบับ): เป็นชุด Input สำหรับเปิด/ปิด, กำหนดค่า, สี, สไตล์ และความหนาของเส้น Fibonacci Levels ต่างๆ (0.786, 0.705, 0.618, 0.5, 0.382) ที่จะถูกคำนวณจากโครงสร้างตลาดปัจจุบัน 2.2 Helper Functions (ฟังก์ชันช่วยทำงาน) getLineStyle(lineOption): ฟังก์ชันนี้ใช้แปลงค่า String ที่เลือกจาก Input (เช่น "─", "┈", "╌") ให้เป็นรูปแบบ line.style_ ที่ Pine Script เข้าใจ get_structure_highest_bar(lookback): ฟังก์ชันนี้พยายามหา Bar Index ของแท่งเทียนที่ทำ Swing High ภายในช่วง lookback ที่กำหนด get_structure_lowest_bar(lookback): ฟังก์ชันนี้พยายามหา Bar Index ของแท่งเทียนที่ทำ Swing Low ภายในช่วง lookback ที่กำหนด is_structure_high_broken(...): ฟังก์ชันนี้ตรวจสอบว่าราคาปัจจุบันได้ Break เหนือ _structureHigh (Swing High) หรือไม่ โดยพิจารณาจาก _highStructBreakPrice (ราคาปิดหรือราคา High ขึ้นอยู่กับการตั้งค่า isStructBodyCandleBreak) FVGDraw(...): ฟังก์ชันนี้รับ Arrays ของ FVG Boxes, Types, Mitigation Status และ Labels มาประมวลผล เพื่ออัปเดตสถานะของ FVG (เช่น ถูก Mitigate หรือไม่) และปรับขนาด/ตำแหน่งของ FVG Box และ Label บนกราฟ 2.3 Global Variables (ตัวแปรทั่วทั้งอินดิเคเตอร์) เป็นตัวแปรที่ประกาศด้วย var ซึ่งหมายความว่าค่าของมันจะถูกเก็บไว้และอัปเดตในแต่ละแท่งเทียน (persists across bars) structureLines, structureLabels: Arrays สำหรับเก็บอ็อบเจกต์ line และ label ของเส้น Choch/BoS ที่วาดบนกราฟ fvgBoxes, fvgTypes, fvgLabels, isFvgMitigated: Arrays สำหรับเก็บข้อมูลของ FVG Boxes และสถานะต่างๆ structureHigh, structureLow: เก็บราคาของ Swing High/Low ที่สำคัญของโครงสร้างตลาดปัจจุบัน structureHighStartIndex, structureLowStartIndex: เก็บ Bar Index ของจุดเริ่มต้นของ Swing High/Low ที่สำคัญ structureDirection: เก็บสถานะของทิศทางโครงสร้างตลาด (1 = Bullish, 2 = Bearish, 0 = Undefined) fiboXPrice, fiboXStartIndex, fiboXLine, fiboXLabel: ตัวแปรสำหรับเก็บข้อมูลและอ็อบเจกต์ของเส้น Fibonacci Levels isBOSAlert, isCHOCHAlert: (Boolean) ใช้สำหรับส่งสัญญาณ Alert (หากมีการตั้งค่า Alert ไว้) 2.4 FVG Processing (การประมวลผล FVG) ส่วนนี้จะตรวจสอบเงื่อนไขการเกิด FVG (Bullish FVG: high < low , Bearish FVG: low > high ) หากเกิด FVG และ isFvgToShow เป็น true จะมีการสร้าง box และ label ใหม่เพื่อแสดง FVG บนกราฟ มีการจัดการ fvgBoxes และ fvgLabels เพื่อจำกัดจำนวน FVG ที่แสดงตาม fvgHistoryNbr และลบ FVG เก่าออก ฟังก์ชัน FVGDraw จะถูกเรียกเพื่ออัปเดตสถานะของ FVG (เช่น การถูก Mitigate) และปรับการแสดงผล 2.5 Structures Processing (การประมวลผลโครงสร้างตลาด) Initialization: ที่ bar_index == 0 (แท่งเทียนแรกของกราฟ) จะมีการกำหนดค่าเริ่มต้นให้กับ structureHigh, structureLow, structureHighStartIndex, structureLowStartIndex Finding Current High/Low: highest, highestBar, lowest, lowestBar ถูกใช้เพื่อหา High/Low ที่สุดและ Bar Index ของมันใน 10 แท่งล่าสุด (หรือทั้งหมดหากกราฟสั้นกว่า 10 แท่ง) Calculating Structure Max/Min Bar: structureMaxBar และ structureMinBar ใช้ฟังก์ชัน get_structure_highest_bar และ get_structure_lowest_bar เพื่อหา Bar Index ของ Swing High/Low ที่แท้จริง (ไม่ใช่แค่ High/Low ที่สุดใน lookback แต่เป็นจุด Pivot ที่สมบูรณ์) Break Price: lowStructBreakPrice และ highStructBreakPrice จะเป็นราคาปิด (close) หรือราคา Low/High ขึ้นอยู่กับ isStructBodyCandleBreak isStuctureLowBroken / isStructureHighBroken: เงื่อนไขเหล่านี้ตรวจสอบว่าราคาได้ทำลาย structureLow หรือ structureHigh หรือไม่ โดยพิจารณาจากราคา Break, ราคาแท่งก่อนหน้า และ Bar Index ของจุดเริ่มต้นโครงสร้าง Choch/BoS Logic (ส่วนสำคัญที่ถูกผสานกับ MACD): if(isStuctureLowBroken and is_bearish_macd_cross): นี่คือจุดที่ MACD เข้ามามีบทบาท หากราคาทำลาย structureLow (สัญญาณขาลง) และ MACD Histogram เกิด Bearish Zero Cross (is_bearish_macd_cross เป็น true) อินดิเคเตอร์จะพิจารณาว่าเป็น Choch หรือ BoS หาก structureDirection == 1 (เดิมเป็นขาขึ้น) หรือ 0 (ยังไม่กำหนด) จะตีเป็น "CHoCH" (เปลี่ยนทิศทางโครงสร้างเป็นขาลง) หาก structureDirection == 2 (เดิมเป็นขาลง) จะตีเป็น "BOS" (ยืนยันโครงสร้างขาลง) มีการสร้าง line.new และ label.new เพื่อวาดเส้นและป้ายกำกับ structureDirection จะถูกอัปเดตเป็น 1 (Bullish) structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow จะถูกอัปเดตเพื่อกำหนดโครงสร้างใหม่ else if(isStructureHighBroken and is_bullish_macd_cross): เช่นกันสำหรับขาขึ้น หากราคาทำลาย structureHigh (สัญญาณขาขึ้น) และ MACD Histogram เกิด Bullish Zero Cross (is_bullish_macd_cross เป็น true) อินดิเคเตอร์จะพิจารณาว่าเป็น Choch หรือ BoS หาก structureDirection == 2 (เดิมเป็นขาลง) หรือ 0 (ยังไม่กำหนด) จะตีเป็น "CHoCH" (เปลี่ยนทิศทางโครงสร้างเป็นขาขึ้น) หาก structureDirection == 1 (เดิมเป็นขาขึ้น) จะตีเป็น "BOS" (ยืนยันโครงสร้างขาขึ้น) มีการสร้าง line.new และ label.new เพื่อวาดเส้นและป้ายกำกับ structureDirection จะถูกอัปเดตเป็น 2 (Bearish) structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow จะถูกอัปเดตเพื่อกำหนดโครงสร้างใหม่ การลบเส้นเก่า: d.delete_line (หากไลบรารีทำงาน) จะถูกเรียกเพื่อลบเส้นและป้ายกำกับเก่าออกเมื่อจำนวนเกิน structHistoryNbr Updating Structure High/Low (else block): หากไม่มีการ Break เกิดขึ้น แต่ราคาปัจจุบันสูงกว่า structureHigh หรือต่ำกว่า structureLow ในทิศทางที่สอดคล้องกัน (เช่น ยังคงเป็นขาขึ้นและทำ High ใหม่) structureHigh หรือ structureLow จะถูกอัปเดตเพื่อติดตาม High/Low ที่สุดของโครงสร้างปัจจุบัน Current Structure Display: หาก isCurrentStructToShow เป็น true อินดิเคเตอร์จะวาดเส้น structureHighLine และ structureLowLine เพื่อแสดงขอบเขตของโครงสร้างตลาดปัจจุบัน Fibonacci Display: หาก isFiboXToShow เป็น true อินดิเคเตอร์จะคำนวณและวาดเส้น Fibonacci Levels ต่างๆ (0.786, 0.705, 0.618, 0.5, 0.382) โดยอิงจาก structureHigh และ structureLow ของโครงสร้างตลาดปัจจุบัน Alerts: alertcondition: ใช้สำหรับตั้งค่า Alert ใน TradingView เมื่อเกิดสัญญาณ BOS หรือ CHOCH plot(na): plot(na) เป็นคำสั่งที่สำคัญในอินดิเคเตอร์ที่ไม่ได้ต้องการพล็อต Series ของข้อมูลบนกราฟ (เช่น ไม่ได้พล็อตเส้น EMA หรือ RSI) แต่ใช้วาดอ็อบเจกต์ (Line, Label, Box) โดยตรง การมี plot(na) ช่วยให้ Pine Script รู้ว่าอินดิเคเตอร์นี้มีเอาต์พุตที่แสดงผลบนกราฟ แม้ว่าจะไม่ได้เป็น Series ที่พล็อตตามปกติก็ตาม 3. วิธีใช้งาน คัดลอกโค้ดทั้งหมด ที่อยู่ในบล็อก immersive ด้านบน ไปที่ TradingView และเปิดกราฟที่คุณต้องการ คลิกที่เมนู "Pine Editor" ที่อยู่ด้านล่างของหน้าจอ ลบโค้ดเดิมที่มีอยู่ และ วางโค้ดที่คัดลอกมา ลงไปแทน คลิกที่ปุ่ม "Add to Chart" อินดิเคเตอร์จะถูกเพิ่มลงในกราฟของคุณโดยอัตโนมัติ คุณสามารถคลิกที่รูปฟันเฟืองข้างชื่ออินดิเคเตอร์บนกราฟเพื่อเข้าถึงหน้าต่างการตั้งค่าและปรับแต่งตามความต้องการของคุณได้ Hello! I will explain the "SMC Structures and FVG + MACD" indicator you provided in detail, section by section, so you can fully understand how it works.This indicator combines the concepts of Smart Money Concept (SMC), which focuses on analyzing Market Structure and Fair Value Gaps (FVG), with the MACD indicator to serve as a filter or confirmation for Choch (Change of Character) and BoS (Break of Structure) signals.1. Overall PurposeThe main purposes of this indicator are:Identify Market Structure: Automatically draw lines and label Choch (Change of Character) and BoS (Break of Structure) on the chart.Integrate MACD Confirmation: Choch/BoS signals will only be considered when the MACD Histogram performs a cross (Zero Cross) in the corresponding direction.Display Fair Value Gap (FVG): If enabled, FVG boxes will be drawn on the chart.Display Fibonacci Levels: Calculate and display important Fibonacci levels based on the current market structure.Adapt to Timeframe: All calculations and displays will automatically adjust to the timeframe you are currently using.2. Code BreakdownThis code can be divided into the following main sections:2.1 Inputs (Settings)This section contains variables that you can adjust in the indicator's settings window (click the gear icon next to the indicator's name on the chart).MACD Settings:fast_len: Length of the Fast EMA for MACD (default 12)slow_len: Length of the Slow EMA for MACD (default 26)signal_len: Length of the Signal Line for MACD (default 9) = ta.macd(close, fast_len, slow_len, signal_len): Calculates the MACD Line, Signal Line, and Histogram using the closing price (close) and the specified lengths.is_bullish_macd_cross: Checks if the MACD Histogram crosses above the 0 line (from negative to positive).is_bearish_macd_cross: Checks if the MACD Histogram crosses below the 0 line (from positive to negative).Fear Value Gap (FVG) Settings:isFvgToShow: (Boolean) Enables/disables the display of FVG on the chart.bullishFvgColor: Color for Bullish FVG.bearishFvgColor: Color for Bearish FVG.mitigatedFvgColor: Color for FVG that has been mitigated.fvgHistoryNbr: Number of historical FVG to display.isMitigatedFvgToReduce: (Boolean) Enables/disables reducing the size of FVG when mitigated.Structures (โครงสร้างตลาด) Settings:isStructBodyCandleBreak: (Boolean) If true, the break must occur with the candle body closing above/below the Swing High/Low. If false, a wick break is sufficient.isCurrentStructToShow: (Boolean) Enables/disables the display of the current market structure lines (blue lines in the example image).pivot_len: Lookback length for identifying Pivot points (Swing High/Low). A smaller value captures smaller, more frequent swings; a larger value captures larger, more significant swings.bullishBosColor, bearishBosColor: Colors for bullish/bearish BOS lines and labels.bosLineStyleOption, bosLineWidth: Style (Solid, Dotted, Dashed) and width of BOS lines.bullishChochColor, bearishChochColor: Colors for bullish/bearish CHoCH lines and labels.chochLineStyleOption, chochLineWidth: Style (Solid, Dotted, Dashed) and width of CHoCH lines.currentStructColor, currentStructLineStyleOption, currentStructLineWidth: Color, style, and width of the current market structure lines.structHistoryNbr: Number of historical breaks (Choch/BoS) to display.Structure Fibonacci (from original code):A set of inputs to enable/disable, define values, colors, styles, and widths for various Fibonacci Levels (0.786, 0.705, 0.618, 0.5, 0.382) that will be calculated from the current market structure.2.2 Helper FunctionsgetLineStyle(lineOption): This function converts the selected string input (e.g., "─", "┈", "╌") into a line.style_ format understood by Pine Script.get_structure_highest_bar(lookback): This function attempts to find the Bar Index of the Swing High within the specified lookback period.get_structure_lowest_bar(lookback): This function attempts to find the Bar Index of the Swing Low within the specified lookback period.is_structure_high_broken(...): This function checks if the current price has broken above _structureHigh (Swing High), considering _highStructBreakPrice (closing price or high price depending on isStructBodyCandleBreak setting).FVGDraw(...): This function takes arrays of FVG Boxes, Types, Mitigation Status, and Labels to process and update the status of FVG (e.g., whether it's mitigated) and adjust the size/position of FVG Boxes and Labels on the chart.2.3 Global VariablesThese are variables declared with var, meaning their values are stored and updated on each bar (persists across bars).structureLines, structureLabels: Arrays to store line and label objects for Choch/BoS lines drawn on the chart.fvgBoxes, fvgTypes, fvgLabels, isFvgMitigated: Arrays to store FVG box data and their respective statuses.structureHigh, structureLow: Stores the price of the significant Swing High/Low of the current market structure.structureHighStartIndex, structureLowStartIndex: Stores the Bar Index of the start point of the significant Swing High/Low.structureDirection: Stores the status of the market structure direction (1 = Bullish, 2 = Bearish, 0 = Undefined).fiboXPrice, fiboXStartIndex, fiboXLine, fiboXLabel: Variables to store data and objects for Fibonacci Levels.isBOSAlert, isCHOCHAlert: (Boolean) Used to trigger alerts in TradingView (if alerts are configured).2.4 FVG ProcessingThis section checks the conditions for FVG formation (Bullish FVG: high < low , Bearish FVG: low > high ).If FVG occurs and isFvgToShow is true, a new box and label are created to display the FVG on the chart.fvgBoxes and fvgLabels are managed to limit the number of FVG displayed according to fvgHistoryNbr and remove older FVG.The FVGDraw function is called to update the FVG status (e.g., whether it's mitigated) and adjust its display.2.5 Structures ProcessingInitialization: At bar_index == 0 (the first bar of the chart), structureHigh, structureLow, structureHighStartIndex, and structureLowStartIndex are initialized.Finding Current High/Low: highest, highestBar, lowest, lowestBar are used to find the highest/lowest price and its Bar Index of it in the last 10 bars (or all bars if the chart is shorter than 10 bars).Calculating Structure Max/Min Bar: structureMaxBar and structureMinBar use get_structure_highest_bar and get_structure_lowest_bar functions to find the Bar Index of the true Swing High/Low (not just the highest/lowest in the lookback but a complete Pivot point).Break Price: lowStructBreakPrice and highStructBreakPrice will be the closing price (close) or the Low/High price, depending on the isStructBodyCandleBreak setting.isStuctureLowBroken / isStructureHighBroken: These conditions check if the price has broken structureLow or structureHigh, considering the break price, previous bar prices, and the Bar Index of the structure's starting point.Choch/BoS Logic (Key Integration with MACD):if(isStuctureLowBroken and is_bearish_macd_cross): This is where MACD plays a role. If the price breaks structureLow (bearish signal) AND the MACD Histogram performs a Bearish Zero Cross (is_bearish_macd_cross is true), the indicator will consider it a Choch or BoS.If structureDirection == 1 (previously bullish) or 0 (undefined), it will be labeled "CHoCH" (changing structure direction to bearish).If structureDirection == 2 (already bearish), it will be labeled "BOS" (confirming bearish structure).line.new and label.new are used to draw the line and label.structureDirection will be updated to 1 (Bullish).structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow will be updated to define the new structure.else if(isStructureHighBroken and is_bullish_macd_cross): Similarly for bullish breaks. If the price breaks structureHigh (bullish signal) AND the MACD Histogram performs a Bullish Zero Cross (is_bullish_macd_cross is true), the indicator will consider it a Choch or BoS.If structureDirection == 2 (previously bearish) or 0 (undefined), it will be labeled "CHoCH" (changing structure direction to bullish).If structureDirection == 1 (already bullish), it will be labeled "BOS" (confirming bullish structure).line.new and label.new are used to draw the line and label.structureDirection will be updated to 2 (Bearish).structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow will be updated to define the new structure.Deleting Old Lines: d.delete_line (if the library works) will be called to delete old lines and labels when their number exceeds structHistoryNbr.Updating Structure High/Low (else block): If no break occurs, but the current price is higher than structureHigh or lower than structureLow in the corresponding direction (e.g., still bullish and making a new high), structureHigh or structureLow will be updated to track the highest/lowest point of the current structure.Current Structure Display:If isCurrentStructToShow is true, the indicator draws structureHighLine and structureLowLine to show the boundaries of the current market structure.Fibonacci Display:If isFiboXToShow is true, the indicator calculates and draws various Fibonacci Levels (0.786, 0.705, 0.618, 0.5, 0.382) based on the structureHigh and structureLow of the current market structure.Alerts:alertcondition: Used to set up alerts in TradingView when BOS or CHOCH signals occur.plot(na):plot(na) is an important statement in indicators that do not plot data series directly on the chart (e.g., not plotting EMA or RSI lines) but instead draw objects (Line, Label, Box).Having plot(na) helps Pine Script recognize that this indicator has an output displayed on the chart, even if it's not a regularly plotted series.3. How to UseCopy all the code in the immersive block above.Go to TradingView and open your desired chart.Click on the "Pine Editor" menu at the bottom of the screen.Delete any existing code and paste the copied code in its place.Click the "Add to Chart" button.The indicator will be added to your chart automatically. You can click the gear icon next to the indicator's name on the chart to access the settings window and customize it to your needs.I hope this explanation helps you understand this indicator in detail. If anything is unclear, or you need further adjustments, please let me know.
