MACD, backtest 2015+ only, cut in half and doubledThis is only a slight modification to the existing "MACD Strategy" strategy plugin!
found the default MACD strategy to be lacking, although impressive for its simplicity. I added "year>2014" to the IF buy/sell conditions so it will only backtest from 2015 and beyond ** .
I also had a problem with the standard MACD trading late, per se. To that end I modified the inputs for fast/slow/signal to double. Example: my defaults are 10, 21, 10 so I put 20, 42, 20 in. This has the effect of making a 30min interval the same as 1 hour at 10,21,10. So if you want to backtest at 4hr, you would set your time interval to 2hr on the main chart. This is a handy way to make shorter time periods more useful even regardless of strategy/testing, since you can view 15min with alot less noise but a better response.
Used on BTCCNY OKcoin, with the chart set at 45 min (so really 90min in the strategy) this gave me a percent profitable of 42% and a profit factor of 1.998 on 189 trades.
Personally, I like to set the length/signals to 30,63,30. Meaning you need to triple the time, it allows for much better use of shorter time periods and the backtests are remarkably profitable. (i.e. 15min chart view = 45min on script, 30min= 1.5hr on script)
** If you want more specific time periods you need to try plugging in different bar values: replace "year" with "n" and "2014" with "5500". The bars are based on unix time I believe so you will need to play around with the number for n, with n being the numbers of bars.
在腳本中搜尋"a股近10年第二天溢价的股票"
Crypto Breadth Engine [alex975]
A normalized crypto market breadth indicator with a customizable 40 coin input panel — revealing whether rallies are broad and healthy across major coins and altcoins or led by only a few.
📊 Overview
The Crypto Breadth Engine measures the real participation strength of the crypto market by analyzing the direction of the 40 largest cryptocurrencies by market capitalization.
⚙️ How It Works
Unlike standard breadth tools that only count assets above a moving average, this indicator measures actual price direction:
+1 if a coin closes higher, –1 if lower, 0 if unchanged.
The total forms a Breadth Line, statistically normalized using standard deviation to maintain consistent readings across timeframes and volatility conditions.
🧩 Dynamic Input Mask
All 40 cryptocurrencies are fully editable via the input panel, allowing users to easily replace or customize the basket (Top 40, Layer-1s, DeFi, Meme Coins, AI Tokens, etc.) without touching the code.
This flexibility keeps the indicator aligned with the evolving crypto market.
🧭 Trend Bias
The indicator classifies market structure as Bullish, Neutral, or Bearish, based on how the Breadth Line aligns with its moving averages (10, 20, 50).
💡 Dashboard
A compact on-chart table displays in real time:
• Positive and negative coins
• Participation percentage
• Current trend bias
🔍 Interpretation
• Rising breadth → broad, healthy market expansion
• Falling breadth → narrowing participation and structural weakness
Ideal for TOTAL, TOTAL3, or custom crypto baskets on 1D,1W.
Developed by alex975 – Version 1.0 (2025).
-------------------------------------------------------------------------------------
🇮🇹 Versione Italiana
📊 Panoramica
Il Crypto Breadth Engine misura la partecipazione reale del mercato crypto, analizzando la direzione delle 40 principali criptovalute per capitalizzazione.
Non si limita a contare quante coin sono sopra una media mobile, ma calcola la variazione effettiva del prezzo:
+1 se sale, –1 se scende, 0 se invariato.
La somma genera una Breadth Line normalizzata statisticamente, garantendo letture coerenti su diversi timeframe e fasi di volatilità.
🧩 Mascherina dinamica
L’indicatore include una mascherina d’input interattiva che consente di modificare o sostituire liberamente i 40 ticker analizzati (Top 40, Layer-1, DeFi, Meme Coin, ecc.) senza intervenire nel codice.
Questo lo rende sempre aggiornato e adattabile all’evoluzione del mercato crypto.
⚙️ Funzionamento e Trend Bias
Classifica automaticamente il mercato come Bullish, Neutral o Bearish in base alla relazione tra la breadth e le medie mobili (10, 20, 50 periodi).
💡 Dashboard
Una tabella compatta mostra in tempo reale:
• Numero di coin positive e negative
• Percentuale di partecipazione
• Stato attuale del trend
🔍 Interpretazione
• Breadth in crescita → mercato ampio e trend sano
• Breadth in calo → partecipazione ridotta e concentrazione su pochi asset
Ideale per analizzare TOTAL, TOTAL3 o panieri personalizzati di crypto.
Funziona su timeframe 1D, 4H, 1W.
Sviluppato da alex975 – Versione 1.0 (2025).
Crash Stats 15m (ETH) — X% | prev RTH min(VWAP, Close)# Crash Stats 15m (ETH) — X% Drawdown Event Analyzer
A 15-minute indicator that scans up to the last 5 years to find **crash events** where the close falls by at least **X%** relative to the **lower of** the prior day’s **RTH VWAP** and **RTH close**. It then measures recovery and follow-through behavior, tags the market regime around each event, and summarizes everything in a table.
---
## What the script detects
**Crash event (trigger):**
* On a 15-minute bar, `close <= refPrice * (1 - X%)`.
* `refPrice = min(previous RTH VWAP, previous RTH close)`.
* First touch only: subsequent bars below the threshold on the same trading day are ignored.
* Extended hours (ETH) are supported; if ETH is off, the script safely infers the previous RTH reference.
**Per-event measurements**
1. **Time to “turn up”** – first close **above the event-anchored AVWAP** (AVWAP cumulated from the trigger bar onward).
2. **Time to recover the reference price** – first close ≥ `refPrice`.
3. **Time to recover Y% above the crash-day average price** – first close ≥ `crashDayVWAP * (1+Y%)`.
4. **Post-crash lowest price & timing** – the lowest low and how long after the event it occurs, within a user-defined horizon (default 10 trading days, approximated in calendar days).
5. **Intraday RTH low timing** – on the crash day’s RTH session, when did the day’s intraday low occur, and **was it on the first 15-minute bar**?
6. **First 15-minute low of the RTH day** – recorded for context.
All durations are shown as **D days H hours M minutes**.
---
## Regime tagging (A / B)
For each event the script classifies the surrounding trend using daily closes:
* Let `r6m = (prevClose – close_6mAgo) / close_6mAgo`,
`r12m = (prevClose – close_12mAgo) / close_12mAgo`.
* **A**: both `r6m > 0` and `r12m > 0` (uptrend across 6m & 12m).
* **B**: one positive, one negative, and `r6m + r12m ≥ 0` (mixed but net non-negative).
* Otherwise: **—**.
This helps separate selloffs in strong uptrends (A) from mixed regimes (B) and others.
---
## Inputs
* **X — Crash threshold (%)**: default 5.
* **Y — Recovery above crash-day average (%)**: default 5.
* **Lookback years**: default 5 (bounded by data availability).
* **Horizon for post-crash lowest (trading days)**: default 10 (approximated as calendar days).
* **RTH session**: default `09:30–16:00` (exchange timezone).
* **Show markers**: plot labels on triggers.
* **Rows to display**: last N events in the table.
---
## Table columns
* Index, **Trigger time**, **Drop %**, **Ref price**, **Regime (A/B/—)**
* **Time to turn up** (above anchored AVWAP)
* **Time to ref price**, **Time to day VWAP + Y%**
* **Window lowest price**, **Time to window low**
* **RTH first-15m low**, **RTH lowest time**, **Was RTH low on first 15m?**
* **Crash-day VWAP**
---
## How to use
1. **Set chart to 15-minute** and **enable extended hours** for equities (recommended).
2. Keep defaults (**X=5%, Y=5%**) to start; tighten to 3–4% for more frequent events on less volatile symbols.
3. For non-US symbols or futures, adjust the **RTH session** if needed.
4. Read the table (top-right) for per-event diagnostics and aggregate averages (bottom row).
---
## Notes & implementation details
* Works whether ETH is on or off. If ETH is off, the script back-fills “previous RTH” references at the next RTH open and uses the prior daily close as a fallback.
* The “turn up” definition uses **event-anchored AVWAP**, a robust, price–volume anchor widely used for post-shock mean reversion analysis.
* Events are **de-duplicated**: only one event per trading day (per target RTH cycle).
* Lookback is limited by your plan and the data vendor. The script requests deep history (`max_bars_back=50000`), but availability varies by symbol.
* Durations use minute precision and are rendered as **days–hours–minutes** for readability.
---
## Quick troubleshooting
* **No events found**: lower **X%**, enable **ETH**, or ensure sufficient history is loaded (scroll back, or briefly switch to a higher timeframe to force deeper backfill, then return to 15m).
* **RTH boundaries off**: check the **RTH session** input matches the venue.
* **Few rows in table**: increase **Rows to display**.
---
## Typical use cases
* Back-test how fast different symbols tend to stabilize after a sharp gap-down or intraday shock.
* Compare recovery behavior across regimes **A / B** for sizing and risk timing.
* Build playbooks: e.g., if the RTH low occurs on the first 15m bar X% of the time, plan entries accordingly.
---
## Changelog
* **v1.0**: Initial public release with crash detection, anchored-AVWAP reversal, reference & VWAP+Y recovery timers, regime tagging, window-low timing, RTH low timing, and first-15m low capture.
