Periodic ChannelThis indicator try to create a channel by summing a re-scaled and readapted sinusoidal wave form to the price mean.
The length parameter control the speed of the sinusoidal wave form, this parameter is not converted to a sine wave period for allowing a better estimation, higher length's work better but feel free to try shorter periods.
The invert parameter invert the sinusoidal wave.
Each bands represent possible return points, the higher the band the higher the probability.
Inverted sin wave exemple
The performance of the indicator is subjective to the main estimation (blue line), select the parameter that best fit the blue line to the price.
Best ragards
Cari dalam skrip untuk "wave"
rem sim v0.1every alt-coin has similarity.
cause of bitcoin.
always i want to delete that similarity and read the true(?) value of each coin.
and i made some script for that, but not good enough.
this one is different.
Rem Sim (rs) removes the similarity very effectively.
it make avg WaveTrend from nxt, strat, steem, ...
and that is the similarity
and it show true(?) WaveTrend without similarity.
so if the alt-coin move like other alt-coin, the WT almost 0.
sorry my bad english.
if you dont understand my english. just look at that chart.
also you can see source code.
--------
대부분의 알트가 어느정도 비슷한 차트를 가지는데, 그 유사성을 제거하면 어떤 모양인지 궁금해서 만들었어요.
전에 만들었던 비트코인의 영향력을 제거해주는 아이디어는 실제론 별 효용이 없는데 이건 좀 쓸만해보이네요.
웨이브트렌드의 모양으로 보여줍니다.
FLD's - Future Lines of Demarcation Backtest An FLD is a line that is plotted on the same scale as the price and is in fact the
price itself displaced to the right (into the future) by (approximately) half the
wavelength of the cycle for which the FLD is plotted. There are three FLD's that can be
plotted for each cycle:
An FLD based on the median price.
An FLD based on the high price.
An FLD based on the low price.
FLD - Future Lines of Demarcation Strategy An FLD is a line that is plotted on the same scale as the price and is in fact the
price itself displaced to the right (into the future) by (approximately) half the
wavelength of the cycle for which the FLD is plotted. There are three FLD's that can be
plotted for each cycle:
An FLD based on the median price.
An FLD based on the high price.
An FLD based on the low price.
FLD's - Future Lines of Demarcation An FLD is a line that is plotted on the same scale as the price and is in fact the
price itself displaced to the right (into the future) by (approximately) half the
wavelength of the cycle for which the FLD is plotted. There are three FLD's that can be
plotted for each cycle:
An FLD based on the median price.
An FLD based on the high price.
An FLD based on the low price.
Volatility Aurora [The_lurker]█░░░░░░░░░░░░░░░░░░░ VOLATILITY AURORA ░░░░░░░░░░░░░░░░░░░░█
█░░░░░░░░░░░░░░░ Where Market Energy Meets Visual Poetry ░░░░░░░░░░░░░░░░█
📖 INTRODUCTION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
The Aurora Borealis occurs when charged particles from the sun collide with gases in Earth's atmosphere, creating mesmerizing waves of colorful light.
𝗩𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗔𝘂𝗿𝗼𝗿𝗮 applies this elegant concept to financial markets:
⚡ Price Momentum = Charged Particles
🌌 ATR Layers = Atmospheric Layers
🎨 Color Intensity = Energy Magnitude
📐 Layer Expansion = Volatility State
When momentum "collides" with volatility layers, the Aurora illuminates potential market regime changes — often before they fully manifest in price action.
🔬 THE SCIENCE BEHIND IT
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Unlike traditional volatility indicators that provide a single value, Volatility Aurora creates a 𝗺𝘂𝗹𝘁𝗶-𝗱𝗶𝗺𝗲𝗻𝘀𝗶𝗼𝗻𝗮𝗹 𝘃𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗳𝗶𝗲𝗹𝗱 using five distinct ATR layers based on Fibonacci periods:
│ Layer │ Period │ Atmospheric │ Function │
├──────────────────────┼─────────────────┼─────────────────┤
│ Layer 1 │ 5 │ Ionosphere │ Captures immediate vol shifts
│ Layer 2 │ 13 │ Mesosphere │ Medium-term vol response
│ Layer 3 │ 34 │ Stratosphere │ Intermediate vol structure
│ Layer 4 │ 55 │ Troposphere │ Foundational vol baseline
│ Layer 5 │ 89 │ Surface │ Structural, long-term vol
⚡ CORE CONCEPTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
𝟭. 𝗟𝗮𝘆𝗲𝗿 𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 & 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻
Each layer dynamically expands or contracts based on its normalized ATR value:
• 𝗘𝘅𝗽𝗮𝗻𝗱𝗶𝗻𝗴 𝗟𝗮𝘆𝗲𝗿𝘀 → Increasing volatility regime
• 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝗶𝗻𝗴 𝗟𝗮𝘆𝗲𝗿𝘀 → Decreasing volatility / Consolidation
• 𝗕𝗿𝗲𝗮𝘁𝗵𝗶𝗻𝗴 𝗘𝗳𝗳𝗲𝗰𝘁 → Natural market rhythm visualization
𝟮. 𝗛𝗮𝗿𝗺𝗼𝗻𝘆 𝗦𝗰𝗼𝗿𝗲
Measures alignment between all five layers:
• 𝗛𝗶𝗴𝗵 𝗛𝗮𝗿𝗺𝗼𝗻𝘆 (>70%) → All timeframes agree → Strong, reliable trends
• 𝗟𝗼𝘄 𝗛𝗮𝗿𝗺𝗼𝗻𝘆 (<30%) → Timeframe divergence → Choppy conditions
𝟯. 𝗘𝗻𝗲𝗿𝗴𝘆 𝗜𝗻𝘁𝗲𝗻𝘀𝗶𝘁𝘆
Quantifies how strongly momentum is "hitting" the volatility layers:
• 𝗛𝗶𝗴𝗵 𝗜𝗻𝘁𝗲𝗻𝘀𝗶𝘁𝘆 → Strong directional conviction
• 𝗟𝗼𝘄 𝗜𝗻𝘁𝗲𝗻𝘀𝗶𝘁𝘆 → Weak momentum, potential reversal
𝟰. 𝗥𝗲𝗴𝗶𝗺𝗲 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻
Based on aggregate layer states:
🟢 𝗖𝗔𝗟𝗠 → Low volatility across all layers
🟡 𝗡𝗢𝗥𝗠𝗔𝗟 → Balanced market conditions
🟠 𝗩𝗢𝗟𝗔𝗧𝗜𝗟𝗘 → Elevated activity
🔴 𝗘𝗫𝗧𝗥𝗘𝗠𝗘 → Maximum volatility state
🎨 VISUAL COMPONENTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🌈 𝗔𝘂𝗿𝗼𝗿𝗮 𝗟𝗮𝘆𝗲𝗿𝘀 (𝗚𝗿𝗮𝗱𝗶𝗲𝗻𝘁 𝗕𝗮𝗻𝗱𝘀)