Pine Script® göstergesi
Mr-7TRILL tarafından
Failed Breakout DetectionThis indicator is a reverse-engineered copy of the FBD Detection indicator published by xfuturesgod. The original indicator aimed at detecting "Failed Breakdowns". This version tracks the opposite signals, "Failed Breakouts". It was coded with the ES Futures 15 minute chart in mind but may be useful on other instruments and time frames. The original description, with terminology reversed to explain this version: 'Failed Breakouts' are a popular set up for short entries. In short, the set up requires: 1) A significant high is made ('initial high') 2) Initial high is undercut with a new high 3) Price action then 'reclaims' the initial high by moving +8-10 points from the initial high This script aims at detecting such set ups. It was coded with the ES Futures 15 minute chart in mind but may be useful on other instruments and time frames. Business Logic: 1) Uses pivot highs to detect 'significant' initial highs 2) Uses amplitude threshold to detect a new high above the initial high; used /u/ben_zen script for this 3) Looks for a valid reclaim - a red candle that occurs within 10 bars of the new high 4) Price must reclaim at least 8 points for the set up to be valid 5) If a signal is detected, the initial high value (pivot high) is stored in array that prevents duplicate signals from being generated. 6) FBO Signal is plotted on the chart with "X" 7) Pivot high detection is plotted on the chart with "P" and a label 8) New highs are plotted on the chart with a red triangle Notes: User input - My preference is to use the defaults as is, but as always feel free to experiment - Can modify pivot length but in my experience 10/10 work best for pivot highs - New high detection - 55 bars and 0.05 amplitude work well based on visual checks of signals - Can modify the number of points needed to reclaim a high, and the # of bars limit over which this must occur. Alerts: - Alerts are available for detection of new highs and detection of failed breakouts - Alerts are also available for these signals but only during 7:30PM-4PM EST - 'prime time' US trading hours Limitations: - Current version of the script only compares new highs to the most recent pivot high, does not look at anything prior to that - Best used as a discretionary signal
Pine Script® göstergesi
Merchantprince tarafından
2
Timeframe PivotsUse this tool to plot open prices from any timeframe as a pivot level with the option to go advanced and turn on extensions (instructions below), which review the relationship between previous and current open prices to build range extensions up to six levels wide. Please be aware extensions, nor vwap are not enabled by default! It is up to the user to determine how they wish to setup this indicator. Please read the full description for utilizing this indicator so that it's well known the complete feature set and understanding of how to enable additional plots, complete instruction is provided for all users below. Default configuration example: To enable extensions the user must open the indicator configuration by clicking the gear icon for "Timeframe Pivots", depending on screen resolution scrolling with mouse may need to occur in order to find the section labeled "Extensions", use the mouse or equivalent human interface device to check the checkbox to the right of the color plots and line type drop down. Extensions enabled example: Timeframe Selection Timeframes available to the indicator are any timeframe the platform makes available to the user by default, or also if the TradingView user has higher tier plan to create custom timeframes - those should be available as well. To adjust timeframe the user must open the indicator configuration by clicking the gear icon for "Timeframe Pivots", depending on screen resolution scrolling with mouse may need to occur in order to find the input labeled "Timeframe", use the mouse or equivalent human interface device select the drop down and select timeframe suitable to users application. How the extension width and extensions are calculated: The exact process takes the new timeframe change open price calculates the difference between prior open, once that has been completed then it's divided in half to build extensions. Code example: Extension Width = (Open - Open ) / 2 How the extensions are calculated: // +1 for positive extension, -1 for negative extension (Extension Width * (Configured Multiplier * 1)) + Pivot Open Price +1 Extension: $5 * (1.0 * 1) + $400 = $405 -1 Extension: $5 * (1.0 * -1) + $400 = $395 So it should be established how each projected extension, either positive or negative, is created. Range bound market detection and notes: One note regarding the ranges, sometimes the open prices of each period can be close in proximity to their predecessor, there's not enough range to build meaningful projections. In these situations this means the market is most likely range bound and prior range data is utilized to continue providing guidance. This addresses an issue with other pivot indicators that will instead blindly follow price and present useless pivot ranges. It does this through detection of average half range widths, the last 14 ranges to be exact, if the current, (open - open / 2), half range width is smaller than the average, prior half range width will be used. Code example: // assume past half range widths are 10, 8, 9, 5, 14, 7, 7, 9, 10, 10, 4, 7, 7, 8 float v_halfRangeWidthToUseForExtensions = na v_priorHalfRangeWidth = 10 v_avgHalfRangeWidth = 8.2 // past range widths sum = 115 / 14 v_newHalfRangeWidthToUseForExtensions = 2 // new open - open is tiny compared to avg if v_newHalfRangeWidthToUseForExtensions < v_avgHalfRangeWidth // replace new half range width with previous one v_newHalfRangeWidthToUseForExtensions := v_priorHalfRangeWidth In the code example above if the new half range width was above or equal to the rolling average, no adjustment would be made by the indicator. VWAP Additional feature of showing vwap, anchored to the same timeframe as the pivot, provides a trend and volume analysis within the confines of the pivots range. The user must open the indicator configuration by clicking the gear icon for "Timeframe Pivots", scroll using mouse to the "VWAP" section and click the checkbox next to the "Source" field, past the color plots. They are not enabled by default! The user can also add the bands for VWAP by clicking the checkbox next to the "Bands" field, past the color plots. They are not enabled by default! VWAP calculations begin from open price of new timeframe change, then afterwards the "Source" set is utilized, the default is HLC3 which is standard for VWAP indicators. Multiple Timeframe Analysis (MTFA) It's simple to create a unique combination of favored timeframes for multiple timeframe analysis, consider daily, weekly and monthly combined analysis for powerful indications of market sentiment and directional bias. Example MTFA demonstration: Why was this created? I created this while investigating the efficacy of open price ranges, it became apparent that these pivot ranges are some of the more price respecting pivots I've ever observed. I also grew tired of lack of price adherence to other pivot indicators widely available. There exists a relationship between each timeframes open price in comparison to prior open price, if the market is willing to navigate to a prior lower open price from higher open price, it could be perceived as bearish and the extensions (if enabled as instructed above), could be suitable range based projections for future price movements. Example comparison: As can be seen, and there are many examples, where Timeframe Pivots provides more discreet levels and potential explanations for price movements.
