BANKNIFTY Contribution Table [GSK-VIZAG-AP-INDIA]1. Overview
This indicator provides a real-time visual contribution table of the 12 constituent stocks in the BANKNIFTY index. It displays key metrics for each stock that help traders quickly understand how each component is impacting the index at any given moment.
2. Purpose / Trading Use Case
The tool is designed for intraday and short-term traders who rely on index movement and its internal strength or weakness. By seeing which stocks are contributing positively or negatively, traders can:
Confirm trend strength or divergence within the index.
Identify whether a BANKNIFTY move is broad-based or driven by a few heavyweights.
Detect reversals when individual components decouple from index direction.
3. Key Features and Logic
Live LTP: Current price of each BANKNIFTY stock.
Price Change: Difference between current LTP and previous day’s close.
% Change: Percentage move from previous close.
Weight %: Static weight of each stock within the BANKNIFTY index (user-defined).
This estimates how much each stock contributes to the BANKNIFTY’s point change.
Sorted View: The stocks are sorted by their weight (descending), so high-impact movers are always at the top.
4. User Inputs / Settings
Table Position (tableLocationOpt):
Choose where the table appears on the chart:
top_left, top_right, bottom_left, or bottom_right.
This helps position the table away from your price action or indicators.
5. Visual and Plotting Elements
Table Layout: 6 columns
Stock | Contribution | Weight % | LTP | Change | % Change
Color Coding:
Green/red for positive/negative price changes and contributions.
Alternating background rows for better visibility.
BANKNIFTY row is highlighted separately at the top.
Text & Background Colors are chosen for both readability and direction indication.
6. Tips for Effective Use
Use this table on 1-minute or 5-minute intraday charts to see near real-time market structure.
Watch for:
A few heavyweight stocks pulling the index alone (can signal weak internal breadth).
Broad green/red across all rows (signals strong directional momentum).
Combine this with price action or volume-based strategies for confirmation.
Best used during market hours for live updates.
7. What Makes It Unique
Unlike other contribution tables that show only static data or require paid feeds, this script:
Updates in real time.
Uses dynamic calculated contributions.
Places BANKNIFTY at the top and presents the entire internal structure clearly.
Doesn’t repaint or rely on lagging indicators.
8. Alerts / Additional Features
No alerts are added in this version.
(Optional: Alerts can be added to notify when a certain stock contributes above/below a threshold.)
9. Technical Concepts Used
request.security() to pull both 1-minute and daily close data.
Conditional color formatting based on price change direction.
Dynamic table rendering using table.new() and table.cell().
Static weights assigned manually for BANKNIFTY stocks (can be updated if index weights change).
10. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a buy/sell recommendation.
Users should test and validate the tool on paper or demo accounts before applying it to live trading.
📌 Note: Due to internet connectivity, data delays, or broker feeds, real-time values (LTP, change, contribution, etc.) may slightly differ from other platforms or terminals. Use this indicator as a supportive visual tool, not a sole decision-maker.
Script Title: BANKNIFTY Contribution Table -
Author: GSK-VIZAG-AP-INDIA
Version: Final Public Release
Indicatori e strategie
Bearish Fibonacci Extension Distance Table
### 📉 **Bearish Fibonacci Extension Distance Table – Pine Script Indicator**
This TradingView indicator calculates and displays **bearish Fibonacci extension targets** based on recent price swings, specifically designed for traders looking to **analyze downside potential** in a trending market. Unlike traditional Fibonacci retracement tools that help identify pullbacks, this version projects likely **price targets below current levels** using Fibonacci ratios commonly followed by institutional and retail traders alike.
#### 🔧 **How It Works:**
* **Swing Calculation**:
The script looks back over a user-defined period (`swingLen`, default 20 bars) to find:
* `B`: The **highest high** in the lookback (start of bearish move)
* `A`: The **lowest low** in the same period (end of bearish swing)
* `C`: The **current high**, serving as the base for projecting future downside levels.
* **Bearish Extensions**:
It then calculates Fibonacci extension levels **below** the current high using standard ratios:
* **100%**, **127.2%**, **161.8%**, **200%**, and **261.8%**
* **Distance Calculation**:
For each level, the indicator computes:
* The **target price**
* The **distance (in %)** between the current close and each Fibonacci level
* **Visual Output**:
A live, auto-updating **data table** is shown in the **top-right corner** of the chart. This provides at-a-glance insight into how far current price is from each bearish target, with color-coded levels for clarity.
#### 📊 **Use Cases**:
* Identify **bearish continuation targets** in downtrending or correcting markets.