• Five pairs of symmetrical bands around the price core
• Color gradient from core (bright) to outer (dim)
• Expansion reflects current volatility state
💠 𝗖𝗼𝗿𝗲 𝗟𝗶𝗻𝗲
• Central EMA-based trend line
• Color changes with momentum direction:
🟢 Cyan/Teal = Bullish
🔴 Pink/Magenta = Bearish
🟣 Purple = Neutral
💫 𝗘𝗻𝗲𝗿𝗴𝘆 𝗣𝘂𝗹𝘀𝗲 𝗟𝗶𝗻𝗲𝘀
• Diagonal flow lines showing momentum trajectory
• Thicker lines = Higher energy
• Direction indicates momentum flow
🎵 𝗛𝗮𝗿𝗺𝗼𝗻𝘆 𝗪𝗮𝘃𝗲𝘀
• Vertical dotted lines appear when harmony exceeds 70%
• Signals timeframe alignment — high-probability zones
📊 HOW TO USE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 𝗧𝗿𝗲𝗻𝗱 𝗙𝗼𝗹𝗹𝗼𝘄𝗶𝗻𝗴
• Enter when Aurora expands in your direction
• Core line color confirms bias
• High harmony = Higher confidence
💥 𝗩𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗕𝗿𝗲𝗮𝗸𝗼𝘂𝘁𝘀
• Watch for regime shift from CALM to VOLATILE
• Expanding layers signal incoming movement
• Intensity spike confirms breakout strength
↩️ 𝗠𝗲𝗮𝗻 𝗥𝗲𝘃𝗲𝗿𝘀𝗶𝗼𝗻
• EXTREME regime often precedes reversals
• Contracting layers after expansion = Potential pullback
• Low harmony during trends = Weakening momentum
🛡️ 𝗥𝗶𝘀𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁
• Use outer layers as dynamic support/resistance
• Wider Aurora = Wider stops required
• Contracting Aurora = Tighter risk parameters
⚙️ SETTINGS GUIDE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🌌 𝗔𝘂𝗿𝗼𝗿𝗮 𝗖𝗼𝗿𝗲
│ Setting │Default │ Description
│ Layer 1-5 │ Fib │ ATR periods (5,13,34,55,89)
│ Expansion Factor │ 2.5 │ Controls layer width multiplier
│ Smoothing │ 5 │ EMA smoothing for visual clarity
⚡ 𝗘𝗻𝗲𝗿𝗴𝘆 𝗙𝗶𝗲𝗹𝗱
│ Setting │ Default │ Description
│ Momentum Length │ 14 │ Period for momentum calculation
│ Energy Lookback │ 21 │ Normalization window
│ Energy Multiplier │ 1.5 │ Amplifies energy display
🎨 𝗩𝗶𝘀𝘂𝗮𝗹
│ Setting │ Default │ Description
│ Language │ EN │ Interface language (EN/AR)
│ Show Aurora │ ✓ │ Toggle layer visibility
│ Show Core Line │ ✓ │ Toggle center line
│ Show Energy Pulse │ ✓ │ Toggle flow lines
│ Show Harmony Waves │ ✓ │ Toggle alignment indicators
🔔 ALERTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚡ 𝗥𝗲𝗴𝗶𝗺𝗲 𝗦𝗵𝗶𝗳𝘁 — Volatility regime changed
🎵 𝗛𝗶𝗴𝗵 𝗛𝗮𝗿𝗺𝗼𝗻𝘆 — All layers aligned (>85%)
↕️ 𝗗𝗶𝗿𝗲𝗰𝘁𝗶𝗼𝗻 𝗖𝗵𝗮𝗻𝗴𝗲 — Momentum direction reversed
🔥 𝗜𝗻𝘁𝗲𝗻𝘀𝗶𝘁𝘆 𝗦𝗽𝗶𝗸𝗲 — Energy exceeded 80% threshold
💡 TIPS FOR BEST RESULTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1️⃣ 𝗛𝗶𝗴𝗵𝗲𝗿 𝗧𝗶𝗺𝗲𝗳𝗿𝗮𝗺𝗲𝘀 — Aurora works best on 1H+ charts
2️⃣ 𝗖𝗼𝗺𝗯𝗶𝗻𝗲 𝘄𝗶𝘁𝗵 𝗣𝗔 — Use Aurora as context, not signals
3️⃣ 𝗪𝗮𝘁𝗰𝗵 𝗛𝗮𝗿𝗺𝗼𝗻𝘆 — High harmony setups win more
4️⃣ 𝗥𝗲𝘀𝗽𝗲𝗰𝘁 𝗥𝗲𝗴𝗶𝗺𝗲 — Don't fight EXTREME volatility
5️⃣ 𝗟𝗮𝘆𝗲𝗿 𝗖𝗼𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲 — Multi-layer bounces = Strong S/R
⚠️ DISCLAIMER
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
This indicator is for educational purposes only. Past performance does not
guarantee future results. Always use proper risk management and conduct your
own analysis before making trading decisions.
█████████████████████████████████████████████████████████████
█░░░░░░░░░░░░░░░░░░░░░ شفق التقلب ░░░░░░░░░░░░░░░░░░░░░░█
█░░░░░░░░░░░░░░░ حيث تلتقي طاقة السوق بالشعور البصري ░░░░░░░░░░░░░░░░█
📖 المقدمة
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
يحدث الشفق القطبي عندما تصطدم الجسيمات المشحونة القادمة من الشمس بالغازات في الغلاف الجوي للأرض، مما يخلق موجات ساحرة من الضوء الملون.
يطبق نفس المفهوم الأنيق على الأسواق المالية
⚡ زخم السعر = الجسيمات المشحونة
🌌 طبقات ATR = طبقات الغلاف الجوي
🎨 شدة اللون = حجم الطاقة
📐 توسع الطبقات = حالة التقلب
عندما "يصطدم" الزخم بطبقات التقلب، يُضيء الشفق التغيرات المحتملة في نظام السوق — غالباً قبل أن تتجلى بالكامل في حركة السعر.
🔬 العلم وراء المؤشر
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
على عكس مؤشرات التقلب التقليدية التي تقدم قيمة واحدة، يُنشئ شفق التقلب 𝗽𝗮𝗾𝗹 𝘁𝗮𝗾𝗮𝗹𝗹𝘂𝗯 𝗺𝘂𝘁𝗮'𝗮𝗱𝗱𝗶𝗱 𝗮𝗹-𝗮𝗯'𝗮𝗱 باستخدام خمس طبقات ATR مميزة مبنية على أرقام فيبوناتشي:
│ الطبقة │ الفترة │ المعادل الجوي │ الوظيفة
│ الطبقة١ │ 5 │ الأيونوسفير │ تلتقط تحولات التقلب الفورية
│ الطبقة٢ │ 13 │ الميزوسفير │ استجابة التقلب متوسطة المدى
│ الطبقة٣ │ 34 │ الستراتوسفير │ هيكل التقلب المتوسط
│ الطبقة٤ │ 55 │ التروبوسفير │ خط الأساس للتقلب
│ الطبقة٥ │ 89 │ السطح │ التقلب الهيكلي طويل المدى
⚡ المفاهيم الأساسية
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
𝟭. توسع وانكماش الطبقات
تتوسع أو تنكمش كل طبقة ديناميكياً بناءً على قيمة ATR المعيارية:
• طبقات متوسعة ← نظام تقلب متزايد
• طبقات منكمشة ← تقلب متناقص / تجميع
• تأثير التنفس ← تصور إيقاع السوق الطبيعي
𝟮. درجة التناغم
تقيس التوافق بين جميع الطبقات الخمس:
• تناغم عالي (>٧٠٪) ← جميع الأطر متفقة ← اتجاهات قوية
• تناغم منخفض (<٣٠٪) ← تباين الأطر ← ظروف متقطعة
𝟯. شدة الطاقة
تحدد مدى قوة "اصطدام" الزخم بطبقات التقلب:
• شدة عالية ← قناعة اتجاهية قوية
• شدة منخفضة ← زخم ضعيف، احتمال انعكاس
𝟰. تصنيف النظام
بناءً على حالات الطبقات المجمعة:
🟢 هادئ ← تقلب منخفض عبر جميع الطبقات
🟡 طبيعي ← ظروف سوق متوازنة
🟠 متقلب ← نشاط مرتفع
🔴 متطرف ← حالة التقلب القصوى
🎨 المكونات البصرية
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🌈 طبقات الشفق (النطاقات المتدرجة)
• خمسة أزواج من النطاقات المتماثلة حول نواة السعر
• تدرج لوني من النواة (ساطع) إلى الخارج (خافت)
• التوسع يعكس حالة التقلب الحالية
💠 خط النواة
• خط اتجاه مركزي قائم على EMA
• يتغير اللون مع اتجاه الزخم:
🟢 سماوي = صاعد
🔴 وردي = هابط
🟣 بنفسجي = محايد
💫 خطوط نبض الطاقة
• خطوط تدفق مائلة تُظهر مسار الزخم
• خطوط أسمك = طاقة أعلى
• الاتجاه يشير إلى تدفق الزخم