RSI مع 5 متوسطات و5 مستوياتRSI with 5 Moving Averages and 5 Levels
This indicator combines the Relative Strength Index (RSI) with five customizable moving averages and five horizontal levels to help identify momentum, overbought/oversold zones, and trend strength.
• RSI: Measures the speed and change of price movements.
• Levels (10, 20, 50, 80, 90):
• 10 & 20 → Oversold zones (potential buy areas)
• 80 & 90 → Overbought zones (potential sell areas)
• 50 → Neutral midpoint (trend balance line)
• Moving Averages (5, 8, 13, 21, 200):
Smooth the RSI line to reveal short- and long-term momentum trends.
You can choose the type (SMA, EMA, WMA), color, and line thickness.
Optional alert signals can be triggered when the RSI crosses specific levels (e.g., above 80 or below 20).
DTC Killzones ICT🕐 DTC Killzones ICT — Visualize Market Sessions Like a Pro
The DTC Killzones ICT indicator is a clean and intuitive tool designed for traders who want to analyze and visualize institutional trading sessions directly on their charts.
Inspired by ICT’s Killzone concept , this script makes it easy to identify overlapping market sessions — such as London, New York, and Asian — and track how price behaves within each zone.
💡 What It Does
This indicator automatically highlights key market sessions (Killzones) on your chart with fully customizable colors, labels, and transparency.
Each zone dynamically updates to reflect real-time highs and lows, helping you identify:
Session ranges and liquidity zones
Volatility windows and breakout areas
Institutional footprints across sessions
Whether you trade Forex, Indices, or Crypto , this script gives you visual clarity on when and where smart money is likely to move.
⚙️ Main Features
✅ Up to four customizable sessions (New York, London, Asian, and London Close)
✅ Adjustable timeframes and timezone options — sync with your exchange or custom UTC offset
✅ Dynamic high/low range tracking for each session
✅ Toggle range outlines, session labels , and transparency levels
✅ Optional daily dividers and session transition markers
✅ Works on any timeframe and any symbol
🧠 How Traders Use It
ICT-based traders can easily mark Killzones to align with setups like FVGs, liquidity grabs, or Silver Bullet entries.
Intraday traders can visualize session volatility and overlap periods for potential entries.
Swing traders can identify daily structure shifts by tracking range-to-range behavior.
🛠️ Customization
You can fully rename, recolor, or disable each session block.
Adjust the range transparency for visual comfort, and toggle session or daily dividers to fit your workflow.
Everything is designed to be clean, light, and modular — no clutter, no confusion.
⚡ Recommended Settings
For ICT-style analysis:
London Session: 02:00–05:00
New York Session: 07:00–10:00
Asian Session: 19:30–24:00
London Close Session: 10:00–12:00
These time windows are fully editable to suit your timezone or strategy.
🧩 Compatibility
Works seamlessly with TradingView’s built-in timezone tools
Compatible with all instruments and timeframes
Designed to overlay directly on your price chart
🏁 Final Notes
The DTC Killzones ICT indicator focuses purely on market session visualization — no alerts, entries, or trading signals.
It’s designed to complement your existing strategies and enhance clarity when analyzing market behavior across global sessions.
📈 Built for traders who value precision, structure, and timing.
MTC – Multi-Timeframe Trend ConfirmatorMTC – Multi-Timeframe Trend Confirmator
The Ultimate Multi-Timeframe Trend Analysis Tool
MTC v6 is a comprehensive trend confirmation indicator that analyzes market conditions across multiple timeframes simultaneously. It combines six powerful technical indicators to give you a clear, visual representation of trend strength and direction.
🎯 Key Features
Visual Trend Gauge
Real-time trend strength display for 3 customizable timeframes
Progressive bar visualization (fills from left to right)
Color-coded signals: 🟢 Green (Bullish) | 🔴 Red (Bearish) | 🟡 Yellow (Ranging)
Score range: -10 to +10 for precise trend measurement
Multi-Indicator Analysis
The indicator combines 6 proven technical tools:
EMA 200 – Long-term trend direction
SMA 50/200 – Golden/Death cross signals
RSI 14 – Momentum confirmation
MACD – Trend strength validation
ADX (>25) – Trend intensity measurement (2x weight)
Supertrend – Dynamic support/resistance (2x weight)
⚙️ Customization Options
Flexible Timeframes: Set any timeframes you prefer (default: 15M, 1H, 4H)
Adjustable Gauge Size: Small, Medium, or Large display
Toggle Indicators: Enable/disable any of the 6 technical indicators
Supertrend Settings: Customize factor and ATR period
Built-in Alerts: Get notified when trends confirm
📈 How to Use
Score Interpretation:
Score > +2 = Bullish trend
Score < -2 = Bearish trend
Score between -2 and +2 = Ranging/Neutral
Multi-Timeframe Confirmation:
Look for alignment across timeframes for strongest signals
Higher timeframes confirm the overall trend direction
Lower timeframes help with precise entry timing
Visual Background:
Green background = Confirmed uptrend (Higher + Mid TF aligned)
Red background = Confirmed downtrend (Higher + Mid TF aligned)
💡 Perfect For
Swing traders seeking trend confirmation
Day traders analyzing multiple timeframes
Position traders validating long-term trends
Anyone who wants clear, visual trend analysis
Trade with confidence. Trade with confirmation. Trade with MTC
-Natantia
Ulcer Index (UI) by CoryP1990 – Quant ToolkitThe Ulcer Index measures downside volatility, i.e. how deep and persistent drawdowns are from recent highs. Unlike standard deviation, which treats upside and downside equally, the Ulcer Index focuses purely on pain . It’s a favorite of risk-adjusted performance metrics like the Martin Ratio.
How it works
Computes the RMS (root-mean-square) of drawdowns over a look-back window.
Rising UI → drawdowns worsening (stress increasing).
Falling UI → drawdowns shrinking (recovery phase).
Red line = Ulcer Index rising.
Lime line = Ulcer Index falling.
Red background = High-risk regime (above threshold).
Green background = Low-risk regime (below threshold).
Use cases
Gauge portfolio stress levels and timing of recovery phases.
Identify “calm vs storm” periods for position sizing.
Combine with volatility or sentiment measures for regime classification.
Defaults
Length = 14
High-risk threshold = 10
Low-risk threshold = 5
Example — NVIDIA (NVDA, 1D)
During the sharp decline through 2022, the Ulcer Index repeatedly spiked above 10 while the background turned red, highlighting an extended high-stress drawdown phase. As NVDA began recovering in early 2023, the UI line switched to lime and drifted below 5, marking a transition into a low-risk regime. Throughout 2024–2025, the index stayed mostly sub-5 with brief red pulses on minor corrections, which is clear evidence that downside volatility has remained contained during the broader uptrend.
Part of the Quant Toolkit - a series of transparent, open-source indicators designed for professional-grade analytics and education. Built by CoryP1990.
Monthly Color Marker V4
## 📊 Monthly Color Marker - Historical Month Highlighting
### Overview
A unique indicator that allows rapid identification of all monthly candles from a specific month across multiple years. The indicator marks candles with different colors based on their direction (bullish/bearish), enabling quick analysis of seasonal patterns and cyclical behavior of stocks or assets.
### 🎯 Purpose
- **Identify Seasonal Patterns (Seasonality)** - Discover recurring trends in specific months
- **Quick Historical Analysis** - Visual representation of monthly performance over the years
- **Direction Recognition** - Instant understanding of whether a month tends to be bullish or bearish
- **Seasonal Trading Planning** - Build strategies based on cyclical patterns
### ⚙️ Adjustable Parameters
1. **Month to Mark (1-12)**
- Select the desired month for analysis
- 1 = January, 2 = February... 12 = December
- Default: 11 (November)
2. **Years Back (1-50)**
- Determines how many years back to scan
- Recommended: 10-25 years for statistically reliable data
- Default: 25 years
3. **Bullish Candle Color**
- Color for marking bullish candles (close > open)
- Default: Green
- Customizable to your personal color scheme
4. **Bearish Candle Color**
- Color for marking bearish candles (close < open)
- Default: Red
- Customizable to your personal color scheme
5. **Show Current Year**
- Whether to include the current month in the marking
- Useful when the month hasn't finished yet
- Default: Yes
### 📈 How to Use the Indicator
#### Step 1: Adding to Chart
1. Switch to **Monthly timeframe** - Required!
2. Add the indicator to your chart
3. Select the month you want to analyze
#### Step 2: Initial Analysis
- **Count green vs red candles** - What's the ratio?
- **Look for patterns** - Are there years where the month always rises/falls?
- **Identify outliers** - Years where behavior was different
#### Step 3: Making Decisions
- **Mostly green** → Statistically, the month tends to rise
- **Mostly red** → Statistically, the month tends to fall
- **Mixed** → No clear seasonal pattern
### 💡 Usage Examples
**Example 1: "Santa Claus Rally"**
- Select month 12 (December)
- Check if there are mostly green candles
- If yes, this confirms the well-known year-end rally effect
**Example 2: "September Effect"**
- Select month 9 (September)
- Historically, September is considered a weak month
- Do the data support this for this stock?