* Help manage **take-profit** zones for short trades.
* Assess **risk-reward** scenarios when entering bearish positions.
* Combine with indicators like RSI, OBV, or MACD for **confluence-based setups**.
#### ⚙️ **Inputs**:
* `Swing Lookback`: Number of bars to consider for calculating the swing high and swing low.
* `Show Table`: Toggle to display or hide the Fibonacci level table.
---
### 🧠 Example Interpretation:
Suppose the stock is trading at ₹180 and the 161.8% Fibonacci extension level is ₹165 with a -8.3% distance — this suggests the price may continue down to ₹165, offering a potential 8% short opportunity if confirmed by other indicators.
[TH] กลยุทธ์ SMC หลายกรอบเวลา (V5.2 - M15 Lead)English Explanation
This Pine Script code implements a multi-timeframe trading strategy based on Smart Money Concepts (SMC). It's designed to identify high-probability trading setups by aligning signals across three different timeframes.
The core logic is as follows:
High Timeframe (HTF) - M15: Determines the overall market direction or bias.
Medium Timeframe (MTF) - M5: Identifies potential Points of Interest (POI), such as Order Blocks or Fair Value Gaps, in alignment with the M15 bias.
Low Timeframe (LTF) - Current Chart: Looks for a specific entry trigger within the M5 POI to execute the trade.
Detailed Breakdown
## Part 1: Inputs & Settings
This section allows you to customize the indicator's parameters:
General Settings:
i_pivotLookback: Sets the lookback period for identifying pivot highs and lows on the LTF, which is crucial for finding the Change of Character (CHoCH).
M15 Bias Settings:
i_m15EmaFast / i_m15EmaSlow: These two EMA (Exponential Moving Average) values on the 15-minute chart determine the main trend. A bullish trend is confirmed when the fast EMA is above the slow EMA, and vice-versa for a bearish trend.
M5 Point of Interest (POI) Settings:
i_showM5Fvg / i_showM5Ob: Toggles the visibility of Fair Value Gaps (FVG) and Order Blocks (OB) on the 5-minute chart. These are the zones where the script will look for trading opportunities.
i_maxPois: Limits the number of POI zones drawn on the chart to keep it clean.
LTF Entry Settings:
i_entryMode:
Confirmation: The script waits for a Change of Character (CHoCH) on the LTF (your current chart) after the price enters an M5 POI. A CHoCH is a break of a recent pivot high (for buys) or pivot low (for sells), suggesting a potential reversal. This is the safer entry method.
Aggressive: The script triggers an entry as soon as the price touches the 50% level of the M5 POI, without waiting for a CHoCH. This is higher risk but can provide a better entry price.
i_showChoch: Toggles the visibility of the CHoCH confirmation lines.
Trade Management Settings:
i_tpRatio: Sets the Risk-to-Reward Ratio (RRR) for the Take Profit target. For example, a value of 2.0 means the Take Profit distance will be twice the Stop Loss distance.
i_slMode: (New in V5.2) Provides four different methods to calculate the Stop Loss:
POI Zone (Default): Places the SL at the outer edge of the M5 POI zone.
Last Swing: Places the SL at the most recent LTF swing high/low before the entry.
ATR: Uses the Average True Range (ATR) indicator to set a volatility-based SL.
Previous Candle: Places the SL at the high or low of the candle immediately preceding the entry. This is the tightest and riskiest option.
i_maxHistory: Sets the number of past trades to display on the chart.
## Part 2: Data Types & Variables
This section defines custom data structures (type) to organize information:
Poi: A structure to hold all information related to a single Point of Interest, including its price boundaries, direction (bullish/bearish), and whether it has been mitigated (touched by price).
Trade: A structure to store details for each trade, such as its entry price, SL, TP, result (Win/Loss/Active), and chart objects for drawing.
## Part 3: Core Logic & Calculations
This is the engine of the indicator:
Data Fetching: It uses request.security to pull EMA data from the M15 timeframe and candle data (high, low, open, close) from the M5 timeframe.
POI Identification: The script constantly scans the M5 data for FVG and OB patterns. When a valid pattern is found that aligns with the M15 bias (e.g., a bullish OB during an M15 uptrend), it's stored as a Poi and drawn on the chart.
Entry Trigger:
It checks if the price on the LTF enters a valid (unmitigated) POI zone.
Based on the selected i_entryMode, it either waits for a CHoCH or enters aggressively.