🎵 موجات التناغم
• خطوط عمودية منقطة تظهر عندما يتجاوز التناغم ٧٠٪
• تشير إلى توافق الأطر الزمنية — مناطق احتمالية عالية
📊 كيفية الاستخدام
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 تتبع الاتجاه
• ادخل عندما يتوسع الشفق في اتجاهك
• لون خط النواة يؤكد التحيز
• تناغم عالي = ثقة أعلى
💥 اختراقات التقلب
• راقب تحول النظام من هادئ إلى متقلب
• الطبقات المتوسعة تشير إلى حركة قادمة
• ارتفاع الشدة يؤكد قوة الاختراق
↩️ الارتداد للمتوسط
• النظام المتطرف غالباً يسبق الانعكاسات
• طبقات منكمشة بعد التوسع = احتمال تراجع
• تناغم منخفض أثناء الاتجاهات = زخم ضعيف
🛡️ إدارة المخاطر
• استخدم الطبقات الخارجية كدعم/مقاومة ديناميكية
• شفق أوسع = وقف خسارة أوسع مطلوب
• شفق منكمش = معايير مخاطر أضيق
⚙️ دليل الإعدادات
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🌌 نواة الشفق
│ الإعداد │الافتراضي│ الوصف
│ الطبقات ١-٥ │ Fib │ فترات ATR (5,13,34,55,89)
│ معامل التوسع │ 2.5 │ يتحكم في مضاعف عرض الطبقات
│ التنعيم │ 5 │ تنعيم EMA للوضوح البصري
⚡ مجال الطاقة
│ الإعداد │الافتراضي│ الوصف
│ فترة الزخم │ 14 │ فترة حساب الزخم
│ فترة الطاقة │ 21 │ نافذة التطبيع
│ مضاعف الطاقة │ 1.5 │ يضخم عرض الطاقة
🎨 العرض البصري
│ الإعداد │الافتراضي│ الوصف
│ اللغة │ EN │ لغة الواجهة (EN/AR)
│ إظهار الشفق │ ✓ │ تبديل ظهور الطبقات
│ خط النواة │ ✓ │ تبديل الخط المركزي
│ نبض الطاقة │ ✓ │ تبديل خطوط التدفق
│ موجات التناغم │ ✓ │ تبديل مؤشرات التوافق
🔔 التنبيهات
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚡ تحول النظام — تغير نظام التقلب
🎵 تناغم عالي — جميع الطبقات متوافقة (>٨٥٪)
↕️ تغير الاتجاه — انعكس اتجاه الزخم
🔥 ارتفاع الشدة — تجاوزت الطاقة عتبة ٨٠٪
💡 نصائح للحصول على أفضل النتائج
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1️⃣ الأطر الزمنية الأعلى — الشفق يعمل بشكل أفضل على ساعة فأكثر
2️⃣ ادمج مع حركة السعر — استخدم الشفق كسياق وليس إشارات
3️⃣ راقب التناغم — إعدادات التناغم العالي تربح أكثر
4️⃣ احترم النظام — لا تحارب التقلب المتطرف
5️⃣ تقاطع الطبقات — ارتداد من طبقات متعددة = دعم/مقاومة قوية
⚠️ إخلاء المسؤولية
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
هذا المؤشر للأغراض التعليمية فقط. الأداء السابق لا يضمن النتائج المستقبلية.
استخدم دائماً إدارة مخاطر مناسبة وقم بتحليلك الخاص قبل اتخاذ قرارات التداول.
█████████████████████████████████████████████████████████████
BOS and CHoCHThe market never moves in a straight line. It moves in waves.
It makes a High, comes down a bit (Low), then breaks the previous High to make a new High.
Similarly, It makes a Low, goes up a bit (High), then breaks the previous Low to make a new Low.
BOS (Break Of Structure) - Trend Continuation
BOS means the market is continuing its current trend. If the market is in an Uptrend and breaks the old "High" -> Bullish BOS. If the market is in a Downtrend and breaks the old "Low" -> Bearish BOS.
3. CHOCH (Change Of Character) - Trend Reversal
CHOCH means the mood of the market has changed. For the first time, the trend has shifted its nature.
Bullish to Bearish CHOCH: The market was making Higher Highs, but suddenly it broke its previous "Low". Now the market can fall.
Bearish to Bullish CHOCH: The market was falling (Lower Lows), but suddenly it broke its previous "High". Now the market can rise.
BOS: Confirms the trend (Breaking the ceiling to go higher).
CHOCH: Signals a trend change (Slipping and falling below the previous floor).
QLC v8.4 – GIBAUUM BEAST + ANTI-FAKEOUTQLC v8.4 – GIBAUUM BEAST + ANTI-FAKEOUT
QLC v8.4 — Gibauum Beast Edition (Self-Adaptive Lorentzian Classification + Anti-Fakeout
The most powerful open-source Lorentzian / KNN strategy ever released on TradingView.
Key Features
• True Approximate Nearest Neighbors using Lorentzian Distance (extremely robust to outliers)
• 5 hand-picked, z-score normalized features (RSI, WaveTrend, CCI, ADX, RSI)
• Real-time self-learning engine — the indicator tracks its own past predictions and automatically adjusts Lorentzian Power and number of neighbors (k) to maximize live accuracy
• Live Win-Rate calculation (last 100 strong signals) shown on dashboard
• Super-aggressive early entries on extreme predictions (|Pred| ≥ 12)
• Smart dynamic exits with Kernel + ATR trailing
• Powerful Anti-Fakeout filter — blocks entries on massive volume spikes (stops almost all whale dumps and liquidation cascades)
• SuperTrend + low choppiness + volatility filters → only trades in strong trending regimes
• Beautiful huge arrows + “GOD MODE” label when conviction is nuclear
Performance (real-time monitored on BTC, ETH, SOL 15m–4h)
→ Average live win-rate 74–84 % after the first few hours of adaptation
→ Almost zero false breakouts thanks to the volume-spike guard
Perfect for scalping, day trading and swing trading crypto and major forex pairs.
No repainting | Bar-close confirmed | Works on all timeframes (best 15m–4h)
Enjoy the beast.
Trend TraderMost trend indicators don’t offer continuation signals or accurate bounce points, so I created this indicator that uses one of the most common trading levels (EMAs). This indicator uses the 50, 100, and 200 EMAs along with WaveTrend signals to trade trends. Buy Signals are filtered so that they only show up when the 100 EMA is above the 200. And Inverse for Sell Signals.
This indicator works well with both Stocks and Crypto. Default settings work best on 15 min, 1H, 2H, and 4H.
(Chart examples are using Heikin Ashi Candles, on Log Scale.)
*Buy and Sell Signals do not repaint.
Settings:
- Ability to show all buy and sell signals regardless of trend.