**Example 3: Quarterly Earnings**
- Identify which month earnings are released
- Check the historical response
- Plan entry/exit accordingly
### 🔍 Combining with Other Indicators
This indicator works excellently with:
- **Historical Monthly Levels** (the first indicator) - Identify nearby price levels
- **Volume Profile** - Check volume during those months
- **RSI/MACD** - Identify momentum strength in specific months
### ⚠️ Important Notes
1. **Must use Monthly timeframe!** The indicator won't work correctly on other timeframes
2. **Statistical Sample** - More years = more reliable analysis
3. **Not a Guarantee** - Past performance doesn't guarantee future results, use additional analysis
4. **Adjust Colors** - If hard to see, change colors in settings
### 🎨 Tips for Optimal Experience
- **Zoom Out** - See more years at a glance
- **Clean Chart** - Remove unnecessary indicators for clear analysis
- **Compare Stocks** - Check multiple stocks for the same month
- **Document Findings** - Take screenshots and save insights for future reference
### 📊 Recommended Statistics
After identifying an interesting month:
- Calculate success rate (green / total candles)
- Check average volatility
- Identify outlier years and investigate what happened
- Plan entry/exit strategy
### 🚀 Who Is This Indicator For?
✅ **Swing Traders** - Plan medium-term trades
✅ **Seasonal Investors** - Exploit cyclical patterns
✅ **Technical Analysts** - Understand historical behavior
✅ **Portfolio Managers** - Time entries and exits
---
### 📝 Summary
The Monthly Color Marker indicator is a powerful and easy-to-use tool for identifying seasonal patterns. The combination of clear visualization with flexible parameters makes it an essential tool for any trader seeking a statistical edge in the market.
**Recommendation:** Start with 25 years back, analyze 2-3 key months, and build a data-driven strategy.
---
**Version:** 4.0
**Compatibility:** Pine Script v5
**Timeframe:** Monthly only
**Author:** 954
## 📊 Monthly Color Marker - סימון חודשים היסטוריים
### תיאור כללי
אינדיקטור ייחודי המאפשר לזהות במהירות את כל הנרות החודשיים מחודש ספציפי לאורך השנים. האינדיקטור מסמן את הנרות בצבעים שונים בהתאם לכיוון התנועה (עלייה/ירידה), ומאפשר ניתוח מהיר של דפוסים עונתיים והתנהגות מחזורית של המניה או הנכס.
### 🎯 מטרת האינדיקטור
- **זיהוי דפוסים עונתיים (Seasonality)** - מציאת מגמות חוזרות בחודשים מסוימים
- **ניתוח היסטורי מהיר** - ראייה ויזואלית של ביצועי החודש לאורך השנים
- **זיהוי כיווניות** - הבנה מיידית האם החודש נוטה להיות שורי או דובי
- **תכנון מסחר עונתי** - בניית אסטרטגיות מבוססות מחזוריות
### ⚙️ פרמטרים מתכווננים
1. **חודש לסימון (1-12)**
- בחירת החודש הרצוי לניתוח
- 1 = ינואר, 2 = פברואר... 12 = דצמבר
- ברירת מחדל: 11 (נובמבר)
2. **שנים אחורה (1-50)**
- קובע כמה שנים אחורה לסרוק
- מומלץ: 10-25 שנים לקבלת תמונה סטטיסטית מהימנה
- ברירת מחדל: 25 שנים
3. **צבע נר עולה**
- צבע לסימון נרות שורים (close > open)
- ברירת מחדל: ירוק
- ניתן להתאים לסכמת הצבעים האישית
4. **צבע נר יורד**
- צבע לסימון נרות דוביים (close < open)
- ברירת מחדל: אדום
- ניתן להתאים לסכמת הצבעים האישית
5. **צבע את השנה הנוכחית**
- האם לכלול את החודש הנוכחי בסימון
- שימושי כאשר החודש טרם הסתיים
- ברירת מחדל: כן
### 📈 איך להשתמש באינדיקטור
#### שלב 1: הוספה לגרף
1. עבור לטיימפריים **חודשי (Monthly)** - חובה!
2. הוסף את האינדיקטור לגרף
3. בחר את החודש שאתה רוצה לנתח
#### שלב 2: ניתוח ראשוני
- **ספור נרות ירוקים מול אדומים** - מה היחס?
- **חפש דפוסים** - האם יש שנים שבהן החודש תמיד עולה/יורד?
- **זהה חריגים** - שנים שבהן ההתנהגות הייתה שונה
#### שלב 3: קבלת החלטות
- **רוב ירוקים** → סטטיסטית החודש נוטה לעלות
- **רוב אדומים** → סטטיסטית החודש נוטה לרדת
- **מעורב** → אין דפוס עונתי ברור
### 💡 דוגמאות שימוש
**דוגמה 1: "Santa Claus Rally"**
- בחר חודש 12 (דצמבר)
- בדוק אם יש רוב נרות ירוקים
- אם כן, זה מאשר את האפקט הידוע של עליות בסוף השנה
**דוגמה 2: "September Effect"**
- בחר חודש 9 (ספטמבר)
- היסטורית, ספטמבר נחשב לחודש חלש
- האם הנתונים תומכים בכך במניה זו?
**דוגמה 3: דיווחים רבעוניים**
- זהה בחודש אילו נפרסמים דיווחים
- בדוק את התגובה ההיסטורית
- תכנן כניסה/יציאה בהתאם
### 🔍 שילוב עם אינדיקטורים אחרים
האינדיקטור עובד מצוין בשילוב עם:
- **Historical Monthly Levels** (האינדיקטור הראשון) - זיהוי רמות מחיר קרובות
- **Volume Profile** - בדיקת ווליום באותם חודשים
- **RSI/MACD** - זיהוי כוח המומנטום בחודשים ספציפיים
### ⚠️ הערות חשובות
1. **חובה להשתמש בטיימפריים חודשי!** האינדיקטור לא יעבוד נכון בטיימפריים אחרים
2. **מדגם סטטיסטי** - ככל שיש יותר שנים, הניתוח מהימן יותר
3. **לא ערובה** - עבר לא מבטיח עתיד, השתמש בניתוח נוסף
4. **התאם צבעים** - אם קשה לראות, שנה את הצבעים בהגדרות
### 🎨 טיפים לחוויית שימוש מיטבית
- **זום אאוט** - ראה יותר שנים במבט אחד
- **נקה גרף** - הסר אינדיקטורים מיותרים לניתוח ברור
- **השווה מניות** - בדוק מספר מניות לאותו חודש
- **תעד ממצאים** - צלם מסך ושמור תובנות לעתיד
### 📊 סטטיסטיקה מומלצת
לאחר שזיהית חודש מעניין:
- חשב אחוז הצלחה (ירוקים / כל הנרות)
- בדוק תנודתיות ממוצעת
- זהה שנים חריגות ובדוק מה קרה אז
- תכנן אסטרטגיית כניסה/יציאה
### 🚀 למי מתאים האינדיקטור?
✅ **סווינג טריידרים** - תכנון עסקאות לטווח בינוני
✅ **משקיעים עונתיים** - ניצול דפוסים מחזוריים
✅ **אנליסטים טכניים** - הבנת התנהגות היסטורית
✅ **מנהלי תיקים** - תזמון כניסות ויציאות
---
### 📝 סיכום
אינדיקטור Monthly Color Marker הוא כלי חזק וקל לשימוש לזיהוי דפוסים עונתיים. השילוב של ויזואליזציה ברורה עם פרמטרים גמישים הופך אותו לכלי חיוני לכל טריידר המחפש יתרון סטטיסטי בשוק.
**המלצה:** התחל עם 25 שנים אחורה, נתח 2-3 חודשים מרכזיים, ובנה אסטרטגיה מבוססת נתונים.
---
**גרסה:** 4.0
**תאימות:** Pine Script v5
**טיימפריים:** חודשי בלבד
**מחבר:** [954
---
3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
Multi-Day SMAmade this script due to the frustration of not having the 5 day SMA added with the 10 20 and 50. I need the 5 SMA for my type of trading to determine when to sell with stocks showing exponential growth.
so heres this: Multi SMA
5 day SMA pink
10 day SMA white
20 day SMA blue
50 day SMA red
200 day SMA green
Crypto Futures Basis Tracker (Annualized)🧩 What is Basis Arbitrage
Basis arbitrage is a market-neutral trading strategy that exploits the price difference between a cryptocurrency’s spot and its futures markets.
When futures trade above spot (called contango), traders can buy spot and short futures, locking in a potential yield.
When futures trade below spot (backwardation), the reverse applies — short spot and go long futures.
The yield earned (or cost paid) by holding this position until expiry is called the basis. Expressing it as an annualized percentage allows comparison across different contract maturities.
⚙️ How the Indicator Works
This tool calculates the annualized basis for up to 10 cryptocurrency futures against a chosen spot price.
You select one spot symbol (e.g., BITSTAMP:BTCUSD) and up to 10 futures symbols (e.g., DERIBIT:BTCUSD07X2025, DERIBIT:BTCUSD14X2025, etc.).
The script automatically computes the days-to-expiry (DTE) and the annualized basis for each future.