Once an entry condition is met, it calculates the SL based on the i_slMode, calculates the TP using the i_tpRatio, and creates a new Trade.
Trade Monitoring: For every active trade, the script checks on each new bar if the price has hit the SL or TP level. When it does, the trade's result is updated, and the visual boxes are finalized.
## Part 5: On-Screen Display
This part creates the Performance Dashboard table shown on the top-right of the chart. It provides a real-time summary of:
M15 Bias: Current market direction.
Total Trades: The total number of completed trades from the history.
Win Rate: The percentage of winning trades.
Total R-Multiple: The cumulative Risk-to-Reward multiple (sum of RRR from wins minus losses). A positive value indicates overall profitability.
🇹🇭 คำอธิบายและข้อแนะนำภาษาไทย
สคริปต์นี้เป็น Indicator สำหรับกลยุทธ์การเทรดแบบ Smart Money Concepts (SMC) ที่ใช้การวิเคราะห์จากหลายกรอบเวลา (Multi-Timeframe) เพื่อหาจุดเข้าเทรดที่มีความเป็นไปได้สูง
หลักการทำงานของ Indicator มีดังนี้:
Timeframe ใหญ่ (HTF) - M15: ใช้กำหนดทิศทางหลักของตลาด หรือ "Bias"
Timeframe กลาง (MTF) - M5: ใช้หาโซนสำคัญ หรือ "Point of Interest (POI)" เช่น Order Blocks หรือ Fair Value Gaps ที่สอดคล้องกับทิศทางจาก M15
Timeframe เล็ก (LTF) - กราฟปัจจุบัน: ใช้หาสัญญาณยืนยันเพื่อเข้าเทรดในโซน POI ที่กำหนดไว้
รายละเอียดของโค้ด
## ส่วนที่ 1: การตั้งค่า (Inputs & Settings)
ส่วนนี้ให้คุณปรับแต่งค่าต่างๆ ของ Indicator ได้:
การตั้งค่าทั่วไป:
i_pivotLookback: กำหนดระยะเวลาที่ใช้มองหาจุดกลับตัว (Pivot) ใน Timeframe เล็ก (LTF) เพื่อใช้ยืนยันสัญญาณ Change of Character (CHoCH)
การตั้งค่า M15 (ทิศทางหลัก):
i_m15EmaFast / i_m15EmaSlow: ใช้เส้น EMA 2 เส้นบน Timeframe 15 นาที เพื่อกำหนดเทรนด์หลัก หาก EMA เร็วอยู่เหนือ EMA ช้า จะเป็นเทรนด์ขาขึ้น และในทางกลับกัน
การตั้งค่า M5 (จุดสนใจ - POI):
i_showM5Fvg / i_showM5Ob: เปิด/ปิด การแสดงโซน Fair Value Gaps (FVG) และ Order Blocks (OB) บน Timeframe 5 นาที ซึ่งเป็นโซนที่สคริปต์จะใช้หาโอกาสเข้าเทรด
i_maxPois: จำกัดจำนวนโซน POI ที่จะแสดงผลบนหน้าจอ เพื่อไม่ให้กราฟดูรกเกินไป
การตั้งค่า LTF (การเข้าเทรด):
i_entryMode:
ยืนยัน (Confirmation): เป็นโหมดที่ปลอดภัยกว่า โดยสคริปต์จะรอให้เกิดสัญญาณ Change of Character (CHoCH) ใน Timeframe เล็กก่อน หลังจากที่ราคาเข้ามาในโซน POI แล้ว
เชิงรุก (Aggressive): เป็นโหมดที่เสี่ยงกว่า โดยสคริปต์จะเข้าเทรดทันทีที่ราคาแตะระดับ 50% ของโซน POI โดยไม่รอสัญญาณยืนยัน CHoCH
i_showChoch: เปิด/ปิด การแสดงเส้น CHoCH บนกราฟ
การตั้งค่าการจัดการเทรด:
i_tpRatio: กำหนด อัตราส่วนกำไรต่อความเสี่ยง (Risk-to-Reward Ratio) เพื่อตั้งเป้าหมายทำกำไร (Take Profit) เช่น 2.0 หมายถึงระยะทำกำไรจะเป็น 2 เท่าของระยะตัดขาดทุน
i_slMode: (ฟีเจอร์ใหม่ V5.2) มี 4 รูปแบบในการคำนวณ Stop Loss:
โซน POI (ค่าเริ่มต้น): วาง SL ไว้ที่ขอบนอกสุดของโซน POI
Swing ล่าสุด: วาง SL ไว้ที่จุด Swing High/Low ล่าสุดของ Timeframe เล็ก (LTF) ก่อนเข้าเทรด
ATR: ใช้ค่า ATR (Average True Range) เพื่อกำหนด SL ตามระดับความผันผวนของราคา
แท่งเทียนก่อนหน้า: วาง SL ไว้ที่ราคา High/Low ของแท่งเทียนก่อนหน้าที่จะเข้าเทรด เป็นวิธีที่ SL แคบและเสี่ยงที่สุด