- To change the sensitivity of the buy and sell signals, change the “Average Length”
- (The lower the number the more sensitive, the higher the number the less they pop up)
- Ability to change EMA Lengths
imgur.com
CSS_LFU_v0.1Overview:
A multi-factor, market-adaptive swing strategy designed for intraday and short-term crypto trading. It synthesizes momentum, volatility, and trend signals into a unified composite score over a configurable lookback window. The strategy leverages a modular, signal-weighted approach to ensure robust entry timing while remaining compatible with human-in-the-loop validation and algorithmic execution.
Core Modules:
AJFFRSI (RSX-based Momentum): Measures smoothed price momentum with noise-reduction filters to detect crossovers relative to the QQE trailing stop.
QQE (Quantitative Qualitative Easing RSI): A modified RSI with a dynamic trailing stop that adapts to short-term volatility, identifying exhaustion and potential reversal points.
Keltner Channel Zones: Determines overextension relative to trend, providing buy/sell zones based on ATR-banded EMA.
WaveTrend Oscillator: Confirms short-term swings and market direction through smoothed oscillator cross signals.
Rolling Composite Score: Aggregates module signals over a unified lookback (e.g., 144 bars) to normalize noise and capture consistent trends.
Signal Logic:
Each module outputs a discrete score (+1 / 0 / -1).
The rolling composite score sums all module scores over the lookback period.
Long positions trigger when the rolling score meets or exceeds the long threshold.
Short positions trigger when the rolling score meets or falls below the short threshold.
Multi-dimensional signal aggregation reduces false positives from single indicators.
Rolling lookback ensures score normalization across different volatility regimes.
Highly modular: easy to adapt modules or weights to different instruments or timeframes.
Fully compatible with automated execution pipelines, including custom exchange screener bots.
Use Case:
Ideal for quant-driven altcoin or multi-asset strategies where high-frequency validation is critical and sequential module weighting enhances trend flip detection.
Fib and Slope Trend Detector [EWT] + MTF Dashboard🚀 Overview
The Momentum Structure Trend Detector is a sophisticated trend-following tool that combines Price Velocity (Slope) with Market Structure (Fibonacci) to identify high-probability trend reversals and continuations.
Unlike traditional indicators that rely heavily on lagging moving averages, this script analyzes the speed of price action in real-time. It operates on the core principle of market structure: Impulse moves are fast and steep, while corrections are slow and shallow.
🧠 The Logic: Physics Meets Market Structure
This indicator determines the trend direction by calculating the Slope (Velocity) of price swings.
ZigZag Calculation: It first identifies market swings (Highs and Lows) using a standard pivot detection algorithm.
Slope Calculation: It calculates the velocity of every completed leg using the formula: $Slope = \frac{|Price Change|}{|Time Duration|}$.
Trend Definition:
Uptrend : If the previous Up-move was fast (Impulse) and the subsequent Down-move is slower (Correction), the market is primed for an uptrend.
Downtrend : If the previous Down-move was fast (Impulse) and the subsequent Up-move is slower (Correction), the market is primed for a downtrend.
🔥 Key Features
1. Aggressive Real-Time Detection (No Lag)
Most structure indicators wait for a "Higher High" to confirm a trend, which often leads to late entries. This script uses an Aggressive Live Slope calculation:
It compares the current developing slope of the live price action against the slope of the previous completed leg.
Result: As soon as the current move becomes "steeper" (faster) than the previous correction, the trend flips immediately. This allows you to catch the "meat" of the move before a new pivot is even confirmed.
2. Fibonacci Validity Filter
Momentum alone isn't enough; we need structural integrity.
The script calculates the 78.6% Retracement level of the impulse leg.
If a correction moves deeper than this Fibonacci limit (on a closing basis), the trend structure is considered "broken" or "invalid," and the indicator switches to a Neutral state. This filters out choppy/ranging markets.
3. Multi-Timeframe (MTF) Dashboard
A customizable dashboard on the chart allows for fractal analysis. You can view the trend state (UP/DOWN/NEUTRAL) across 9 different timeframes (1m to 1M) simultaneously.
Green Row : Uptrend
Red Row : Downtrend
Gray : Neutral/Indeterminate
4. Smart Visuals
Background Colo r: Changes dynamically (Teal for Bullish, Red for Bearish, Gray for Neutral) to give you an instant read of the market state.
Slope Labels : Displays the calculated numeric slope on the chart, helping you visualize the momentum difference between impulse and corrective waves.
Invalidation Levels : Automatically plots the invalidation line (Stop Loss level) based on the market structure.
🛠️ Settings & Inputs
Strategy Settings
Pivot Deviation Length : Sensitivity of the ZigZag calculation (Default: 5). Lower numbers = more sensitive to small swings.
Max Retracement % : The Fibonacci limit for a valid correction (Default: 78.6%).
Min Bars for Live Calc : To prevent noise, the script waits for this many bars after a pivot before calculating the "Live Slope" (Default: 3).
Dashboard Settings
Show Dashboard : Toggle the table on/off.
Timeframe Toggles : Enable/Disable specific timeframes (1m, 5m, 15m, 30m, 1H, 4H, 1D, 1W, 1M) to suit your trading style.
🎯 How to Use
Wait for Background Change : When the background turns Teal, it indicates that a corrective pullback has ended and a new impulse with high velocity has begun.
Check Invalidation : Look at the plotted Stop Loss Level. If price closes below this line, the trade idea is invalid.
Confirm with Dashboard : Use the table to ensure the higher timeframes (e.g., 1H, 4H) align with your current chart's direction for higher probability setups.
Disclaimer : This tool is designed for trend analysis and educational purposes. Past performance (momentum) is not indicative of future results. Always manage your risk.
Nuh's Multi-Timeframe DashboardAll 10 indicators (EMA, RSI, ADX, RI, Squeezee, WaveTrend, Alpha Trend, SuperTrend, Stoch RSI, Vix Fix) across 7 time frames (5m, 15m, 1h, 2h, 4h, 1D, 1W) consolidated into a single table.
Cipher B Free | WaveTrend (v6)Uh.. I call this.. Mona Lisa kek. Tried creating my own version of Cipher B with Grok. Feel free to tweak to your heart's content
Ehlers Even Better Sinewave (EBSW)# EBSW: Ehlers Even Better Sinewave
## Overview and Purpose
The Ehlers Even Better Sinewave (EBSW) indicator, developed by John Ehlers, is an advanced cycle analysis tool. This implementation is based on a common interpretation that uses a cascade of filters: first, a High-Pass Filter (HPF) to detrend price data, followed by a Super Smoother Filter (SSF) to isolate the dominant cycle. The resulting filtered wave is then normalized using an Automatic Gain Control (AGC) mechanism, producing a bounded oscillator that fluctuates between approximately +1 and -1. It aims to provide a clear and responsive measure of market cycles.
## Core Concepts
* **Detrending (High-Pass Filter):** A 1-pole High-Pass Filter removes the longer-term trend component from the price data, allowing the indicator to focus on cyclical movements.
* **Cycle Smoothing (Super Smoother Filter):** Ehlers' Super Smoother Filter is applied to the detrended data to further refine the cycle component, offering effective smoothing with relatively low lag.
* **Wave Generation:** The output of the SSF is averaged over a short period (typically 3 bars) to create the primary "wave".
* **Automatic Gain Control (AGC):** The wave's amplitude is normalized by dividing it by the square root of its recent power (average of squared values). This keeps the oscillator bounded and responsive to changes in volatility.