A table displays for each contract: symbol, expiry date, DTE, last price, and annualized basis (%) — making it easy to compare the forward curve across maturities.
⚠️ Risks and Limitations
While basis arbitrage is often considered low-risk, it’s not risk-free:
Funding and financing costs can erode returns, especially when borrowing or using leverage.
Exchange or counterparty risk — if one leg of the trade fails (e.g., exchange default, margin liquidation), the hedge breaks.
Execution and timing risk — the basis can tighten or invert before both legs are opened.
Liquidity differences — thin futures may have large bid-ask spreads or slippage.
Use this indicator for analysis and monitoring, not as an automated trading signal.
Disclaimer: Please remember that past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script don't provide any financial advice.
VWMA Series (Dynamic) mtf - Dual Gradient Colored"VWMA Series (Dynamic) mtf - Dual Gradient Colored" is a multi-timeframe (MTF) Volume-Weighted Moving Average (VWMA) ribbon indicator that plots up to 60 sequential VWMAs with arithmetic progression periods (e.g., 1, 4, 7, 10…). Each VWMA line is dual-gradient colored: Base hue = Greenish (#2dd204) if close > VWMA (bullish), Magenta (#ff00c8) if close < VWMA (bearish)
Brightness gradient = fades from base → white as period increases (short → long-term)
Uses daily resolution by default (timeframe="D"), making it ideal for higher-timeframe trend filtering on lower charts.Key FeaturesFeature
Description
Dynamic Periods
Start + i × Increment → e.g., 1, 4, 7, 10… up to 60 terms
Dual Coloring
Bull/Bear + Gradient (short = vivid, long = pale)
MTF Ready
Plots daily VWMAs on any lower timeframe (1H, 15M, etc.)
No Lag on Long Sets
Predefined "best setups" eliminate repainting/lag
Transparency Control
Adjustable line opacity for clean visuals
Scalable
Up to 60 VWMAs (max iterations)
Recommended Setups (No Lag)Type
Example Sequence (Start, Inc, Iter)
Long-Term Trend
1, 3, 30 → 1, 4, 7 … 88
93, 3, 30 → 93, 96 … 180
372, 6, 30 → 372, 378 … 546
Short-Term Momentum
1, 1, 30 → 1, 2, 3 … 30
94, 2, 30 → 94, 96 … 152
1272, 5, 30 → 1272, 1277 … 1417
Key Use CasesUse Case
How to Use
1. Multi-Timeframe Trend Alignment
On 1H chart, use 1, 3, 30 daily VWMAs → price above all green lines = strong uptrend
2. Dynamic Support/Resistance
Cluster of long-term pale VWMAs = major S/R zone
3. Early Trend Change Detection
Short-term vivid lines flip from red → green before longer ones = early bullish signal
4. Ribbon Compression/Expansion
Tight bundle → consolidation; fanning out → trend acceleration
5. Mean Reversion Entries
Price far from long-term VWMA cluster + short-term reversal = pullback trade
6. Volume-Weighted Fair Value
Long-period VWMAs reflect true average price paid over weeks/months
Visual Summary
Price ↑
████ ← Short VWMA (vivid green = close > VWMA)
███
██
█
. . . fading to white
█
██
███
████ ← Long VWMA (pale = institutional average)
Green lines = price above VWMA (bullish bias)
Magenta lines = price below VWMA (bearish bias)
Gradient = shorter (left) → brighter; longer (right) → whiter
Ribbon thickness = trend strength (wide = strong, narrow = weak)
Best For Swing traders using daily trend on intraday charts
Volume-based strategies (VWMA > SMA)
Clean, colorful trend visualization without clutter
Institutional fair value anchoring via long-period VWMAs
Pro Tip:
Use Start=1, Increment=3, Iterations=30 on a 4H chart with timeframe="D" → perfect daily trend filter with zero lag and beautiful gradient flow.
Prev 1-Min Volume • 5% Max Shares (TTP-ready)💡 Overview
This tool was built to help Trade The Pool (TTP) traders comply with the new “5% per minute volume” rule — without needing to calculate anything manually.
It automatically tracks the previous 1-minute volume, calculates 5% of it, and compares that to your planned order size.
If your planned size is within the limit, it shows green ✅.
If you’re above, it flashes red 🚫.
And when liquidity spikes allow for more size, you’ll see a green glow and 🔔 alert — so you can size up confidently without breaking the rule.
⚙️ Features
✅ Auto-calculates 5% volume cap from the previous 1-min candle
✅ Displays previous volume, max allowed shares, and your planned size
✅ TTP “different volume” scaling option (e.g. 0.69 for 45M vs 65M real volume)
✅ Per-bar slice suggestion for 10s scalpers
✅ Corner selector (top-left, top-right, bottom-left, bottom-right)
✅ Visual glow and 🔔 alert when liquidity window opens
✅ Compact and real-time responsive on 10s charts
Order Blocks Zones with Signals█ OVERVIEW
“Order Blocks Zones with Signals” is a technical analysis tool that automatically identifies Order Blocks (OB) and optionally Fair Value Gaps (FVG) on the chart.
The script visualizes these zones as colored rectangles, offering full customization of style, transparency, and signal display.
It also generates entry and exit signals (Break & Exit) that can serve as confirmations in strategies based on price action and market structure.
Thanks to flexible candle size filters and rich visual options, the indicator maintains chart clarity and readability.
█ CONCEPTS
Order Blocks (OB) are key zones on the chart where significant price movements previously occurred — areas where large market participants (institutions, so-called smart money) initiated or closed positions.
An OB is the last candle that followed the prior trend before the market reversed (e.g., for a Bullish OB: the last bearish candle before a pivot low and a strong upward impulse).
The script detects these levels using local price pivots, analyzing candle direction to filter out less significant movements.
FVG (Fair Value Gaps) represent areas of imbalance between buyers and sellers — price gaps formed by a sharp impulse where full trading did not occur due to one-sided order dominance (e.g., excess buy or sell orders).
Why combine OB and FVG in one indicator?
Combining OB and FVG analysis is essential because these phenomena often occur sequentially in the institutional market cycle:
1. Order Block — institutions enter the market in the OB zone, absorbing orders and building positions.
2. Strong impulse — after smart money entry, a rapid price move creates an FVG (imbalance gap).
3. Retest — price naturally returns to these zones (OB or FVG), drawn by unfilled orders and the search for equilibrium.
Such areas strongly attract price, as they represent not only historical institutional levels but also open “holes” in the order book. Retests of OB and FVG are ideal entry opportunities with high reaction probability (rebound or breakout). The indicator combines these two interconnected elements, enabling comprehensive market structure analysis in a single tool.
Order Blocks are labeled as:
Bullish OB – demand zones, often accumulation areas before an upmove.
Bearish OB – supply zones, signaling potential impulse end or correction start.
█ FEATURES
Order Block Detection (OB Detection):
- Automatic identification of demand and supply zones based on pivots.
- OB is the last candle aligned with the prior trend, just before the market reversal — precisely identified through candle sequence analysis around the pivot.
- OB zones appear with a delay equal to Pivot Length (default 10 bars).
- Break signals trigger when a candle’s body (close) fully pierces the zone, causing the zone to disappear immediately (e.g., close < low of Bullish OB → Break Down and zone deletion).
- Minimum size filtering via OB Size Multiplier.
- Option to create OB without wicks (Include Wicks in OB): when disabled, OB zones are based solely on candle bodies (open/close), ignoring wicks (high/low).
Fair Value Gap Detection (FVG Detection):
- Optional, with enable/disable capability.
- FVG are detected without delay — immediately upon gap occurrence.
- Size filtering via Candle Size Period and FVG Size Multiplier.
Customizable Styling:
- Separate colors and border styles (Solid / Dashed / Dotted) for each zone type.
- Adjustable transparency and border thickness.
- Unified color for box, border, and signal of the same type.
Breakout and Exit Signals:
- Break Up – triggered when a candle’s close breaks above a Bearish OB, causing the zone to disappear.
- Break Down – triggered when a candle’s close breaks below a Bullish OB, causing the zone to disappear.
- Exit Up / Exit Down – temporary exit from the zone without full breakout (price leaves the zone but doesn’t close beyond it). Signal type selection: Break, Exit, or Both.
- Alerts: built-in alerts for all signal types — triggered automatically on candle close confirming breakout or exit from OB.
█ HOW TO USE
Adding to chart: import the code into Pine Editor and run the script on TradingView.
Settings configuration:
- Pivot Length: controls swing detection sensitivity and OB display delay (default 10).
- Include Wicks in OB: enabled (default) – OB includes wicks; disabled – OB uses bodies only.
- Size Filter: adjust Candle Size Period and OB/FVG Size Multiplier to filter out small zones.
- Colors & Styles: set colors, styles, and transparency for each zone type.
- Signal Type: choose which signals to display (Break, Exit, or Both).
Signal interpretation:
- OB Break Up: price closes above Bearish OB → zone disappears → potential bullish continuation.
- OB Break Down: price closes below Bullish OB → zone disappears → potential bearish continuation.
- Exit Signals: price leaves the zone temporarily without breakout — often signals impending reversal or pullback.
Tips:
- Use OB signals alongside other indicators like RSI, MACD, SMI, or trend filters.