i_maxHistory: กำหนดจำนวนประวัติการเทรดที่จะแสดงย้อนหลังบนกราฟ
## ส่วนที่ 2: ประเภทข้อมูลและตัวแปร
ส่วนนี้เป็นการสร้างโครงสร้างข้อมูล (type) เพื่อจัดเก็บข้อมูลให้เป็นระบบ:
Poi: เก็บข้อมูลของโซน POI แต่ละโซน เช่น กรอบราคาบน-ล่าง, ทิศทาง (ขึ้น/ลง) และสถานะว่าถูกใช้งานไปแล้วหรือยัง (Mitigated)
Trade: เก็บรายละเอียดของแต่ละการเทรด เช่น ราคาเข้า, SL, TP, ผลลัพธ์ (Win/Loss/Active) และอ็อบเจกต์สำหรับวาดกล่องบนกราฟ
## ส่วนที่ 3: ตรรกะหลักและการคำนวณ
เป็นหัวใจสำคัญของ Indicator:
ดึงข้อมูลข้าม Timeframe: ใช้ฟังก์ชัน request.security เพื่อดึงข้อมูล EMA จาก M15 และข้อมูลแท่งเทียนจาก M5 มาใช้งาน
ระบุ POI: สคริปต์จะค้นหา FVG และ OB บน M5 ตลอดเวลา หากเจ้ารูปแบบที่สอดคล้องกับทิศทางหลักจาก M15 (เช่น เจอ Bullish OB ในขณะที่ M15 เป็นขาขึ้น) ก็จะวาดโซนนั้นไว้บนกราฟ
เงื่อนไขการเข้าเทรด:
เมื่อราคาใน Timeframe เล็ก (LTF) วิ่งเข้ามาในโซน POI ที่ยังไม่เคยถูกใช้งาน
สคริปต์จะรอสัญญาณตาม i_entryMode ที่เลือกไว้ (รอ CHoCH หรือเข้าแบบ Aggressive)
เมื่อเงื่อนไขครบ จะคำนวณ SL และ TP จากนั้นจึงบันทึกการเทรดใหม่
ติดตามการเทรด: สำหรับเทรดที่ยัง "Active" อยู่ สคริปต์จะคอยตรวจสอบทุกแท่งเทียนว่าราคาไปถึง SL หรือ TP แล้วหรือยัง เมื่อถึงจุดใดจุดหนึ่ง จะบันทึกผลและสิ้นสุดการวาดกล่องบนกราฟ
## ส่วนที่ 5: การแสดงผลบนหน้าจอ
ส่วนนี้จะสร้างตาราง "Performance Dashboard" ที่มุมขวาบนของกราฟ เพื่อสรุปผลการทำงานแบบ Real-time:
M15 Bias: แสดงทิศทางของตลาดในปัจจุบัน
Total Trades: จำนวนเทรดทั้งหมดที่เกิดขึ้นในประวัติ
Win Rate: อัตราชนะ คิดเป็นเปอร์เซ็นต์
Total R-Multiple: ผลตอบแทนรวมจากความเสี่ยง (R) ทั้งหมด (ผลรวม RRR ของเทรดที่ชนะ ลบด้วยจำนวนเทรดที่แพ้) หากเป็นบวกแสดงว่ามีกำไรโดยรวม
📋 ข้อแนะนำในการใช้งาน
Timeframe ที่เหมาะสม: Indicator นี้ถูกออกแบบมาให้ใช้กับ Timeframe เล็ก (LTF) เช่น M1, M3 หรือ M5 เนื่องจากมันดึงข้อมูลจาก M15 และ M5 มาเป็นหลักการอยู่แล้ว
สไตล์การเทรด:
Confirmation: เหมาะสำหรับผู้ที่ต้องการความปลอดภัยสูง รอการยืนยันก่อนเข้าเทรด อาจจะตกรถบ้าง แต่ลดความเสี่ยงจากการเข้าเทรดเร็วเกินไป
Aggressive: เหมาะสำหรับผู้ที่ยอมรับความเสี่ยงได้สูงขึ้น เพื่อให้ได้ราคาเข้าที่ดีที่สุด
การเลือก Stop Loss:
"Swing ล่าสุด" และ "โซน POI" เป็นวิธีมาตรฐานตามหลัก SMC
"ATR" เหมาะกับตลาดที่มีความผันผวนสูง เพราะ SL จะปรับตามสภาพตลาด
"แท่งเทียนก่อนหน้า" เป็นวิธีที่เสี่ยงที่สุด เหมาะกับการเทรดเร็วและต้องการ RRR สูงๆ แต่ก็มีโอกาสโดน SL ง่ายขึ้น
การบริหารความเสี่ยง: Indicator นี้เป็นเพียง เครื่องมือช่วยวิเคราะห์ ไม่ใช่สัญญาณซื้อขายอัตโนมัติ 100% ผู้ใช้ควรมีความเข้าใจในหลักการของ SMC และทำการบริหารความเสี่ยง (Risk Management) อย่างเคร่งครัดเสมอ
การทดสอบย้อนหลัง (Backtesting): ควรทำการทดสอบ Indicator กับสินทรัพย์และตั้งค่าต่างๆ เพื่อให้เข้าใจลักษณะการทำงานและประสิทธิภาพของมันก่อนนำไปใช้เทรดจริง
Spot Nachkauf-Zonen High TF (RSI + BB)**Spot Buy/Sell Zones High TF Indicator (RSI + Bollinger Bands + Trend & Volume Filters)**
This is an overlay indicator for TradingView that highlights optimal buy and sell areas on a higher timeframe (e.g. Daily, Weekly) while you view a lower timeframe chart. It combines volatility, momentum, trend and volume checks to reduce false signals.