Pine Script® göstergesi
TradeSeekers tarafından
17
Percent Change of Day [ilovealgotrading] OVERVIEW: This indicator aims to effectively show us the percentage change of the price within the time frame we have chosen. What is the purpose of this indicator? This indicator shows how the price changes for each bar at different time frames we have chosen. By examining the percentage change in different time periods, we can easily look at the change in the face of the market during the time interval. Also if the price is above or below the value of 0 during the specified time, the color of our percentage line changes. IMPLEMENTATION DETAILS: First of all, let's understand How to Calculate Percent Change? The difference between the old and new value of a quantity given in percentages is known as a percent change. It's rather simple to calculate the % difference between two given quantities. The formula is given by; Example The price of a kilo of rice went from 10$ to12.5$, what is the percentage change? Explanation • The old value of sugar = $ 10 • New value = $12.5 • Now apply the percent change formula; • Percentage change = ×100% = x 100% = (2.5/10) x 100% = 25% In this case, the percent change is positive and therefore, it is an increase. How Is Percentage Change Used in Finance? In the world of finance, percentage change is frequently used to analyze changes in the value of stocks or major market indexes over time. Percentage change is used for many purposes in finance, most notably to track the price change of stocks market and crypto market. What can we change from the settings panel ? We can set time frame setting of the percentage change from place number 1 We are able to adjust the changing color if the percentage change is above or below zero from place 2 and 3 ALSO: Please do not open trades without properly managing your risk and psychology!!! If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Pine Script® göstergesi
projeadam tarafından
3
Failed Breakdown Detection'Failed Breakdowns' are a popular set up for long entries. In short, the set up requires: 1) A significant low is made ('initial low') 2) Initial low is undercut with a new low 3) Price action then 'reclaims' the initial low by moving +8-10 points from the initial low This script aims at detecting such set ups. It was coded with the ES Futures 15 minute chart in mind but may be useful on other instruments and time frames. Business Logic: 1) Uses pivot lows to detect 'significant' initial lows 2) Uses amplitude threshold to detect a new low beneath the initial low; used /u/ben_zen script for this 3) Looks for a valid reclaim - a green candle that occurs within 10 bars of the new low 4) Price must reclaim at least 8 points for the set up to be valid 5) If a signal is detected, the initial low value (pivot low) is stored in array that prevents duplicate signals from being generated. 6) FBD Signal is plotted on the chart with "X" 7) Pivot low detection is plotted on the chart with "P" and a label 8) New lows are plotted on the chart with a blue triangle Notes: User input - My preference is to use the defaults as is, but as always feel free to experiment - Can modify pivot length but in my experience 10/10 work best for pivot lows - New low detection - 55 bars and 0.05 amplitude work well based on visual checks of signals - Can modify the number of points needed to reclaim a low, and the # of bars limit under which this must occur. Alerts: - Alerts are available for detection of new lows and detection of failed breakdowns - Alerts are also available for these signals but only during 7:30PM-4PM EST - 'prime time' US trading hours Limitations: - Current version of the script only compares new lows to the most recent pivot low, does not look at anything prior to that - Best used as a discretionary signal Visit /u/ben_zen's Profile: www.tradingview.com Profile Link www.tradingview.com
Pine Script® göstergesi
xfuturesgod tarafından
20
TASC 2022.10 RS VA EMA█ OVERVIEW TASC's October 2022 edition Traders' Tips includes the second part of the "​Relative Strength Moving Averages" article series authored by Vitali Apirine. This is the code that implements the ​Relative Strength Volume-Adjusted ​Exponential Moving Average (​RS VA ​EMA) presented in this publication. █ CONCEPTS In his article series, the author argues that the relative strength of price, ​volume, and ​volatility can potentially be used to filter price movements and define turning points. In particular, the ​RS VA ​​EMA indicator is designed to account for the ​relative strength of ​volume. Like the traditional ​ exponential moving average (​EMA) , it is a lagging trend-following indicator. The difference is that it responds more quickly. In a trading strategy, ​​RS VA ​EMA is suggested to be used in combination with ​​EMA of the same length to determine the overall trend or in combination with ​RS VA ​EMA of a different length to identify turning points and filter price movements. █ CALCULATIONS The calculation of ​RS VA ​EMA is based on the concept of ​volume strength (VS). By definition, VS measures the difference between "positive" and "negative" ​volume flow. ​Volume is indicated as "positive" when the close is higher than the previous close and "negative" when the close is below the previous close. The following steps are used in the calculation process: • Calculate the ​volume strength (VS) of a given length. • Multiply VS by a predefined multiplier and calculate the ​EMA of the resulting time series. The values of 10,10,10 are the typical input settings for ​RS VA ​EMA, where the first parameter is the length of the moving average, the second is the length of VS, and the third is the ​volume strength multiplier.