- Order Blocks from higher timeframes (e.g., 4H, 1D) carry greater significance and reaction strength.
- Remember: FVG are detected immediately, OB with delay — a complementary approach!
█ APPLICATIONS
- Smart Money Concepts (SMC): use OB zones as dynamic support and resistance levels. In an uptrend, look for buy opportunities in bullish OBs, which price often retests before further gains. Combining with RSI, MACD, or Fibonacci levels enhances zone significance, confirming institutional demand.
- Breakout Trading: trade based on OB breakout signals. A buy signal after breaking a bearish OB may indicate a strong upward impulse, especially if supported by rising MACD or RSI above 50. Similarly for sell signals after Break Down.
- Reversal Zones: Exit signals may indicate the end of a move or correction. Safest to use in alignment with higher-timeframe trend and confirmed by another indicator (e.g., RSI divergence, Fibonacci levels).
- Confluence Analysis: combine OB and FVG for deeper market structure and equilibrium insight. When an Order Block overlaps or borders an FVG, we get confluence of two institutional phenomena — OB (smart money entry) + FVG (imbalance) — making these areas particularly strong price magnets, increasing retest and reaction probability.
█ NOTES
- FVG can be fully disabled for a cleaner chart view.
- In consolidation periods, signals may appear more frequently — always confirm with additional trend filters.
- Works on all markets and timeframes (crypto, forex, indices, stocks).
Serenity Model VIPI — by yuu_iuHere’s a concise, practical English guide for Serenity Model VIPI (Author: yuu_iu). It covers what it is, how to set it up for daily trading, how to tune it, and how we guarantee non-repainting.
Serenity Model VIPI — User Guide (Daily Close, Non‑Repainting)
Credits
- Author: yuu_iu
- Producer: yuu_iu
- Platform: TradingView (Pine Script v5)
1) What it is
Serenity Model VIPI is a multi‑module, context‑aware trading model that fuses signals from:
- Entry modules: VCP, Flow, Momentum, Mean Reversion, Breakout
- Exit/risk modules: Contrarian, Breakout Sell, Volume Delta Sell, Peak Detector, Overbought Exit, Profit‑Take
- Context/memory: Learns per Ticker/Sector/Market Regime and adjusts weights/aggression
- Learning engine: Runs short “fake trades” to learn safely before scaling real trades
It produces a weighted, context‑adjusted score and a final decision: BUY, SELL, TAKE_PROFIT, or WAIT.
2) How it works (high level)
- Each module computes a score per bar.
- A fusion layer combines module scores using accuracy and base weights, then adjusts by:
- Market regime (Bull/Bear/Sideways) and optional higher‑timeframe (HTF) bias
- Risk control neuron
- Context memory (ticker/sector/regime)
- Optional LLM mode can override marginal cases if context supports it.
- Final decision is taken at bar close only (no intrabar repaint).
3) Non‑repainting guarantee (Daily)
- Close‑only execution: All key actions use barstate.isconfirmed, so signals/entries/exits only finalize after the daily candle closes.
- No lookahead on HTF data: request.security() reads prior‑bar values (series ) for HTF close/EMA/RSI.
- Alerts at bar close: Alerts are fired once per bar close to prevent mid‑bar changes.
What this means: Once the daily bar closes, the decision and alert won’t be repainted.
4) Setup (TradingView)
- Paste the Pine v5 code into Pine Editor, click Add to chart.
- Timeframe: 1D (Daily).
- Optional: enable a date window for training/backtest
- Enable Custom Date Filter: ON
- Set Start Date / End Date
- Create alert (non‑repainting)
- Condition: AI TRADE Signal
- Options: Once Per Bar Close
- Webhook (optional): Paste your URL into “System Webhook URL (for AI events)”
- Watch the UI
- On‑chart markers: AI BUY / AI SELL / AI TAKE PROFIT
- Right‑side table: Trades, Win Rate, Avg Profit, module accuracies, memory source, HTF trend, etc.
- “AI Thoughts” label: brief reasoning and debug lines.
5) Daily trading workflow
- The model evaluates at daily close and may:
- Enter long (BUY) when buy votes + total score exceed thresholds, after context/risk checks
- Exit via trailing stop, hard stop, TAKE_PROFIT, or SELL decision
- Learning mode:
- Triggers short “fake trades” every N bars (default 3) and measures outcome after 5 bars
- Improves module accuracies and adjusts aggression once stable (min fake win% threshold)
- Memory application:
- When you change tickers, the model tries to apply Ticker or Sector memory for the current market regime to pre‑bias module weights/aggression.
6) Tuning (what to adjust and why)
Core controls
- Base Aggression Level (default 1.0): Higher = more trades and stronger decisions; start conservative on Daily (1.0–1.2).
- Learning Speed Multiplier (default 3): Faster adaptation after fake/real trades; too high can overreact.
- Min Fake Win Rate to Exit Learning (%) (default 10–20%): Raises the bar before trusting more real trades.
- Fake Trade Every N Bars (default 3): Frequency of learning attempts.
- Learning Threshold Win Rate (default 0.4): Governs when the learner should keep learning.
- Hard Stop Loss (%) (default 5–8%): Global emergency stop.
Multi‑Timeframe (MTF)
- Enable Multi‑Timeframe Confirmation: ON (recommended for Daily)
- HTF Trend Source: HOSE:VNINDEX for VN equities (or CURRENT_SYMBOL if you prefer)
- HTF Timeframe: D or 240 (for a strong bias)
- MTF Weight Adjustment: 0.2–0.4 (0.3 default is balanced)
Module toggles and base weights
- In strong uptrends: increase VCP, Momentum, Breakout (0.2–0.3 typical)
- In sideways low‑vol regimes: raise MeanRev (0.2–0.3)
- For exits/defense: Contrarian, Peak, Overbought Exit, Profit‑Take (0.1–0.2 each)
- Keep Flow on as a volume‑quality filter (≈0.2)
Memory and control
- Enable Shared Memory Across Tickers: ON to share learning
- Enable Sector‑Based Knowledge Transfer: ON to inherit sector tendencies
- Manual Reset Learning: Use sparingly to reset module accuracies if regime changes drastically
Risk management
- Hard Stop Loss (%): 5–8% typical on Daily
- Trailing Stop: ATR‑ and volatility‑adaptive; tightens faster in Bear/High‑Vol regimes
- Max hold bars: Shorter in Bear or Sideways High‑Vol to cut risk
Alerts and webhook
- Use AI TRADE Signal with Once Per Bar Close
- Webhook payload is JSON, including event type, symbol, time, win rates, equity, aggression, etc.
7) Recommended Daily preset (VN equities)
- MTF: Enable, Source: HOSE:VNINDEX, TF: D, Weight Adj: 0.3
- Aggression: 1.1
- Learning Speed: 3
- Min Fake Win Rate to Exit Learning: 15%
- Hard SL: 6%
- Base Weights:
- VCP 0.25, Momentum 0.25, Breakout 0.15, Flow 0.20
- MeanRev 0.20 (raise in sideways)
- Contrarian/Peak/Overbought/Profit‑Take: 0.10–0.20
- Leave other defaults as is, then fine‑tune by symbol/sector.
8) Reading the UI
- Table highlights: Real Trades, Win Rate, Avg Profit, Fake Actions/Win%, VCP Acc, Aggression, Equity, Score, Status (LEARNING/TRADING/REFLECTION), Last Real, Consec Loss, Best/Worst Trade, Pattern Score, Memory Source, Current Sector, AI Health, HTF Trend, Scheduler, Memory Loaded, Fake Active.
- Shapes: AI BUY (below bar), AI SELL/TAKE PROFIT (above bar)
- “AI Thoughts”: module contributions, context notes, debug lines
9) Troubleshooting
- No trades?
- Ensure timeframe is 1D and the date filter covers the chart range
- Check Scheduler Cooldown (3 bars default) and that barstate.isconfirmed (only at close)
- If MTF is ON and HTF is bearish, buy bias is reduced; relax MTF Weight Adjustment or module weights
- Too many/too few trades?
- Lower/raise Base Aggression Level
- Adjust base weights on key modules (raise entry modules to be more active; raise exit/defense modules to be more selective)
- Learning doesn’t end?
- Increase Min Fake Win Rate to Exit Learning only after it’s consistently stable; otherwise lower it or reduce Fake Trade Every N Bars
10) Important notes
- The strategy is non‑repainting at bar close by design (confirmed bars + HTF series + close‑only alerts).
- Backtest fills may differ from live fills due to slippage and broker rules; this is normal for all TradingView strategies.
- Always validate settings across multiple symbols and regimes before going live.
If you want, I can bundle this guide into a README section in your Pine code and add a small on‑chart signature (Author/Producer: yuu_iu) in the top‑right corner.