* **Normalized Oscillator:** The final output is a single sinewave-like oscillator.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
| ----------- | ------- | --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| Source | close | Price data used for calculation. | Typically `close`, but `hlc3` or `ohlc4` can be used for a more comprehensive price representation. |
| HP Length | 40 | Lookback period for the 1-pole High-Pass Filter used for detrending. | Shorter periods make the filter more responsive to shorter cycles; longer periods focus on longer-term cycles. Adjust based on observed cycle characteristics. |
| SSF Length | 10 | Lookback period for the Super Smoother Filter used for smoothing the detrended cycle component. | Shorter periods result in a more responsive (but potentially noisier) wave; longer periods provide more smoothing. |
**Pro Tip:** The `HP Length` and `SSF Length` parameters should be tuned based on the typical cycle lengths observed in the market and the desired responsiveness of the indicator.
## Calculation and Mathematical Foundation
**Simplified explanation:**
1. Remove the trend from the price data using a 1-pole High-Pass Filter.
2. Smooth the detrended data using a Super Smoother Filter to get a clean cycle component.
3. Average the output of the Super Smoother Filter over the last 3 bars to create a "Wave".
4. Calculate the average "Power" of the Super Smoother Filter output over the last 3 bars.
5. Normalize the "Wave" by dividing it by the square root of the "Power" to get the final EBSW value.
**Technical formula (conceptual):**
1. **High-Pass Filter (HPF - 1-pole):**
`angle_hp = 2 * PI / hpLength`
`alpha1_hp = (1 - sin(angle_hp)) / cos(angle_hp)`
`HP = (0.5 * (1 + alpha1_hp) * (src - src )) + alpha1_hp * HP `
2. **Super Smoother Filter (SSF):**
`angle_ssf = sqrt(2) * PI / ssfLength`
`alpha2_ssf = exp(-angle_ssf)`
`beta_ssf = 2 * alpha2_ssf * cos(angle_ssf)`
`c2 = beta_ssf`
`c3 = -alpha2_ssf^2`
`c1 = 1 - c2 - c3`
`Filt = c1 * (HP + HP )/2 + c2*Filt + c3*Filt `
3. **Wave Generation:**
`WaveVal = (Filt + Filt + Filt ) / 3`
4. **Power & Automatic Gain Control (AGC):**
`Pwr = (Filt^2 + Filt ^2 + Filt ^2) / 3`
`EBSW_SineWave = WaveVal / sqrt(Pwr)` (with check for Pwr == 0)
> 🔍 **Technical Note:** The combination of HPF and SSF creates a form of band-pass filter. The AGC mechanism ensures the output remains scaled, typically between -1 and +1, making it behave like a normalized oscillator.
## Interpretation Details
* **Cycle Identification:** The EBSW wave shows the current phase and strength of the dominant market cycle as filtered by the indicator. Peaks suggest cycle tops, and troughs suggest cycle bottoms.
* **Trend Reversals/Momentum Shifts:** When the EBSW wave crosses the zero line, it can indicate a potential shift in the short-term cyclical momentum.
* Crossing up through zero: Potential start of a bullish cyclical phase.
* Crossing down through zero: Potential start of a bearish cyclical phase.
* **Overbought/Oversold Levels:** While normalized, traders often establish subjective or statistically derived overbought/oversold levels (e.g., +0.85 and -0.85, or other values like +0.7, +0.9).
* Reaching above the overbought level and turning down may signal a potential cyclical peak.
* Falling below the oversold level and turning up may signal a potential cyclical trough.
## Limitations and Considerations
* **Parameter Sensitivity:** The indicator's performance depends on tuning `hpLength` and `ssfLength` to prevailing market conditions.
* **Non-Stationary Markets:** In strongly trending markets with weak cyclical components, or in very choppy non-cyclical conditions, the EBSW may produce less reliable signals.
* **Lag:** All filtering introduces some lag. The Super Smoother Filter is designed to minimize this for its degree of smoothing, but lag is still present.
* **Whipsaws:** Rapid oscillations around the zero line can occur in volatile or directionless markets.
* **Requires Confirmation:** Signals from EBSW are often best confirmed with other forms of technical analysis (e.g., price action, volume, other non-correlated indicators).
## References
* Ehlers, J. F. (2002). *Rocket Science for Traders: Digital Signal Processing Applications*. John Wiley & Sons.
* Ehlers, J. F. (2013). *Cycle Analytics for Traders: Advanced Technical Trading Concepts*. John Wiley & Sons.
Hello Crypto! Modern Combo Snapshot
Unified long/short analyzer blending EMA structure, SuperTrend, WaveTrend, QQE, and volume pressure.
Background shading flags “watch” and “ready” states; optional long/short modules let you focus on one side.
Alerts fire when every checklist item aligns, while the side-panel table summarizes trend, momentum, liquidity, and overall score in real time.
Indicator → Trend Analysis
Indicator → Momentum Oscillators
Indicator → Volume Indicators
Tags:
cryptocurrency, bitcoin, altcoins, trend-following, momentum, volume, ema, supertrend, intraday, swing-trading, alerts, checklist, trading-strategy, risk-management
Modern Combo Crypto SuiteBlends long and short playbooks in one overlay with quick toggles.
Tracks EMA stacks, SuperTrend, WaveTrend, QQE, and volume to score bias.
Colors the chart background when watch/ready conditions align.
Fires alerts for imminent or fully aligned long/short setups.
Displays a live checklist table summarizing trend, momentum, and volume confidence.
Cycle VTLs – with Scaled Channels "Cycle VTLs – with Scaled Channels" for TradingView plots Valid Trend Lines (VTLs) based on Hurst's Cyclic Theory, connecting consecutive price peaks (downward VTLs) or troughs (upward VTLs) for specific cycles. It uses up to eight Simple Moving Averages (SMAs) (default lengths: 25, 50, 100, 200, 400, 800, 1600, 1600 bars) with customizable envelope bands to detect pivots and draw VTLs, enhanced by optional parallel channels scaled to envelope widths.
Key Features:
Valid Trend Lines (VTLs):
Upward VTLs: Connect consecutive cycle troughs, sloping upward.
Downward VTLs: Connect consecutive cycle peaks, sloping downward.
Hurst’s Rules:
Connects consecutive cycle peaks/troughs.
Must not cross price between points.
Downward VTLs:
No longer-cycle trough between peaks.
Invalid if slope is incorrect (upward VTL not up, downward VTL not down).
Expired VTLs: Historical VTLs (crossed by price) from up to three prior cycle waves.
SMA Cycles:
Eight customizable SMAs with envelope bands (offset × multiplier) for pivot detection.
Channels:
Optional parallel lines around VTLs, width set by channelFactor × envelope half-width.
Pivot Detection:
Fractal-based (pivotPeriod) on envelopes or price (usePriceFallback).
Customization:
Toggle cycles, VTLs, and channels.
Adjust SMA lengths, offsets, colors, line styles, and widths.
Enable centered envelopes, slope filtering, and limit stored lines (maxStoredLines).
Usage in Hurst’s Cyclic TheoryAnalysis:
VTLs identify cycle trends; upward VTLs suggest bullish momentum, downward VTLs bearish.
Price crossing below an upward VTL confirms a peak in the next longer cycle; crossing above a downward VTL confirms a trough.
Trading:
Buy: Price bounces off upward VTL or breaks above downward VTL.
Sell: Price rejects downward VTL or breaks below upward VTL.
Use channels for support/resistance, breakouts, or stop-loss/take-profit levels.
Workflow:
Add indicator on TradingView.
Enable desired cycles (e.g., 50-bar, 1600-bar), adjust pivotPeriod, channelFactor, and showOnlyCorrectSlope.
Monitor VTL crossings and channels for trade signals.
NotesOptimized for performance with line limits.
Ideal for cycle-based trend analysis across markets (stocks, forex, crypto).
Debug labels show pivot counts and VTL status.
This indicator supports Hurst’s Cyclic Theory for trend identification and trading decisions with flexible, cycle-based VTLs and channels.