Pine Script® göstergesi
PineCodersTASC tarafından
2
Liquidity Sweep Breakout - LSBLiquidity Sweep Breakout - LSB A professional session-based breakout system designed for OANDA:USDJPY and other JPY pairs. Not guesswork, but precision - built on detailed observation of institutional moves to capture clear trade direction daily. Master the Market’s Daily Bank Flow. --- Strategy Detail: I discovered this strategy after carefully studying how Japanese banks influence the forex market during their daily settlement period. Banks are some of the biggest players in the financial world, and when they adjust or settle their accounts in the morning, it often creates a push in the market. From years of observation, I noticed a consistent pattern, once banks finish their settlements, the market usually continues moving in the same direction that was formed right after those actions. This daily banking flow often sets the tone for the entire trading session, especially for JPY pairs like USDJPY. To capture this move, I built the indicator so that it follows the bank-driven trend with clear rules for entries, stop-loss (SL), and take-profit (TP). The system is designed with professional risk management in mind. By default, it assumes a $10,000 account size, risks only 1% of that balance per trade, and targets a 1:1.5 reward-to-risk ratio. This means for every $100 risked, the potential profit is $150. Such controlled risk makes the system safer and more sustainable for long-term traders. At the same time, users are not limited to this setup, they can adjust the account balance in the settings, and the indicator will automatically recalculate the lot size and risk levels based on their own capital. This ensures the strategy works for small accounts and larger accounts alike. 🌍 Why It Works Fundamentally driven: Based on **daily Japanese banking settlement flows**. Session-specific precision: Targets the exact window when USDJPY liquidity reshapes. Risk-managed: Always calculates lot size based on account and risk preferences. Automatable: With webhook + MT5 EA, it can be fully hands-free. --- ✅ Recommended Pair: USDJPY (best observed behavior). Timeframe: 3-Minute chart. Platform: TradingView Premium (for webhooks). Execution: MT5 via EA. --- 🔎 Strategy Concept The Tokyo Magic Breakout (TMB) is built on years of session observation and the unique daily rhythm of the Japanese banking system. Every morning between 5:50 AM – 6:10 AM PKT (09:50 – 10:10 JST), Japanese banks perform daily reconciliation and settlement. This often sets the tone for the USDJPY direction of the day. This strategy isolates that critical moment of liquidity adjustment and waits for a clean breakout confirmation. Instead of chasing noise, it executes only when price action is aligned with the Tokyo market’s hidden flows. --- 🕒 Timing Logic Session Start: 5:00 AM PKT (Tokyo market open range). Magic Candle: The 5:54 AM PKT candle is marked as the reference “breakout selector.” Checkpoints: First confirmation at 6:30 AM PKT, then every 15 minutes until 8:30 AM PKT. * If price stays inside the magic range → wait. * If a breakout happens but the candle wick touches the range → wait for the next checkpoint. * If by 8:30 AM PKT no clean breakout occurs → the day is marked as No Trade Day (NTD). 👉 Recommended timeframe: 3-Minute chart (3M) for precise signals. --- 📈 Trade Execution Entry: Clean break above/below the magic candle’s range. Stop-Loss: Opposite side of the Tokyo session high/low. Take-Profit: Calculated by Reward\:Risk ratio (default 1.5:1). Lot Size: Auto-calculated based on your risk model: * Fixed Dollar * % of Equity * Conservative (minimum of both). Visuals include: ✅ Entry/SL/TP lines ✅ Shaded risk (red) and reward (green) zones ✅ Trade labels (Buy/Sell with lot size & levels) ✅ TP/SL hit markers --- 🔔 Alerts & Automation (AutoTMB) This strategy is fully automation-ready with EA + MT5: 1. Enable alerts in TMB settings. 2. Insert your PineConnector License Key. 3. Configure your risk management preferences. 4. Create a TradingView alert → in the message box simply type: Pine Script® {{alert_message}} and set the EA webhook. Now, every breakout trade (with exact entry, SL, TP, and lot size) is sent instantly. 👉 On your MT5: * Install the EA. * Use the same license key. * Run it on a VPS or local MT5 terminal. You now have a hands-free trading system: AutoTMB.
Pine Script® stratejisi
humayunmha tarafından
GTrader-ICT All In One-Comumnity VersionMeet the **GTrader-ICT All In One **, a comprehensive toolkit designed to integrate key Inner Circle Trader (ICT) concepts directly onto your chart. This powerful overlay indicator consolidates multiple essential tools, streamlining your technical analysis and helping you identify key temporal and price-based events. 📚 References & Inspiration This indicator stands on the shoulders of giants. With the help of **tradeforopp** and **LuxAlgo**. The concepts and some implementation details were referenced from the following excellent, publicly available scripts: ICT Killzones: The session drawing and pivot logic is adapted from tradeforopp ICT Macros: The macro detection and plotting functionality is inspired by the work of Lux Algo , particularly their widely-used indicators covering ICT concepts. 🎯 Core Features * **ICT Killzones:** Visualize critical trading sessions with customizable boxes. You can easily toggle and style the **Asia**, **London**, and **New York (AM, Lunch, PM)** sessions to focus on the liquidity and volatility that matter most to your strategy. * Fully customizable session times and colors. * Timezone support to align sessions with your local or preferred trading time (defaults to `America/New_York`). * **ICT Macros:** Automatically identify and plot specific, short-duration time windows where institutional algorithms are known to be active (e.g., `09:50-10:10`, `14:50-15:10`, etc.). * Plots the high/low range of the macro, providing clear levels of interest. * Utilizes 1-minute data for precision, even when viewing on 3-minute or 5-minute charts. 📚 Optimization over the other original indicators We add the custom input for macros session, users just need to input the from/to hour: minute format, and they will be converted into session objects in pinescript The macro draws function is optimized, removing redundant draws, leading to better performance Add "Distance from Macro Line to Chart" option Add "Session Drawings Limit" for better performance ⚠️ Notes on TradingView Warnings You may encounter some warnings from TradingView when using this script. These are generally expected due to the script's advanced, event-driven nature: 1. **Function Call Consistency:** The function 'box.new' should be called on each calculation for consistency, which may appear. This happens because drawing elements (like session boxes) are intentionally created only on the *first bar* of a new session, not on every single bar. This is a necessary design choice for performance and to prevent duplicate drawings. 2. **Potential for Repainting/Slow Load:** The **Macro** feature uses the `request.security_lower_tf()` function to get accurate 1-minute data. This can trigger warnings about performance or slow loading times. This is a known trade-off for achieving the precision required for the feature.
Pine Script® göstergesi
GTrader_indicators tarafından
5
ES Gap Trading Levels# ES Gap Trading Levels ## Overview A professional gap trading indicator designed specifically for ES Futures traders. This indicator automatically captures the closing price at 3:59 PM ET (NYSE close) and immediately displays key gap levels for the evening trading session starting at 6:00 PM ET. ## Key Features ### ✅ **Automatic Gap Level Detection** - Captures ES Futures closing price at 3:59-4:00 PM ET - Instantly displays gap levels for immediate session planning - Resets daily for fresh gap analysis ### ✅ **Six Critical Gap Levels** - **±10 Points** (White lines) - Short-term gap targets - **±20 Points** (Light Blue lines) - Medium gap targets - **±30 Points** (Red lines) - Extended gap targets ### ✅ **Professional Display** - Clean horizontal lines with customizable colors - Clear labels showing point values (+30, +20, +10, -10, -20, -30) - Gap levels table showing exact price targets - Optional closing price reference line ### ✅ **Customizable Settings** - Adjustable line colors, width, and extension - Toggle labels and reference table on/off - Manual closing price override for testing - Debug mode for troubleshooting ### ✅ **Smart Management** - Automatic cleanup of previous day's levels - Lines appear immediately after market close - Optimized for ES1!, MES1!, and other ES futures contracts ## How It Works 1. **Market Close Capture**: At 3:59 PM ET, the indicator captures the ES closing price 2. **Instant Display**: Gap levels immediately appear on your chart 3. **Evening Session Ready**: Lines are positioned for 6:00 PM ET session start 4. **Daily Reset**: Old levels are automatically cleared each new trading day ## Perfect For: - Gap trading strategies - Overnight futures trading - ES futures scalping - Session transition analysis - Risk management levels ## Usage Tips: - Best used on 1-15 minute ES futures charts - Ensure chart timezone shows ET times - Use manual mode for backtesting specific dates - Combine with volume and momentum indicators ## Settings Guide: - **Display Settings**: Control lines, labels, and table visibility - **Colors**: Customize each gap level color scheme - **Manual Settings**: Override closing price for testing - **Debug**: View time detection and diagnostic information *Designed by traders, for traders. Clean, professional, and reliable gap level detection for serious ES futures trading.*
Pine Script® göstergesi
CeresTrader tarafından
Statistics plot1. setting the price range At the beginning of the script, set the price range (interval). Price ranges are used to divide prices into several groups (buckets) and record how many prices have been reached within each group. For example, setting the price range to “10” will divide the price into intervals 0-10, 10-20, 20-30, and so on. The price range can also be set manually by the user or automatically calculated based on the initial price. This allows for flexibility in adjusting price ranges for different assets and different time frames. 2. aggregate the number of times a price is reached Record how many times the price reached each price range (e.g., 100-110, 110-120, etc.). This aggregate data is stored in a data structure called an array. Each element of the array corresponds to a price range, and when a price reaches that range, the corresponding array value is incremented by one. This process is performed in real time, tracking price movements. 3. initializing and extending price ranges The first bar of the script (when the chart is first loaded) divides the price ranges into several groups and initializes a count of 0 for each range. When a price reaches a new range, the array is expanded as needed to add the new price range. This allows the script to work with any price movement, even if the price range continues to grow. 4. visualize the number of price arrivals with a histogram The aggregated number of arrivals per price range is visually displayed in the form of a histogram. This histogram is designed to allow the user to see at a glance which price range is being reached most frequently. For example, if prices frequently reach the 100-110 range, the histogram bar corresponding to that range will appear higher than the other ranges. This allows you to visually identify price “dwell points” or support and resistance levels. 5. display of moving averages A moving average (MA) of the number of times a price has been reached is drawn above the histogram. Moving averages are indicators that show a smooth trend for the number of price arrivals and are useful for understanding the overall direction of price movements. The duration of the moving average (how many data points it is calculated based on) can be set by the user. This allows for flexible analysis of short or long term price trends. 6. 6. price range tracking and labeling The script keeps track of which price range the current price is located in. Based on this, information related to the current price range is displayed on the chart as labels. In particular, labels indicate the beginning and end points of the price range, including which range the price was in at the beginning and which range the price reached at the end. These labels are a useful feature to visually identify price ranges on the chart. 7. labeling of current price range To confirm which price range the current price is in, when a price reaches a specific price range, a label corresponding to that price range is displayed. This label indicates the position of the price in real-time, allowing traders to visually track where the current price is in the area. 8. calculating the start and end points of the range The script calculates the start and end points of a range with a non-zero number of price arrivals to find the minimum and maximum of the range. This calculation allows you to see where prices are concentrated within a range. 9. out-of-range price processing When a price reaches outside the range, the script automatically adds the array element corresponding to that price range and inserts the data in the appropriate location for the count. This allows the script to follow the price as it moves unexpectedly.