---
### Key Features
* **Higher-Timeframe Calculations**
All indicators (Bollinger Bands, RSI, moving averages, volume) use data from a user-selected timeframe (for example “D” for daily or “W” for weekly).
* **Bollinger Bands**
* Middle line: Simple Moving Average (SMA) over N periods
* Upper/Lower bands: ±M × standard deviation
* Semi-transparent fill between the bands for quick visual reference
* **RSI Momentum**
* Classic 14-period RSI with adjustable overbought (e.g. 70) and oversold (e.g. 30) levels
* **Buy** when RSI crosses up out of oversold and price touches or goes below the lower Bollinger Band
* **Sell** when RSI crosses down out of overbought and price touches or goes above the upper Bollinger Band
* **Trend Filter (Optional)**
* Higher-TF SMA (default 200 periods) plotted in orange
* Signals only fire when price is above the SMA (for buys) or below (for sells) to align with the main trend
* **Volume Filter (Optional)**
* Compares current higher-TF volume against its SMA
* Signals require volume to exceed a user-set multiplier of average volume, ensuring real market participation
* **Visual Signals**
* Green triangles below bars mark buy zones; red triangles above bars mark sell zones
* Light green background highlights active buy areas
* **Built-In Alerts**
* Two alert conditions (“Buy Signal” and “Sell Signal”) ready to be used in TradingView’s Alert dialog
* Customizable alert messages include ticker and timeframe
---
### Inputs
| Setting | Default | Purpose |
| ------------------------- | ------- | ------------------------------------------------ |
| **Calculation Timeframe** | D | Higher timeframe for all calculations |
| **BB Periods** | 20 | Length of SMA for Bollinger middle line |
| **BB Std-Dev Multiplier** | 2.0 | Number of standard deviations for the bands |
| **RSI Periods** | 14 | Length of the RSI calculation |
| **Overbought / Oversold** | 70 / 30 | RSI thresholds for signal generation |
| **Enable Trend Filter** | true | Use higher-TF SMA to confirm trend direction |
| **Trend MA Periods** | 200 | SMA length for the trend filter |
| **Enable Volume Filter** | true | Require above-average volume to validate signals |
| **Volume MA Periods** | 20 | SMA length for volume filter |
| **Volume Multiplier** | 1.2 | How many times above average volume is needed |
---
### How to Use
1. **Add the Script**: Paste the Pine code into TradingView’s Pine Editor and save.
2. **Adjust Settings**: Choose your higher timeframe (“D”, “W”, etc.) and tweak BB, RSI, trend, and volume parameters.
3. **Activate Alerts**: In the Alerts panel, select the “Buy Signal” or “Sell Signal” alert condition.
4. **Interpret Signals**:
* A green triangle + green background = suggested buy zone
* A red triangle = suggested sell zone
This setup gives you clear, rule-based entry and exit areas by filtering noise and confirming market strength on a higher timeframe.