Use global variable to scale to chart. best results use factors of 2 and double. try 2, 4, 8, 16...128, 256, etc until price action fits 95% in smallest cycle.
Pro Momentum Table + Trade Alerts📊 Indicator Name: Pro Momentum Table – ADX + DI + ATR + Astro Timing
🧠 Concept:
This indicator is designed for professional scalpers and intraday traders who want to capture only strong momentum waves — not noise. It combines trend strength, volatility, directional movement, momentum oscillation, vega divergence, and astrological timing into a single compact table on your chart.
⚙️ Components Explained:
Metric Description
ADX (Average Directional Index) Measures the strength of the trend. Values above 20 indicate that a meaningful move is starting.
+DI / -DI (Directional Indicators) Show whether buyers (+DI) or sellers (-DI) are dominating. Increasing +DI with ADX rising = bullish momentum. Increasing -DI with ADX rising = bearish momentum.
ATR (Average True Range) Shows volatility and expected range. Used for setting realistic stop-loss and multi-level targets (1×, 1.5×, 2×, 2.5× ATR).
Price Displays the current price level for quick reference.
CMO (Chande Momentum Oscillator) Measures short-term momentum direction and strength. Helps identify overbought/oversold conditions in trend continuation.
Vega Divergence Shows a synthetic reading of volatility pressure — "Bullish" when volatility expansion supports upward moves, "Bearish" for downward pressure, and "Neutral" otherwise.
Astro Remark Suggests ideal time windows based on planetary cycles for scalping entries. “Bullish Window” often aligns with high-probability long trades; “Bearish Window” favors shorts.
Trade Signal The core momentum condition: “Bullish Momentum” if ADX > 20 and +DI rising, “Bearish Momentum” if ADX > 20 and -DI rising, else “No Clear Momentum.”
📈 How to Use:
Wait for ADX > 20 – This confirms that the market is entering a strong momentum phase.
Check DI direction:
✅ +DI rising: Buyers gaining strength → look for long setups.
✅ -DI rising: Sellers gaining strength → look for short setups.
Use ATR to plan exits:
🎯 TP1 = Entry ± 1 × ATR
🎯 TP2 = Entry ± 1.5 × ATR
🎯 TP3 = Entry ± 2 × ATR
🎯 TP4 = Entry ± 2.5 × ATR
CMO & Vega Divergence: Confirm momentum direction and volatility expansion before committing.
Astro Remark: Align your scalping activity with the planetary support window for higher probability trades.
🪙 Pro Tips for Scalpers:
Only trade when ADX > 20 and DI is consistently rising. Ignore signals in choppy or sideways phases.
Avoid trades if Vega is neutral and CMO is flat – these usually indicate fake breakouts.
If targets aren’t hit within expected ATR-based time, treat the move as false and exit early.
Combine with 9 EMA and 20 EMA (hidden) for wave structure confirmation without cluttering the chart.
💡 Summary:
This indicator acts as a real-time trade decision dashboard. It removes clutter from the chart and delivers everything a professional scalper needs — strength, direction, volatility, momentum, timing, and actionable trade bias — all in one elegant table.
EvoTrend-X Indicator — Evolutionary Trend Learner ExperimentalEvoTrend-X Indicator — Evolutionary Trend Learner
NOTE: This is an experimental Pine Script v6 port of a Python prototype. Pine wasn’t the original research language, so there may be small quirks—your feedback and bug reports are very welcome. The model is non-repainting, MTF-safe (lookahead_off + gaps_on), and features an adaptive (fitness-based) candidate selector, confidence gating, and a volatility filter.
⸻
What it is
EvoTrend-X is adaptive trend indicator that learns which moving-average length best fits the current market. It maintains a small “population” of fast EMA candidates, rewards those that align with price momentum, and continuously selects the best performer. Signals are gated by a multi-factor Confidence score (fitness, strength vs. ATR, MTF agreement) and a volatility filter (ATR%). You get a clean Fast/Slow pair (for the currently best candidate), optional HTF filter, a fitness ribbon for transparency, and a themed info panel with a one-glance STATUS readout.
Core outputs
• Selected Fast/Slow EMAs (auto-chosen from candidates via fitness learning)
• Spread cross (Fast – Slow) → visual BUY/SELL markers + alert hooks
• Confidence % (0–100): Fitness ⊕ Distance vs. ATR ⊕ MTF agreement
• Gates: Trend regime (Kaufman ER), Volatility (ATR%), MTF filter (optional)
• Candidate Fitness Ribbon: shows which lengths the learner currently prefers
• Export plot: hidden series “EvoTrend-X Export (spread)” for downstream use
⸻
Why it’s different
• Evolutionary learning (on-chart): Each candidate EMA length gets rewarded if its slope matches price change and penalized otherwise, with a gentle decay so the model forgets stale regimes. The best fitness wins the right to define the displayed Fast/Slow pair.
• Confidence gate: Signals don’t light up unless multiple conditions concur: learned fitness, spread strength vs. volatility, and (optionally) higher-timeframe trend.
• Volatility awareness: ATR% filter blocks low-energy environments that cause death-by-a-thousand-whipsaws. Your “why no signal?” answer is always visible in the STATUS.
• Preset discipline, Custom freedom: Presets set reasonable baselines for FX, equities, and crypto; Custom exposes all knobs and honors your inputs one-to-one.
• Non-repainting rigor: All MTF calls use lookahead_off + gaps_on. Decisions use confirmed bars. No forward refs. No conditional ta.* pitfalls.
⸻
Presets (and what they do)
• FX 1H (Conservative): Medium candidates, slightly higher MinConf, modest ATR% floor. Good for macro sessions and cleaner swings.
• FX 15m (Active): Shorter candidates, looser MinConf, higher ATR% floor. Designed for intraday velocity and decisive sessions.
• Equities 1D: Longer candidates, gentler volatility floor. Suits index/large-cap trend waves.
• Crypto 1H: Mid-short candidates, higher ATR% floor for 24/7 chop, stronger MinConf to avoid noise.
• Custom: Your inputs are used directly (no override). Ideal for systematic tuning or bespoke assets.
⸻
How the learning works (at a glance)
1. Candidates: A small set of fast EMA lengths (e.g., 8/12/16/20/26/34). Slow = Fast × multiplier (default ×2.0).
2. Reward/decay: If price change and the candidate’s Fast slope agree (both up or both down), its fitness increases; otherwise decreases. A decay constant slowly forgets the distant past.
3. Selection: The candidate with highest fitness defines the displayed Fast/Slow pair.
4. Signal engine: Crosses of the spread (Fast − Slow) across zero mark potential regime shifts. A Confidence score and gates decide whether to surface them.
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Controls & what they mean
Learning / Regime
• Slow length = Fast ×: scales the Slow EMA relative to each Fast candidate. Larger multiplier = smoother regime detection, fewer whipsaws.
• ER length / threshold: Kaufman Efficiency Ratio; above threshold = “Trending” background.
• Learning step, Decay: Larger step reacts faster to new behavior; decay sets how quickly the past is forgotten.
Confidence / Volatility gate
• Min Confidence (%): Minimum score to show signals (and fire alerts). Raising it filters noise; lowering it increases frequency.
• ATR length: The ATR window for both the ATR% filter and strength normalization. Shorter = faster, but choppier.
• Min ATR% (percent): ATR as a percentage of price. If ATR% < Min ATR% → status shows BLOCK: low vola.
MTF Trend Filter
• Use HTF filter / Timeframe / Fast & Slow: HTF Fast>Slow for longs, Fast threshold; exit when spread flips or Confidence decays below your comfort zone.
2) FX index/majors, 15m (active intraday)
• Preset: FX 15m (Active).
• Gate: MinConf 60–70; Min ATR% 0.15–0.30.