Pine Script® göstergesi
Unjuno tarafından
NSDT Average 6This is a pretty simple concept that we were asked to put together. It uses 6 Moving Averages, and takes the average of each one, then averages them all together. If you don't want to use 6, and only 3 for example, then just enter the same length in two of the input fields as pairs. Example: For 6, you could use 10, 20, 30, 40, 50, 60 For 3, you could use 10, 10, 50, 50, 100, 100 It doesn't ploy 6 MA's, it only plots one - the result of the average of an average of an average, etc.. Publishing open source so other can modify as needed.
Pine Script® göstergesi
NorthStarDayTrading tarafından
1
10yr, 20yr, 30yr Averages: Month/Month % Change; SeasonalityCalculates 10yr, 20yr and 30yr averages for month/month % change ~shows seasonal tendencies in assets (best in commodities). In above chart: August is a seasonally bullish month for Gold: All the averages agree. And January is the most seasonally bullish month. ~averages represent current month/previous month. i.e. Jan22 average % change represents whole of jan22 / whole of dec21 ~designed for daily timeframe only: I found calling monthly data too buggy to work with, and I thought weekly basis may be less precise (though it would certainly reduce calculation time!) ~choose input year, and see the previous 10yrs of monthly % change readings, and previous 10yrs Average, 20yr Average, 30yr Average for the respective month. Labels table is always anchored to input year. ~user inputs: colors | label sizes | decimal places | source expression for averages | year | show/hide various sections ~multi-yr averges always print, i.e if only 10yrs history => 10yr Av = 20yr Av = 30yr Av. 'History Available' label helps here. Based on my previously publised script: "Month/Month Percentage % Change, Historical; Seasonal Tendency" Publishing this as seperate indicator because: ~significantly slower to load (around 13 seconds) ~non-premium users may not have the historical bars available to use 20yr or 30yr averages =>> prefer the lite/speedier version ~~tips~~ ~after loading, touch the new right scale; then can drag the table as you like and seperate it from price chart ##Debugging/tweaking## Comment-in the block at the end: ~test/verifify specific array elements elements. ~see the script calculation/load time ~~other ideas ~~ ~could tweak the array.slice values in lines 313 - 355 to show the last 3 consecutive 10yr averages instead (i.e. change 0, 10 | 0,20 | 0, 30 to 0, 10 | 10, 20 | 20,30) ~add 40yr average by adding another block to each of the array functions, and tweaking the respective labels after line 313 (though this would likely add another 5 seconds to the load time) ~use alternative method for getting obtaining multi-year values from individual month elements. I used array.avg. You could try array.median, array.mode, array.variance, array.max, array.min (lines 313-355)
Pine Script® göstergesi
twingall tarafından
23
TASC 2022.05 Relative Strength Exponential Moving Average█ OVERVIEW TASC's May 2022 edition Traders' Tips includes the "Relative Strength Moving Averages" article authored by Vitali Apirine. This is the code implementing the Relative Strength Exponential Moving Average (​RS EMA) indicator introduced in this publication. █ CONCEPTS ​RS EMA is an adaptive trend-following indicator with reduced lag characteristics. By design, this was made possible by harnessing the relative strength of price. It operates in a similar fashion to a traditional EMA, but it has an improved response to price fluctuations. In a trading strategy, ​RS EMA can be used in conjunction with an EMA of the same length to identify the overall trend (see the preview chart). Alternatively, ​RS EMAs with different lengths can define turning points and filter price movements. ​RS EMA is an adaptive trend-following indicator with reduced lag characteristics. By design, this was made possible by harnessing the relative strength of price. It operates in a similar fashion to a traditional EMA, but it has an improved response to price fluctuations. █ CALCULATIONS The following steps are used in the calculation process: • Calculate the relative strength (​RS) of a given length. • Multiply ​RS by a chosen coefficient (multiplier) to adapt the EMA filtering the original time series. Calculate the EMA of the resulting time series. The author recommends ​RS EMA(10,10,10) as typical settings, where the first parameter is the EMA length, the second parameter is the ​RS length, and the third parameter is the ​RS multiplier. Other values may be substituted depending on your trading style and goals.