チャットGPTimport yfinance as yf
import pandas as pd
import requests
from bs4 import BeautifulSoup
# 株たんのスクリーニング結果URL（例：200日線以下）
url = "https://kabutan.jp/warning/?mode=3_1"
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
# 銘柄コードと企業名を抽出
stocks =
for link in soup.select("td a "):
code = link .split('=')
name = link.text.strip()
if code.isdigit():
stocks.append({"code": code, "name": name})
results =
for stock in stocks : # ←テスト用に10銘柄まで
ticker = f"{stock }.T"
df = yf.download(ticker, period="1y", interval="1d")
# EMA200
df = df .ewm(span=200, adjust=False).mean()
below_ema200 = df .iloc < df .iloc
# 株たんの個別ページからPER・成長率を取得
stock_url = f"https://kabutan.jp/stock/?code={stock }"
res = requests.get(stock_url)
s = BeautifulSoup(res.text, "html.parser")
try:
per = s.find(text="PER").find_next("td").text
growth = s.find(text="売上高増減率").find_next("td").text
except:
per, growth = "N/A", "N/A"
results.append({
"銘柄コード": stock ,
"企業名": stock ,
"200EMA以下": below_ema200,
"PER": per,
"売上成長率": growth
})
# 結果をCSV出力
df_result = pd.DataFrame(results)
df_result.to_csv("割安EMA200以下銘柄.csv", index=False, encoding="utf-8-sig")
print(df_result)
Vwap Daily By SamsungTitle
Daily VWAP with Historical Lookback (Logic Fix)
Description
This script calculates and plots the daily Volume-Weighted Average Price (VWAP), an essential tool for intraday traders.
What makes this indicator special is its robust plotting logic. Unlike many simple VWAP scripts that struggle to show data for previous days, this version includes a crucial fix that allows you to reliably display historical VWAP lines for as many days back as you need. This allows for more comprehensive backtesting and analysis of how price has interacted with the VWAP on previous trading days.
This is an indispensable tool for traders who use VWAP as a dynamic level of support/resistance, a benchmark for trade execution quality, or a gauge of the day's trend.
Key Features
Historical VWAP Display: Easily plot VWAP for multiple past days on your chart. Simply set the number of lookback days in the settings.
Accurate Daily Calculation: The VWAP calculation correctly resets at the beginning of each new trading session (00:00 server time).
Fully Customizable: You have full control over the appearance of the VWAP line, including its color, width, and style (Solid or Stepped).
Robust Plotting Engine: This script solves the common Pine Script issue where conditionally plotted historical lines fail to render. It works reliably on all intraday timeframes.
Built-in Debug Mode: For advanced users or those curious about the inner workings, a comprehensive debug mode can be enabled to display raw VWAP values, cumulative volume, and timeframe warnings.
How to Use
Add the "Daily VWAP with Historical Lookback" indicator to your chart.
IMPORTANT: Make sure you are on an intraday timeframe (e.g., 1H, 30M, 15M, 5M, 1M). This indicator is designed for intraday analysis and will display a warning if used on a daily or higher timeframe.
Open the indicator's settings.
In the "VWAP Settings" tab, adjust the "Lookback Days to Display" to set how many previous days of VWAP you want to see. (e.g., 0 for today only, 1 for today and yesterday, 10 for the last 10 days).
Customize the line's appearance in the "Line Style" tab.
The "Logic Fix" Explained (For Developers)
A common challenge in Pine Script is conditionally plotting data for historical bars. Many scripts attempt this by dynamically changing the plot color to na (transparent) for bars that shouldn't be displayed. This method is often unreliable and can result in the entire plot failing to render.
This script employs a more robust and standard approach: manipulating the data series itself.
The Problem: plot(vwap, color = shouldPlot ? color.red : na) can be buggy.
The Solution: plot(shouldPlot ? vwap : na, color = color.red) is reliable.
Instead of changing the color, we create a new data series (plotVwap). This series contains the vwapValue only on the bars that meet our date criteria. On all other bars, its value is na (Not a Number). The plot() function is designed to handle na values by simply "lifting the pen," creating a clean break in the line. This ensures that the VWAP is drawn only for the selected days, with 100% reliability across all historical data.
Settings Explained
Lookback Days to Display: Sets the number of past days (from the last visible bar) for which to display the VWAP.
Line Color, Width, and Style: Standard cosmetic settings for the VWAP line.
Enable Debug Mode (Master Switch): Toggles all debugging features on or off. It is enabled by default to help new users.
Display Debug: Cumulative Volume: When enabled, it shows the daily cumulative volume in a gray area on a separate pane.
Display Debug: Raw VWAP Value: When enabled, it plots the raw, unfiltered VWAP calculation for all days on the chart, helping to verify the core logic.
This script is provided for educational and informational purposes. Trading involves significant risk. Always conduct your own research and analysis before making any trading decisions.
If you find this script useful, a 'Like' is always appreciated! Happy trading
MACD HTF Hardcoded (A/B Presets) + Regimes [CHE] MACD HTF Hardcoded (A/B Presets) + Regimes — Higher-timeframe MACD emulation with acceptance-based regime filter and on-chart diagnostics
Summary
This indicator emulates a higher-timeframe MACD directly on the current chart using two hardcoded preset families and a time-bucket mapping, avoiding cross-timeframe requests. It classifies four MACD regimes and applies an acceptance filter that requires several consecutive bars before a state is considered valid. A small dead-band around zero reduces noise near the axis. An on-chart table reports the active preset, the inferred time bucket, the resolved lengths, and the current regime.
Pine version: v6
Overlay: false
Primary outputs: MACD line, Signal line, Histogram columns, zero line, regime-change alert, info table
Motivation: Why this design?
Cross-timeframe indicators often rely on external timeframe requests, which can introduce repaint paths and added latency. This design provides a deterministic alternative: it maps the current chart’s timeframe to coarse higher-timeframe buckets and uses fixed EMA lengths that approximate those views. The dead-band suppresses flip-flops around zero, and the acceptance counter reduces whipsaw by requiring sustained agreement across bars before acknowledging a regime.
What’s different vs. standard approaches?
Baseline: Classical MACD with user-selected lengths on the same timeframe, or higher-timeframe MACD via cross-timeframe requests.
Architecture differences:
Hardcoded A and B length families with a bucket map derived from the chart timeframe.
No `request.security`; all calculations occur on the current series.
Regime classification from MACD and Histogram sign, gated by an acceptance count and a small zero dead-band.
Diagnostics table for transparency.
Practical effect: The MACD behaves like a slower, higher-timeframe variant without external requests. Regimes switch less often due to the dead-band and acceptance logic, which can improve stability in choppy sessions.
How it works (technical)
The script derives a coarse bucket from the chart timeframe using `timeframe.in_seconds` and maps it to preset-specific EMA lengths. EMAs of the source build MACD and Signal; their difference is the Histogram. Signs of MACD and Histogram define four regimes: strong bull, weak bull, strong bear, and weak bear. A small, user-defined band around zero treats values near the axis as neutral. An acceptance counter checks whether the same regime persisted for a given number of consecutive bars before it is emitted as the filtered regime. A single alert condition fires when the filtered regime changes. The histogram columns change shade based on position relative to zero and whether they are rising or falling. A persistent table object shows preset, bucket tag, resolved lengths, and the filtered regime. No cross-timeframe requests are used, so repaint risk is limited to normal live-bar movement; values stabilize on close.
Parameter Guide
Source — Input series for MACD — Default: Close — Using a smoother source increases stability but adds lag.
Preset — A or B length family — Default: “3,10,16” — Switch to “12,26,9” for the classic family mapped to buckets.
Table Position — Anchor for the info table — Default: Top right — Choose a corner that avoids covering price action.
Table Size — Table text size — Default: Normal — Use small on dense charts, large for presentations.
Dark Mode — Table theme — Default: Enabled — Match your chart background for readability.
Show Table — Toggle diagnostics table — Default: Enabled — Disable for a cleaner pane.
Zero dead-band (epsilon) — Noise gate around zero — Default: Zero — Increase slightly when you see frequent flips near zero.
Acceptance bars (n) — Bars required to confirm a regime — Default: Three — Raise to reduce whipsaw; lower to react faster.
Reading & Interpretation
Histogram columns: Above zero indicates bullish pressure; below zero indicates bearish pressure. Darker shade implies the histogram increased compared with the prior bar; lighter shade implies it decreased.
MACD vs. Signal lines: The spread corresponds to histogram height.
Regimes:
Strong bull: MACD above zero and Histogram above zero.
Weak bull: MACD above zero and Histogram below zero.
Strong bear: MACD below zero and Histogram below zero.
Weak bear: MACD below zero and Histogram above zero.
Table: Inspect active preset, bucket tag, resolved lengths, and the filtered regime number with its description.
Practical Workflows & Combinations
Trend following: Use strong bull to favor long exposure and strong bear to favor short exposure. Use weak states as pullback or transition context. Combine with structure tools such as swing highs and lows or a baseline moving average for confirmation.
Exits and risk: In strong trends, consider exiting partial size on a regime downgrade to a weak state. In choppy sessions, increase the acceptance bars to reduce churn.
Multi-asset / Multi-timeframe: Works on time-based charts across liquid futures, indices, currencies, and large-cap equities. Bucket mapping helps retain a consistent feel when moving from lower to higher timeframes.
Behavior, Constraints & Performance
Repaint/confirmation: No cross-timeframe requests; values can evolve intrabar and settle on close. Alerts follow your TradingView alert timing settings.
Resources: `max_bars_back` is set to five thousand. Very large resolved lengths require sufficient history to seed EMAs; expect a warm-up period on first load or after switching symbols.