• Flow: Focus on session opens (LDN/NY). The ribbon should heat up on shorter candidates before valid crosses appear—good early warning.
3) SPY / Index futures, 1D (positioning)
• Preset: Equities 1D.
• Gate: MinConf 55–65; Min ATR% 0.05–0.12.
• Flow: Use spread crosses as regime flags; add timing from price structure. For adds, wait for ER to remain trending across several bars.
4) BTCUSD, 1H (24/7)
• Preset: Crypto 1H.
• Gate: MinConf 70–80; Min ATR% 0.20–0.35.
• Flow: Crypto chops—volatility filter is your friend. When ribbon and HTF OK agree, favor continuation entries; otherwise stand down.
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Reading the Info Panel (and fixing “no signals”)
The panel is your self-diagnostic:
• HTF OK? False means the higher-timeframe EMAs disagree with your intended side.
• Regime: If “Chop”, ER < threshold. Consider raising the threshold or waiting.
• Confidence: Heat-colored; if below MinConf, the gate blocks signals.
• ATR% vs. Min ATR%: If ATR% < Min ATR%, status shows BLOCK: low vola.
• STATUS (composite):
• BLOCK: low vola → increase Min ATR% down (i.e., allow lower vol) or wait for expansion.
• BLOCK: HTF filter → disable HTF or align with the HTF tide.
• BLOCK: confidence → lower MinConf slightly or wait for stronger alignment.
• OK → you’ll see markers on valid crosses.
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Alerts
Two static alert hooks:
• BUY cross — spread crosses up and all gates (ER, Vol, MTF, Confidence) are open.
• SELL cross — mirror of the above.
Create them once from “Add Alert” → choose the condition by name.
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Exporting to other scripts
In your other Pine indicators/strategies, add an input.source and select EvoTrend-X → “EvoTrend-X Export (spread)”. Common uses:
• Build a rule: only trade when exported spread > 0 (trend filter).
• Combine with your oscillator: oscillator oversold and spread > 0 → buy bias.
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Best practices
• Let it learn: Keep Learning step moderate (0.4–0.6) and Decay close to 1.0 (e.g., 0.99–0.997) for smooth regime memory.
• Respect volatility: Tune Min ATR% by asset and timeframe. FX 1H ≈ 0.10–0.20; crypto 1H ≈ 0.20–0.35; equities 1D ≈ 0.05–0.12.
• MTF discipline: HTF filter removes lots of “almost” trades. If you prefer aggressive entries, turn it off and rely more on Confidence.
• Confidence as throttle:
• 40–60%: exploratory; expect more signals.
• 60–75%: balanced; good daily driver.
• 75–90%: selective; catch the clean stuff.
• 90–100%: only A-setups; patient mode.
• Watch the ribbon: When shorter candidates heat up before a cross, momentum is forming. If long candidates dominate, you’re in a slower trend cycle.
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Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_on.
• No forward references; decisions rely on confirmed bar data.
• EMA lengths are simple ints (no series-length errors).
• Confidence components are computed every bar (no conditional ta.* traps).
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Limitations & tips
• Chop happens: ER helps, but sideways microstructure can still flicker—use Confidence + Vol filter as brakes.
• Presets ≠ oracle: They’re sensible baselines; always tune MinConf and Min ATR% to your venue and session.
• Theme “Auto”: Pine cannot read chart theme; “Auto” defaults to a Dark-friendly palette.
⸻
Publisher’s Screenshots Checklist
1) FX swing — EURUSD 1H
• Preset: FX 1H (Conservative)
• Params: MinConf=70, ATR Len=14, Min ATR%=0.12, MTF ON (TF=4H, 20/50)
• Show: Clear BUY cross, STATUS=OK, green regime background; Fitness Ribbon visible.
2) FX intraday — GBPUSD 15m
• Preset: FX 15m (Active)
• Params: MinConf=60, ATR Len=14, Min ATR%=0.20, MTF ON (TF=60m)
• Show: SELL cross near London session open. HTF lines enabled (translucent).
• Caption: “GBPUSD 15m • Active session sell with MTF alignment.”
3) Indices — SPY 1D
• Preset: Equities 1D
• Params: MinConf=60, ATR Len=14, Min ATR%=0.08, MTF ON (TF=1W, 20/50)
• Show: Longer trend run after BUY cross; regime shading shows persistence.
• Caption: “SPY 1D • Trend run after BUY cross; weekly filter aligned.”
4) Crypto — BINANCE:BTCUSDT 1H
• Preset: Crypto 1H
• Params: MinConf=75, ATR Len=14, Min ATR%=0.25, MTF ON (TF=4H)
• Show: BUY cross + quick follow-through; Ribbon warming (reds/yellows → greens).
• Caption: “BTCUSDT 1H • Momentum break with high confidence and ribbon turning.”
Guppy MMA [Alpha Extract]A sophisticated trend-following and momentum assessment system that constructs dynamic trader and investor sentiment channels using multiple moving average groups with advanced scoring mechanisms and smoothed CCI-style visualizations for optimal market trend analysis. Utilizing enhanced dual-group methodology with threshold-based trend detection, this indicator delivers institutional-grade GMMA analysis that adapts to varying market conditions while providing high-probability entry and exit signals through crossover and extreme value detection with comprehensive visual mapping and alert integration.
🔶 Advanced Channel Construction
Implements dual-group architecture using short-term and long-term moving averages as foundation points, applying customizable MA types to reduce noise and score-based averaging for sentiment-responsive trend channels. The system creates trader channels from shorter periods and investor channels from longer periods with configurable periods for optimal market reaction zones.
// Core Channel Calculation Framework
maType = input.string("EMA", title="Moving Average Type", options= )
// Short-Term Group Construction
stMA1 = ma(close, st1, maType)
stMA2 = ma(close, st2, maType)
// Long-Term Group Construction
ltMA1 = ma(close, lt1, maType)
ltMA2 = ma(close, lt2, maType)
// Smoothing Application
smoothedavg = ma(overallAvg, 10, maType)
🔶 Volatility-Adaptive Zone Framework
Features dynamic score-based averaging that expands sentiment signals during strong trend periods and contracts during consolidation phases, preventing false signals while maintaining sensitivity to genuine momentum shifts. The dual-group averaging system optimizes zone boundaries for realistic market behavior patterns.
// Dynamic Sentiment Adjustment
shortTermAvg = (stScore1 + stScore2 + ... + stScore11) / 11
longTermAvg = (ltScore1 + ltScore2 + ... + ltScore11) / 11
// Dual-Group Zone Optimization
overallAvg = (shortTermAvg + longTermAvg) / 2
allMAAvg = (shortTermAvg * 11 + longTermAvg * 11) / 22
🔶 Step-Like Boundary Evolution
Creates threshold-based trend boundaries that update on smoothed average changes, providing visual history of evolving bullish and bearish levels with performance-optimized threshold management limited to key zones for clean chart presentation and efficient processing.
🔶 Comprehensive Signal Detection
Generates buy and sell signals through sophisticated crossover analysis, monitoring smoothed average interaction with zero-line and thresholds for high-probability entry and exit identification. The system distinguishes between trend continuation and reversal patterns with precision timing.
🔶 Enhanced Visual Architecture
Provides translucent zone fills with gradient intensity scaling, threshold-based historical boundaries, and dynamic background highlighting that activates upon trend changes. The visual system uses institutional color coding with green bullish zones and red bearish zones for intuitive market structure interpretation.
🔶 Intelligent Zone Management
Implements automatic trend relevance filtering, displaying signals only when smoothed average proximity warrants analysis attention. The system maintains optimal performance through smart averaging management and historical level tracking with configurable MA periods for various market conditions.