Pine Script® göstergesi
PineCodersTASC tarafından
4
Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis. ## 1. Introduction Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017). The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines: - Classical monetary policy rules (Taylor Rule framework) - Real-time macroeconomic indicators from FRED database - Financial market conditions and term structure analysis - Labor market dynamics and inflation expectations - Regime-dependent parameter adjustments This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes. ## 2. Literature Review and Theoretical Foundation ### 2.1 Taylor Rule Framework The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals: rt = r + πt + α(πt - π) + β(yt - y) Where: - rt = nominal federal funds rate - r = equilibrium real interest rate - πt = inflation rate - π = inflation target - yt - y = output gap - α, β = policy response coefficients Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions. ### 2.2 Data-Dependent Monetary Policy The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions. ### 2.3 Financial Conditions and Monetary Transmission The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010). ### 2.4 Labor Market Indicators The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments. ## 3. Methodology ### 3.1 Model Architecture The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index: #### Component 1: Taylor Rule Analysis (Weight: 25%) Implements real-time Taylor Rule calculation using FRED data: - Core PCE inflation (Fed's preferred measure) - Unemployment gap proxy for output gap - Dynamic neutral rate estimation - Regime-dependent parameter adjustments #### Component 2: Employment Conditions (Weight: 20%) Multi-dimensional labor market assessment: - Unemployment gap relative to NAIRU estimates - JOLTS job openings momentum - Average hourly earnings growth - Beveridge curve position analysis #### Component 3: Financial Conditions (Weight: 18%) Comprehensive financial market evaluation: - Chicago Fed NFCI real-time data - Yield curve shape and term structure - Credit growth and lending conditions - Market volatility and risk premia #### Component 4: Inflation Expectations (Weight: 15%) Forward-looking inflation analysis: - TIPS breakeven inflation rates (5Y, 10Y) - Market-based inflation expectations - Inflation momentum and persistence measures - Phillips curve relationship dynamics #### Component 5: Growth Momentum (Weight: 12%) Real economic activity assessment: - Real GDP growth trends - Economic momentum indicators - Business cycle position analysis - Sectoral growth distribution #### Component 6: Liquidity Conditions (Weight: 10%) Monetary aggregates and credit analysis: - M2 money supply growth - Commercial and industrial lending - Bank lending standards surveys - Quantitative easing effects assessment ### 3.2 Normalization and Scaling Each component undergoes robust statistical normalization using rolling z-score methodology: Zi,t = (Xi,t - μi,t-n) / σi,t-n Where: - Xi,t = raw indicator value - μi,t-n = rolling mean over n periods - σi,t-n = rolling standard deviation over n periods - Z-scores bounded at ±3 to prevent outlier distortion ### 3.3 Regime Detection and Adaptation The model incorporates dynamic regime detection based on: - Policy volatility measures - Market stress indicators (VIX-based) - Fed communication tone analysis - Crisis sensitivity parameters Regime classifications: 1. Crisis: Emergency policy measures likely 2. Tightening: Restrictive monetary policy cycle 3. Easing: Accommodative monetary policy cycle 4. Neutral: Stable policy maintenance ### 3.4 Composite Index Construction The final AFDFM index combines weighted components: AFDFMt = Σ wi × Zi,t × Rt Where: - wi = component weights (research-calibrated) - Zi,t = normalized component scores - Rt = regime multiplier (1.0-1.5) Index scaled to range for intuitive interpretation. ### 3.5 Decision Probability Calculation Fed decision probabilities derived through empirical mapping: P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100) P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100) P(Hold) = 100 - |AFDFMt| × 15 Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds). ## 4. Data Sources and Real-Time Implementation ### 4.1 FRED Database Integration - Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted - Unemployment Rate (UNRATE): Monthly, seasonally adjusted - Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate - Federal Funds Rate (FEDFUNDS): Monthly average - Treasury Yields (GS2, GS10): Daily constant maturity - TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data ### 4.2 High-Frequency Financial Data - Chicago Fed NFCI: Weekly financial conditions - JOLTS Job Openings (JTSJOL): Monthly labor market data - Average Hourly Earnings (AHETPI): Monthly wage data - M2 Money Supply (M2SL): Monthly monetary aggregates - Commercial Loans (BUSLOANS): Weekly credit data ### 4.3 Market-Based Indicators - VIX Index: Real-time volatility measure - S&P; 500: Market sentiment proxy - DXY Index: Dollar strength indicator ## 5. Model Validation and Performance ### 5.1 Historical Backtesting (2017-2024) Comprehensive backtesting across multiple Fed policy cycles demonstrates: - Signal Accuracy: 78% correct directional predictions - Timing Precision: 2.3 meetings average lead time - Crisis Detection: 100% accuracy in identifying emergency measures - False Signal Rate: 12% (within acceptable research parameters) ### 5.2 Regime-Specific Performance Tightening Cycles (2017-2018, 2022-2023): - Hawkish signal accuracy: 82% - Average prediction lead: 1.8 meetings - False positive rate: 8% Easing Cycles (2019, 2020, 2024): - Dovish signal accuracy: 85% - Average prediction lead: 2.1 meetings - Crisis mode detection: 100% Neutral Periods: - Hold prediction accuracy: 73% - Regime stability detection: 89% ### 5.3 Comparative Analysis AFDFM performance compared to alternative methods: - Fed Funds Futures: Similar accuracy, lower lead time - Economic Surveys: Higher accuracy, comparable timing - Simple Taylor Rule: Lower accuracy, insufficient complexity - Market-Based Models: Similar performance, higher volatility ## 6. Practical Applications and Use Cases ### 6.1 Institutional Investment Management - Fixed Income Portfolio Positioning: Duration and curve strategies - Currency Trading: Dollar-based carry trade optimization - Risk Management: Interest rate exposure hedging - Asset Allocation: Regime-based tactical allocation ### 6.2 Corporate Treasury Management - Debt Issuance Timing: Optimal financing windows - Interest Rate Hedging: Derivative strategy implementation - Cash Management: Short-term investment decisions - Capital Structure Planning: Long-term financing optimization ### 6.3 Academic Research Applications - Monetary Policy Analysis: Fed behavior studies - Market Efficiency Research: Information incorporation speed - Economic Forecasting: Multi-factor model validation - Policy Impact Assessment: Transmission mechanism analysis ## 7. Model Limitations and Risk Factors ### 7.1 Data Dependency - Revision Risk: Economic data subject to subsequent revisions - Availability Lag: Some indicators released with delays - Quality Variations: Market disruptions affect data reliability - Structural Breaks: Economic relationship changes over time ### 7.2 Model Assumptions - Linear Relationships: Complex non-linear dynamics simplified - Parameter Stability: Component weights may require recalibration - Regime Classification: Subjective threshold determinations - Market Efficiency: Assumes rational information processing ### 7.3 Implementation Risks - Technology Dependence: Real-time data feed requirements - Complexity Management: Multi-component coordination challenges - User Interpretation: Requires sophisticated economic understanding - Regulatory Changes: Fed framework evolution may require updates ## 8. Future Research Directions ### 8.1 Machine Learning Integration - Neural Network Enhancement: Deep learning pattern recognition - Natural Language Processing: Fed communication sentiment analysis - Ensemble Methods: Multiple model combination strategies - Adaptive Learning: Dynamic parameter optimization ### 8.2 International Expansion - Multi-Central Bank Models: ECB, BOJ, BOE integration - Cross-Border Spillovers: International policy coordination - Currency Impact Analysis: Global monetary policy effects - Emerging Market Extensions: Developing economy applications ### 8.3 Alternative Data Sources - Satellite Economic Data: Real-time activity measurement - Social Media Sentiment: Public opinion incorporation - Corporate Earnings Calls: Forward-looking indicator extraction - High-Frequency Transaction Data: Market microstructure analysis ## References Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404. Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945. Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43. Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707. Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52. Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478. Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26. Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System. Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150. Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022. Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City. Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214. Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley. --- Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model. Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
Pine Script® göstergesi
EdgeTools tarafından
4
Wyckoff Entry Times @jqrmThis indicator visually marks two custom time zones on your TradingView chart by drawing vertical lines at the start and end of each zone. The first time zone spans from 9:27 AM to 9:33 AM, highlighted in red, and the second spans from 9:50 AM to 10:10 AM, highlighted in blue. You can enable or disable each zone's lines using the indicator inputs. This helps to quickly spot important intraday sessions or time ranges on your chart.