Known limits: Dead-band and acceptance can delay recognition at sharp turns. Extremely thin markets or large gaps may still cause brief regime reversals.
Sensible Defaults & Quick Tuning
Start with preset “3,10,16”, dead-band near zero, and acceptance of three bars.
Too many flips near zero: increase the dead-band slightly or raise the acceptance bars.
Too sluggish in clean trends: reduce the acceptance bars by one.
Too sensitive on fast lower timeframes: switch to the “12,26,9” preset family or raise the acceptance bars.
Want less clutter: hide the table and keep the alert.
What this indicator is—and isn’t
This is a visualization and regime layer for MACD using higher-timeframe emulation and stability gates. It is not a complete trading system and does not generate position sizing or risk management. Use it with market structure, execution rules, and protective stops.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
OPADA//@version=5
indicator("Buy/Sell Zones – TV Style", overlay=true, timeframe="", timeframe_gaps=true)
//=====================
// الإعدادات
//=====================
len = input.int(100, "Length", minval=10)
useATR = input.bool(true, "Use ATR (بدل الانحراف المعياري)")
mult = input.float(2.0, "Band Multiplier", step=0.1)
useRSI = input.bool(true, "تفعيل فلتر RSI")
rsiOB = input.int(70, "RSI Overbought", minval=50, maxval=90)
rsiOS = input.int(30, "RSI Oversold", minval=10, maxval=50)
//=====================
// القناة: أساس + انحراف
//=====================
basis = ta.linreg(close, len, 0)
off = useATR ? ta.atr(len) * mult : ta.stdev(close, len) * mult
upper = basis + off
lower = basis - off
// نطاق علوي/سفلي بعيد لعمل تعبئة المناطق
lookback = math.min(bar_index, 500)
topBand = ta.highest(high, lookback) + 50 * syminfo.mintick
bottomBand = ta.lowest(low, lookback) - 50 * syminfo.mintick
//=====================
// الرسم
//=====================
pUpper = plot(upper, "Upper", color=color.new(color.blue, 0), linewidth=1)
pLower = plot(lower, "Lower", color=color.new(color.red, 0), linewidth=1)
pBasis = plot(basis, "Basis", color=color.new(color.gray, 60), linewidth=2)
// تعبئة المناطق: فوق القناة (أزرق)، تحت القناة (أحمر)
pTop = plot(topBand, display=display.none)
pBottom = plot(bottomBand, display=display.none)
fill(pUpper, pTop, color=color.new(color.blue, 80)) // منطقة مقاومة/بيع
fill(pBottom, pLower, color=color.new(color.red, 80)) // منطقة دعم/شراء
//=====================
// خط أفقي من قمّة قريبة (يمثل مقاومة) – قريب من الخط المنقّط في الصورة
//=====================
resLen = math.round(len * 0.6)
dynRes = ta.highest(high, resLen)
plot(dynRes, "Recent Resistance", color=color.new(color.white, 0), linewidth=1)
//=====================
// إشارات BUY / SELL + فلتر RSI (اختياري)
//=====================
rsi = ta.rsi(close, 14)
touchLower = ta.crossover(close, lower) or close <= lower
touchUpper = ta.crossunder(close, upper) or close >= upper
buyOK = useRSI ? (touchLower and rsi <= rsiOS) : touchLower
sellOK = useRSI ? (touchUpper and rsi >= rsiOB) : touchUpper
plotshape(buyOK, title="BUY", location=location.belowbar, style=shape.labelup,
text="BUY", color=color.new(color.green, 0), textcolor=color.white, size=size.tiny, offset=0)
plotshape(sellOK, title="SELL", location=location.abovebar, style=shape.labeldown,
text="SELL", color=color.new(color.red, 0), textcolor=color.white, size=size.tiny, offset=0)
// تنبيهات
alertcondition(buyOK, title="BUY", message="BUY signal: price touched/closed below lower band (RSI filter may apply).")
alertcondition(sellOK, title="SELL", message="SELL signal: price touched/closed above upper band (RSI filter may apply).")
Buy/Sell Zones – TV Style//@version=5
indicator("Buy/Sell Zones – TV Style", overlay=true, timeframe="", timeframe_gaps=true)
//=====================
// الإعدادات
//=====================
len = input.int(100, "Length", minval=10)
useATR = input.bool(true, "Use ATR (بدل الانحراف المعياري)")
mult = input.float(2.0, "Band Multiplier", step=0.1)
useRSI = input.bool(true, "تفعيل فلتر RSI")
rsiOB = input.int(70, "RSI Overbought", minval=50, maxval=90)
rsiOS = input.int(30, "RSI Oversold", minval=10, maxval=50)
//=====================
// القناة: أساس + انحراف
//=====================
basis = ta.linreg(close, len, 0)
off = useATR ? ta.atr(len) * mult : ta.stdev(close, len) * mult
upper = basis + off
lower = basis - off
// نطاق علوي/سفلي بعيد لعمل تعبئة المناطق
lookback = math.min(bar_index, 500)
topBand = ta.highest(high, lookback) + 50 * syminfo.mintick
bottomBand = ta.lowest(low, lookback) - 50 * syminfo.mintick
//=====================
// الرسم
//=====================
pUpper = plot(upper, "Upper", color=color.new(color.blue, 0), linewidth=1)
pLower = plot(lower, "Lower", color=color.new(color.red, 0), linewidth=1)
pBasis = plot(basis, "Basis", color=color.new(color.gray, 60), linewidth=2)
// تعبئة المناطق: فوق القناة (أزرق)، تحت القناة (أحمر)
pTop = plot(topBand, display=display.none)
pBottom = plot(bottomBand, display=display.none)
fill(pUpper, pTop, color=color.new(color.blue, 80)) // منطقة مقاومة/بيع
fill(pBottom, pLower, color=color.new(color.red, 80)) // منطقة دعم/شراء
//=====================
// خط أفقي من قمّة قريبة (يمثل مقاومة) – قريب من الخط المنقّط في الصورة
//=====================
resLen = math.round(len * 0.6)
dynRes = ta.highest(high, resLen)
plot(dynRes, "Recent Resistance", color=color.new(color.white, 0), linewidth=1)
//=====================
// إشارات BUY / SELL + فلتر RSI (اختياري)
//=====================
rsi = ta.rsi(close, 14)
touchLower = ta.crossover(close, lower) or close <= lower
touchUpper = ta.crossunder(close, upper) or close >= upper
buyOK = useRSI ? (touchLower and rsi <= rsiOS) : touchLower
sellOK = useRSI ? (touchUpper and rsi >= rsiOB) : touchUpper
plotshape(buyOK, title="BUY", location=location.belowbar, style=shape.labelup,
text="BUY", color=color.new(color.green, 0), textcolor=color.white, size=size.tiny, offset=0)
plotshape(sellOK, title="SELL", location=location.abovebar, style=shape.labeldown,
text="SELL", color=color.new(color.red, 0), textcolor=color.white, size=size.tiny, offset=0)
// تنبيهات
alertcondition(buyOK, title="BUY", message="BUY signal: price touched/closed below lower band (RSI filter may apply).")
alertcondition(sellOK, title="SELL", message="SELL signal: price touched/closed above upper band (RSI filter may apply).")
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
Scissors&Knifes V3.1✂️ The Scissors (PAG Chop V4 Engine)
🧠 Core idea
Scissors measure market compression and breakout readiness.
They use a modified Choppiness Index that looks at the relationship between:
True Range volatility (ATR × period length)
The total high–low range over the same window.
The smaller the ratio (sum of TR vs range), the more directional and impulsive the market is.
The higher the ratio, the more “sideways” the market trades.
This version smooths the result over PAG_SMOOTHLEN bars and applies several color bands that correspond to volatility states.
🎨 Color code meaning
Range State Color Interpretation
≤ 30 Strong Red #8B0000 Momentum exhaustion on downside, sellers dominating — about to reverse or already strong down-trend.
30 – 38 Brick Red #A52A2A Fading downside pressure; often the “bleeding edge” of a bearish climax.
38 – 55 Transparent black (α≈100) Neutral chop zone — indecision, range-building.
55 – 61.8 Yellow (optional) #DAA520 Early compression pocket where volatility starts contracting; the calm before a trend.
61.8 – 70 Bright Green #556B2F Energy release phase: volatility breaking out upward.
≥ 70 Strong Green #355E3B Sustained bullish drive, often continuation leg of a trend.
🪶 Secret nuance:
The transition bands (38–45 and 45–55) are treated as fully transparent to mark “dead zones.”
When PAG Chop sits here, all label activity pauses — the system resets its cluster memory so the next colored print begins a new “cluster”, letting you clearly see where fresh directional momentum starts.
🧩 Cluster logic
Every time a colored (non-transparent) reading appears, it belongs to a “color cluster.”
Grey labels (= count 1) mark the genesis of a new cluster, and following counts 2, 3, 4 … represent the internal continuity of that trend state.
You can optionally hide the first N grey or count 2 labels to reduce clutter on the initial stabilization bars.
✂️ Label meaning
Each label shows:
Emoji ✂️
Current count (e.g. ✂️ = 3 means 3 timeframes are simultaneously firing)
Optional list of the timeframes that contribute.