🔶 Multi-Dimensional Analysis Framework
Combines trend continuation analysis through threshold crossovers with momentum detection via extreme markers, providing comprehensive market structure assessment suitable for both trending and ranging market conditions with score-normalized accuracy.
🔶 Advanced Alert Integration
Features comprehensive notification system covering buy signals, sell signals, strong bull conditions, and strong bear conditions with customizable alert conditions. The system enables precise position management through real-time notifications of critical sentiment interaction events and zone boundary violations.
🔶 Performance Optimization
Utilizes efficient MA smoothing algorithms with configurable types for noise reduction while maintaining responsiveness to genuine market structure changes. The system includes automatic visual level cleanup and performance-optimized visual rendering for smooth operation across all timeframes.
This indicator delivers sophisticated GMMA-based market analysis through score-adaptive averaging calculations and intelligent group construction methodology. By combining dynamic trader and investor sentiment detection with advanced signal generation and comprehensive visual mapping, it provides institutional-grade trend analysis suitable for cryptocurrency, forex, and equity markets. The system's ability to adapt to varying market conditions while maintaining signal accuracy makes it essential for traders seeking systematic approaches to trend trading, momentum reversals, and sentiment continuation analysis with clearly defined risk parameters and comprehensive alert integration.
Swing Oracle Stock// (\_/)
// ( •.•)
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📌 Swing Oracle Stock – Professional Cycle & Trend Detection Indicator
The Swing Oracle Stock is an advanced market analysis tool designed to highlight price cycles, trend shifts, and key trading zones with precision. It combines trendline dynamics, normalized oscillators, and multi-timeframe confirmation into a single comprehensive indicator.
🔑 Key Features
NDOS (Normalized Dynamic Oscillator System):
Measures price strength relative to recent highs and lows to detect overbought, neutral, and oversold zones.
Dynamic Trendline (EMA8 or SMA231):
Flexible source selection for adapting to different trading styles (scalping vs. swing).
Multi-Timeframe H1 Confirmation:
Adds higher-timeframe validation to improve signal reliability.
Automated Buy & Sell Signals:
Triggered only on significant crossovers above/below defined levels.
Weekly Cycles (7-day M5 projection):
Tracks recurring time-based market cycles to anticipate reversal points.
Intuitive Visualization:
Colored zones (high, low, neutral) for quick market context.
Optional background and candlestick coloring for better clarity.
Multi-Timeframe Cross Table:
Automatically compares SMA50 vs. EMA200 across multiple timeframes (1m → 4h), showing clear status:
⭐️⬆️ UP = bullish trend confirmation
💀⬇️ Drop = bearish trend confirmation
📊 Built-in Statistical Tools
Normalized difference between short and long EMA.
Projected normalized mean levels plotted directly on the main chart.
Dynamic analysis of price distance from SMA50 to capture market “waves.”
🎯 Use Cases
Spot trend reversals with multi-timeframe confirmation.
Identify powerful breakout and breakdown zones.
Time entries and exits based on trend + cycle confluence.
Enhance market timing for swing trades, scalps, or long-term positions.
⚡ Swing Oracle Stock brings together cycle detection, oscillator normalization, and multi-timeframe confirmation into one streamlined indicator for traders who want a professional edge.
Divergence TridentA Combination of MACD + VFI + WaveTrend
Tradingview hates me and is making me explain this in greater detail so maybe this is enough????
cd_HTF_bias_CxOverview:
No matter our trading style or model, to increase our success rate, we must move in the direction of the trend and align with the Higher Time Frame (HTF). Trading "gurus" call this the HTF bias. While we small fish tend to swim in all directions, the smart way is to flow with the big wave and the current. This indicator is designed to help us anticipate that major wave.
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Details and Usage:
This indicator observes HTF price action across preferably seven different pairs, following specific rules. It confirms potential directional moves using CISD levels on a Medium Time Frame (MTF). In short, it forecasts the likely direction (HTF bias). The user can then search for trade opportunities aligned with this bias on a Lower Time Frame (LTF), using their preferred pair, entry model, and style.
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Timeframe Alignment:
The commonly accepted LTF/MTF/HTF combinations include:
• 1m – 15m – H4
• 3m – H1 – Daily / 3m – 30m – Daily
• 5m – H1 – Daily
• 15m – H4 – Weekly
• H1 – Daily – Monthly
• H4 – Weekly – Quarterly
Example: If you're trading with a 3m model on a 30m/3m setup, you should seek trades in the direction of the H1/Daily bias.
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How It Works:
The indicator first looks for sweeps on the selected HTF — when any of the last four candles are swept, the first condition is met.
The second step is confirmation with a CISD close on the MTF — once a candle closes above/below the CISD level, the second condition is fulfilled. This suggests the price has made its directional decision.
Example: If a previous HTF candle is swept and we receive a bearish CISD confirmation on H1, the HTF bias becomes bearish.
After this, you may switch to a more granular setup like HTF: 30m and MTF: 3m to look for trade entries aligned with the bias (e.g., 30m sweep + 3m CISD).
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How Is Bias Determined?
• HTF Sweep + MTF CISD = SC (Sweep & CISD)
• Latest Bullish SC → Bias: Bullish
• Latest Bearish SC → Bias: Bearish
• Price closes above the last Bearish SC → Bias: Strong Bullish
• Price closes below the last Bullish SC → Bias: Strong Bearish
• Strong Bullish bias + Bearish CISD (without HTF sweep) → Bias: Bullish
• Strong Bearish bias + Bullish CISD (without HTF sweep) → Bias: Bearish
• Bearish price violates SC high, but Bullish SC is untouched → Bias: Bullish
• Bullish price violates SC low, but Bearish SC is untouched → Bias: Bearish
• If neither side generates SC → Bias: No Bias
The logic is built on the idea that a price overcoming resistance is stronger, and encountering resistance is weaker. This model is based on the well-known “Daily Bias” structure, but with personal refinements.
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What’s on the Screen?
• Classic HTF zones (boxes)
• Potential MTF CISD levels
• Confirmed MTF lines
• Sweep zones when HTF sweeps occur
• Result table showing current bias status
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Usage:
• Select HTF and MTF timeframes aligned with your trading timeframe.
• Adjust color and position settings as needed.
• Enter up to seven pairs to track via the menu.
• Use the checkbox next to each pair to enable/disable them.
• If “Ignore these assets” is checked, all pairs will be disabled, and only the currently open chart pair will be tracked.
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Alerts:
You can choose alerts for Bullish, Bearish, Strong Bullish, or Strong Bearish conditions.
There are two types of alert sources:
1. From the indicator’s internal list
2. From TradingView’s watchlist
Visual example:
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How I Use It:
• For spot trades, I use HTF: Weekly and MTF: H4 and look for Bullish or Strong Bullish pairs.
• For scalping, I follow bias from HTF: Daily and MTF: H1.
Example: If the indicator shows a Bearish HTF Bias, I switch to HTF: 30m and MTF: 3m and enter trades once bearish conditions are met (timeframe alignment).
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Important Notes:
• The indicator defines CISD levels only at HTF high and low levels.
• If your chart is on a higher timeframe than your selected HTF/MTF, no data will appear.
Example: If HTF = H1 and MTF = 5m, opening a chart on H4 will result in a blank screen.
• The drawn CISD level on screen is the MTF CISD level.
• Not every alert should be traded. Always confirm with personal experience and visual validation.
• Receiving multiple Strong Bullish/Bearish alerts is intentional. (Trick 😊)
• Please share your feedback and suggestions!
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And Most Importantly:
Don't leave street animals without water and food!
Happy trading!






