Pine Script® göstergesi
gertbit1 tarafından
ICT Macro and Daye QT ShiftEST Vertical Lines - Auto DST Adjustment Overview This indicator draws customizable vertical lines at specific Eastern Time (EST/EDT) points throughout the trading day, automatically adjusting for daylight savings time. Designed for precision trading on 1-minute and 5-minute charts, it highlights key intraday moments when price action tends to accelerate. Features - **18 pre-configured NY session times** (09:50-15:45 ET) - **Auto timezone conversion** - Always shows correct EST/EDT regardless of your local timezone - **3 line styles** - Choose between solid/dashed/dotted lines - **Clean labeling** - Optional time markers above each line - **1m/5m optimized** - Perfect for scalpers and day traders - **Visual alerts** - "TOUCH" labels when price interacts with lines Inputs | Parameter | Description | Default | |-----------|-------------|---------| | Line Times | Comma-separated HH:MM times | 09:50,10:10,...15:45 | | Line Color | Line color | Black | | Line Width | 1-5px thickness | 2 | | Line Style | Solid/Dashed/Dotted | Solid | | Show Labels | Display time markers | true | How To Use 1. Apply to 1m or 5m charts 2. Lines appear automatically at specified EST times 3. Watch for price reactions at these key levels 4. Customize styles via indicator settings Ideal For - NY open/London close traders - Earnings/News traders - Breakout traders - Market open/close strategies Updates v1.1 - Added line style customization v1.0 - Initial release
Pine Script® göstergesi
ote618 tarafından
Expected Move from RSI [SS]Publishing this experimental indicator. What it does: The indicator uses a user-defined lookback period on a user-defined timeframe to lookback at all instances of RSI. It breaks RSI down as follows: RSI between 0 - 10 10 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 100 From there, it stores the ticker's move from open to high and open to low. It will then use this data to look at the current RSI based on the specified timeframe and plot the expected move based on the average move the ticker does with a similar RSI reading. It will plot the expected range, with the high range being plotted in green and the low range being plotted in red. It will also display an infographic that dictates the current RSI based on the selected time frame, the anticipated up move and the anticipated down move. This infographic will also tell you the strength of the relationship (correlation) RSI has with the ticker's high or low price: From there the user can determine whether this RSI reading is traditionally bullish or bearish for the ticker. A greater down move indicates that the RSI traditionally elicits a bearish response. A greater up move indicates the inverse. The user can also view a chart of a breakdown of the anticipated moves based on RSI. If the option to "Show Expected Move Table" is select in the settings menu, the following table will appear: From here you can see the average up move and down move a ticker does based on its corresponding RSI reading. NOTE: When using the table, please adjust your chart timeframe to the selected timeframe on the indicator. Thus, if you are looking at the 1 hour levels, please adjust your chart to the 1 hour timeframe to use the chart. Additional Note: When using the table, an "NaN" means that there are no instances of the ticker being at that RSI level within the designated timeframe period. You can extend your lookback period to up to 500 candles to see if it finds additional instances of similar RSI. Otherwise, you can adjust the selected timeframe. Uses: The indicator can be used on all timeframes. It can help give you an idea as to whether the RSI indicates a bearish or bullish sentiment. It can signal a potential reversal or continuation. It can also help you with determining target prices for day trades and scalp trades. And that is the indicator. Its pretty straight forward. It is experimental and new, so feel free to play around with it and let me know your thoughts. Safe trades everyone and thank you for reading!
Pine Script® göstergesi
Steversteves tarafından
8
ArcTan Oscillator [LuxAlgo]The following indicator is a normalized oscillator making use of the arc tangent sigmoid function (ArcTan), this allows to "squarify" the output result, thus visually filtering out certain variations originally in the oscillator. The magnitude of this effect can be controlled by the user. The indicator contains a gradient that shows the possibility of a reversal, with red colors indicating that a reversal might occur. Settings Length : Period of the oscillator Pre-Gain : Changes the amplitude of the oscillator before passing through the ArcTan function, this allows to amplify/reduce the "squarification" effect introduced by this function. In order to make it easier for the user, the setting is in a (-10,10) range, with negative values reducing the amplitude and positive one increasing it. Src : Source input of the indicator Usage The oscillator can be used to determine the direction of the trend by looking at its sign, if the oscillator is positive, market is up-trending, else down-trending, based on this usage the user might not be interested to look at every variations produced by the oscillator, this is where the hyperbolic tangent function and pre-gain setting can be useful, by using an high value of pre-gain the user will be able to only focus on the sign of the oscillator. Here pre-gain is set to 5, we can see that the oscillator is now easier to visualize. However, the use of sigmoid functions remove useful information for a trader that needs to find divergences, this is where using a negative value of the pre-gain setting will result useful. Here pre-gain is set to -5. The indicator makes use of a gradient to show potential reversals, this gradient is determined by the correlation between the oscillator and the price (this is a way to measure potential divergences). If the color is closer to red it means that a potential reversal might occur, it is possible to say in which direction price might go by looking at the sign of the oscillator, so if the gradient is red and the oscillator is negative price might rise. The gradient is not affected by the pre-gain setting.
Pine Script® göstergesi
LuxAlgo tarafından
4
Nth Order Differencing Oscillator Perform higher order differencing through convolution, the result is equivalent to cascading N momentum oscillators of periods P : mom(mom(mom(mom(x,P)...,P) Settings length - Period of the oscillator, indicate the lag to use (equivalent to the period in a momentum oscillator) order - Differencing order, indicate how many times differencing is performed (number of times a momentum oscillator is cascaded) src - Input of the indicator Usage Differencing consists in subtracting an input to a previous input, this is what the momentum oscillator performs. This is often done in order to remove longer-term variations in the price. Differencing also induces a 90-degree phase shift for all sinusoids in a signal, this is why oscillators can have this leading effect, as such higher differencing can sometimes help have a faster and more visible lead. In red the indicator with period 50 and differencing order 2, below a momentum oscillator of the same period. It is important to note that differencing is an operation that increases noise, in fact, you might have seen some oscillators use the median price hl2 instead of the closing price, this is because the median price contains less noise than the closing price, as such more differencing require a smoother input. Here both the sma and the oscillator period are equal to 20 with a differencing order of 5. In time series analysis the order of differencing is chosen depending on the order of integration, more simply put we should choose a differencing order that responds to the question: "How many time should I differentiate my time series so that the result is stationary?", for stocks prices this differencing order should be 1. Technically speaking differencing orders higher than 3 might be overkill, as higher orders return noisier outputs that might no longer be representative of the original input. here a period of 14 with differencing order of 20 is used, we can see more periodic results but they are not really representative of the closing prices. Details Simple differencing is actually achieved thought convolution, if we take a first-order difference x - x(1) , we can see that this is equivalent to 1*x + -1*x(1) , the coefficients are 1 and -1, for the momentum oscillator the difference is that the coefficients include 0 values. So we only need a function generating the coefficients of our Nth order difference oscillator, in order to get them lets analyze the impulse response of a cascaded change function. Here 5 change function are cascaded, the coefficients are: (1,-5,10,-10,5,-1) If you look at these coefficients and the ones of higher/lower order differences we can deduce various things The impulse response is symmetric The first coefficient is always 1 and the last always -1 The number of coefficients increase with higher differencing orders The sign of the current coefficient is different from the sign of the previous one From the shape of the impulse response, we can deduce that the coefficients of an Nth order differencing operator is a windowed series of 1,-1,1...,-1 , and that's actually the case, for an Nth order differencing operator the values of this window are given by the Nth row of the Pascal triangle. There are various ways to get the values in the row of the Pascal triangle, one involving using the combination formula, however, we can do it way faster by using the recursive formula used in line number 13. Now that we have our coefficients we only need to separate them with 0 values and that's all. Conclusion We can see that oscillators are noisier than the original input signal, this is can be a desired effect in order to make lagging indicators more reactive, but it can also be overlooked due to the results appearing leading the price or just looking more predictable, however, we should note that higher-order differencing does not provide a consistent nor reliable solution toward minimizing lag, nor does classical oscillators. The indicator is not useful, but if for some reason you require a lot of differencing operations to be done and don't want to use consecutive change or mom functions, then this script might results useful to you.
Pine Script® göstergesi
alexgrover tarafından
7
Trend Lines and MoreMulti-Indicator consisting of several useful indicators in a single package. TREND LINES -By default the 20 SMA and 50 SMA are shown. -Use "MOVING AVERAGE TYPE" to select SMA, EMA, Double-EMA, Triple-EMA, or Hull. -Use "50 MA TREND COLOR" to have the 50 turn green/red for uptrend/downtrend. -Use "DAILY SOURCE ONLY" to always show daily averages regardless of timeframe. -Use "SHOW LONG MA" to also include 100, 150, and 200 moving averages. -Use "SHOW MARKERS" to show a small colored marker identifying which line is which. OTHER INDICATORS -You can show Bollinger Bands and Parabolic SAR. -You can highlight key reversal times (9:50-10:10 and 14:40-15:00). -You can show price offset markers, where was the price "n" periods ago. That last one is useful to show the level of prices which are about to "fall off" the moving average and be replaced with current price. So for example, if current price is significantly below the 200-days-ago price, you can gauge the difficulty for the 200 MA to start climbing again.
Pine Script® göstergesi
nj_guy72 tarafından
4