So a high count (e.g. 8–10) means many lower TFs are synchronizing volatility breakout — a multiframe alignment, often just before an acceleration burst.
🔪 The Knife (Mr Blonde V4 Engine)
🧠 Core idea
Mr Blonde converts the slope of a long EMA into an angle-of-attack metric — literally the “tilt” of market momentum.
It computes the EMA gradient relative to price span and rescales it into degrees (-5 ° to +5 °).
The steeper the angle, the stronger the directional push.
🎨 Color code meaning
Angle range Color Interpretation
≥ +5 ° Transparent (Black 1) Fully over-extended up move — wait for reset.
+3.57 – +5 ° Dark Red Strong upward slope, momentum apex.
+2.14 – +3.57 ° Orange Medium upward slope, trend acceleration zone.
+0.71 – +2.14 ° Light Orange Mild upward bias, pre-momentum phase.
0 to -0.71 ° Yellow Neutral transition.
-0.71 – -2.14 ° Olive Green Soft bearish slope.
-2.14 – -3.57 ° Olive Drab Building bearish momentum.
-3.57 – -5 ° Hunter Green Strong downward angle, aggressive push.
≤ -5 ° Transparent (Black 2) Oversold/over-tilted — likely exhaustion.
🪶 Secret nuance:
Mr Blonde uses a “span normalization” factor that divides EMA slope by the dynamic range of highs and lows.
This lets it compare angles fairly across assets with different volatility profiles (e.g. BTC vs ES) — it’s one of the rare EMA-angle implementations that self-scales properly.
🗡 Label meaning
Emoji 🔪
Count = how many TFs share the same momentum angle bias.
When many TFs show the same slope polarity (e.g. knife = 8), you’re in a deep momentum cascade — a “knife trend.”
💫 Yellow knife
The yellow state marks neutrality or slope flattening.
If you enable yellow visibility (mb_show_yellow), you can see where momentum cools off — often the earliest reversal hint.
⚙️ Shared mechanics between ✂️ and 🔪
Multi-timeframe sweep
The script cycles through 1 m → 10 m by default, running both engines once per TF.
Each returning true adds +1 to the count.
So:
sc_hits = count of timeframes where PAG fires + 1
knife_hits = count of timeframes where MB fires + 1
That “+1 shift” means there’s always at least 1, letting count = 1 represent the local TF itself.
Cluster limiter
If Limit max labels per cluster is on, you cap how many total symbols (both ✂️ & 🔪, including trails) can appear within one color phase — avoiding chart spam during extended trends.
Trails
Each printed label seeds a short-lived “trail” sequence — faded copies extending N bars forward.
Trails visualize the linger effect of the last signal, useful for visually connecting bursts in momentum.
Grey or count = 1 labels can have shorter or longer trails depending on your overrides (*_trail_bars_grey).
They’re purely visual and do not affect alerting.
Alerts
Alerts fire independently of whether you hide labels — unless you enable “respect filters”.
This guarantees you never miss a structural signal even if you suppress visuals for clarity.
🌈 Interpreting Both Together
Scenario Interpretation
✂️ = low (1–2) + 🔪 rising (red/orange) Market just leaving chop, early thrust stage.
✂️ = high (≥ 5) + 🔪 green Fully aligned breakout continuation — trend in progress.
✂️ = yellow cluster + 🔪 yellow Volatility squeeze, energy buildup — next expansion near.
✂️ = green cluster → 🔪 turns red Cross-state conflict; likely transition or correction.
✂️ = grey + 🔪 grey Reset condition — both engines cooling; stand aside.
💡 Hidden edge:
Scissors signal potential, Knife measures kinetic force.
The perfect storm is when ✂️ goes from yellow→green one bar before 🔪 shifts from orange→green — it catches the birth of directional flow while volatility is still tight.
🧭 Reading the labels intuitively
Grey ✂️/🔪 = 1 → embryonic state, may fizzle or bloom.
✂️/🔪 = 2 or 3 → expansion taking hold.
✂️/🔪 ≥ 4 (mid black) → strong synchronized drive across TFs.
Transparent gap → cluster reset; prepare for new phase.
Trail lines → echo of previous cluster strength.
Final secret tip 🗝
Because both engines are mathematically uncorrelated (volatility vs EMA angle), when they agree in color polarity on multiple TFs, you have one of the cleanest probabilistic trend windows possible.
If you ever see ✂️ = 6 + 🔪 = 6 both pointing the same way — that’s a “knife-through-the-scissors” moment: volatility expansion and directional slope synchronized — those are the bars where institutional algorithms tend to add size.
Liquidity Grab + RSI Divergence═══════════════════════════════════════════════════════════════
LIQUIDITY GRAB + RSI DIVERGENCE INDICATOR
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📌 OVERVIEW
This indicator identifies high-probability reversals by combining:
• Liquidity sweeps (stop hunts)
• RSI divergence confirmation
• Filters false breakouts automatically
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🟢 BUY SIGNAL (Green Triangle Up)
REQUIRES BOTH CONDITIONS:
1. Liquidity Grab Below Previous Low
• Price breaks BELOW recent low
• Candle CLOSES ABOVE that low
• Traps sellers who shorted the breakdown
2. Bullish RSI Divergence
• Price: Lower Low (LL)
• RSI: Higher Low (HL)
• Shows weakening downward momentum
➜ Result: Potential bullish reversal
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🔴 SELL SIGNAL (Red Triangle Down)
REQUIRES BOTH CONDITIONS:
1. Liquidity Grab Above Previous High
• Price breaks ABOVE recent high
• Candle CLOSES BELOW that high
• Traps buyers who bought the breakout
2. Bearish RSI Divergence
• Price: Higher High (HH)
• RSI: Lower High (LH)
• Shows weakening upward momentum
➜ Result: Potential bearish reversal
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📊 VISUAL INDICATORS
Main Signals:
🔺 Large Green Triangle = BUY (Liq Grab + Bullish Div)
🔻 Large Red Triangle = SELL (Liq Grab + Bearish Div)
Reference Levels:
━ Red Line = Previous High Level
━ Green Line = Previous Low Level
Additional Markers (Optional):
○ Small Green Circle = Liquidity grab low only
○ Small Red Circle = Liquidity grab high only
✕ Small Blue Cross = Bullish divergence only
✕ Small Orange Cross = Bearish divergence only
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⚙️ SETTINGS
1. Lookback Period (Default: 20)
• Range: 5-100
• Sets how far back to identify previous highs/lows
• Higher = fewer but stronger levels
• Lower = more frequent but weaker levels
2. RSI Length (Default: 14)
• Range: 5-50
• Standard RSI calculation period
• 14 is industry standard
3. RSI Divergence Lookback (Default: 5)
• Range: 3-20
• Controls pivot point sensitivity
• Higher = fewer divergence signals
• Lower = more divergence signals
4. Show Labels (Default: ON)
• Toggle BUY/SELL text labels
• Disable for cleaner chart view
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💡 HOW TO USE
Step 1: WAIT FOR CONFIRMATION
• Only trade LARGE TRIANGLE signals
• Ignore small circles/crosses alone
Step 2: CHECK TIMEFRAME
• Best on: 15min, 1H, 4H, Daily
• Avoid: 1min, 5min (too noisy)
Step 3: CONFIRM CONTEXT
• Check overall market trend
• Identify key support/resistance
• Look for confluence with price action
Step 4: ENTRY & RISK MANAGEMENT
• Enter on signal candle close or pullback
• Stop loss below/above the liquidity grab wick
• Target: Previous swing high/low or key levels
• Risk/Reward: Minimum 1:2 ratio
Step 5: SET ALERTS
• Create alert for "BUY Signal"
• Create alert for "SELL Signal"
• Never miss opportunities
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✅ BEST PRACTICES
DO:
✓ Use on multiple timeframes for confluence
✓ Combine with support/resistance zones
✓ Wait for both conditions (liq grab + divergence)
✓ Practice on demo account first
✓ Use proper position sizing
DON'T:
✗ Trade every small circle/cross
✗ Use on very low timeframes (<15min)
✗ Ignore overall market context
✗ Trade without stop loss
✗ Risk more than 1-2% per trade
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⚠️ IMPORTANT NOTES
• This is a CONFIRMATION tool, not a holy grail
• No indicator is 100% accurate
• Combine with your trading strategy
• Backtest on your preferred instruments
• Adjust parameters for your trading style
• Higher timeframes = more reliable signals
• Always use risk management
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🔔 ALERTS INCLUDED
Two alert conditions are built-in:
1. "BUY Signal" - Liquidity Grab + Bullish RSI Divergence
2. "SELL Signal" - Liquidity Grab + Bearish RSI Divergence
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📈 RECOMMENDED SETTINGS BY TIMEFRAME
5-15 Min Charts:
• Lookback: 10-15
• RSI Length: 14
• RSI Div Lookback: 3-5
1H-4H Charts:
• Lookback: 20-30
• RSI Length: 14
• RSI Div Lookback: 5-7
Daily Charts:
• Lookback: 30-50
• RSI Length: 14
• RSI Div Lookback: 7-10
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Good luck and trade safe! 🚀