Liquidity Sweeps [SB1]Liquidity Sweeps
This indicator detects liquidity sweep events where price briefly breaks above or below recent swing points before reversing. These sweeps often occur during stop hunts, fakeouts, or liquidity grabs, and are commonly used by smart money traders to trap breakout participants before reversing direction.
🔍 What It Does
Identifies key swing highs and lows based on user-defined pivot strength.
Detects:
Bearish Sweeps: Price breaks a recent high but fails to close above it.
Bullish Sweeps: Price breaks a recent low but fails to close below it.
Tracks whether these sweeps are simply wicks, full breakouts and retests, or a combination of both.
Highlights these zones with boxes and labels to signal high-probability reversal or reaction zones.
🧠 Why Use It
Liquidity sweeps are often used by institutions and large players to trigger stops and create movement. Detecting these events helps traders:
Avoid chasing false breakouts
Time entries around exhaustion or reversal points
Align trades with Smart Money Concepts (SMC), ICT principles, or Order Block Theory
Avoid chasing false breakouts
Time entries around exhaustion or reversal points
Align trades with Smart Money Concepts (SMC), ICT principles, or Order Block Theory
⚙️ Settings & Customization
Swings: Adjusts the sensitivity of swing high/low detection.
Detection Type:
Only Wicks: Detects when a wick pierces a level but closes back inside.
Only Outbreaks & Retests: Detects when a candle breaks out and later retests.
Wicks + Outbreaks & Retests: Shows both types for full coverage.
Extend Zones: Draws boxes across future bars until invalidation.
Colors: Fully customizable for bullish and bearish sweeps.
🧬 Original Enhancements
This script is based on open-source work by LuxAlgo and has been significantly enhanced with:
Multiple detection modes
Real-time alert support📣 📣
Efficient pivot memory cleanup📣 📣
Sweep zone auto-extension until broken
Improved visual clarity with dotted/dashed lines, and color-coded boxes
✅ Note: The original version had no alerts. This version adds real-time detection alerts for practical trading use. Credit: Original swing detection logic inspired by LuxAlgo’s open-source Liquidity Sweep framework. This version is extended and modified under the terms of the CC BY-NC-SA 4.0 license.
📣 📣 Alerts Included📣📣
🔼 Bullish Wick Sweep📣
🔽 Bearish Wick Sweep📣
These alerts allow traders to be notified the moment a liquidity sweep occurs, providing immediate edge for reactive or anticipatory trading.
📈 How to Use It
Add to your chart.
Choose the detection type based on your trading style:
Wicks for reversals and stop hunts
Outbreaks for failed breakouts or retests
Wait for sweep zones to form and monitor price behavior around them.
Use in conjunction with:
Fair Value Gaps (FVG)
Order Blocks
VWAP Anchors
Market Structure Breaks/ Breaks of structures
NEXGEN ADXNEXGEN ADX
NEXGEN ADX – Advanced Trend Strength & Directional Indicator
Purpose:
The NEXGEN ADX is a powerful trend analysis tool developed by NexGen Trading Academy to help traders identify the strength and direction of market trends with precision. Based on the Average Directional Index (ADX) along with +DI (Positive Directional Indicator) and –DI (Negative Directional Indicator), this custom indicator provides a reliable foundation for both trend-following strategies and trend reversal setups.
Faytterro Bands Breakout📌 Faytterro Bands Breakout 📌
This indicator was created as a strategy showcase for another script: Faytterro Bands
It’s meant to demonstrate a simple breakout strategy based on Faytterro Bands logic and includes performance tracking.
❓ What Is It?
This script is a visual breakout strategy based on a custom moving average and dynamic deviation bands, similar in concept to Bollinger Bands but with unique smoothing (centered regression) and performance features.
🔍 What Does It Do?
Detects breakouts above or below the Faytterro Band.
Plots visual trade entries and exits.
Labels each trade with percentage return.
Draws profit/loss lines for every trade.
Shows cumulative performance (compounded return).
Displays key metrics in the top-right corner:
Total Return
Win Rate
Total Trades
Number of Wins / Losses
🛠 How Does It Work?
Bullish Breakout: When price crosses above the upper band and stays above the midline.
Bearish Breakout: When price crosses below the lower band and stays below the midline.
Each trade is held until breakout invalidation, not a fixed TP/SL.
Trades are compounded, i.e., profits stack up realistically over time.
📈 Best Use Cases:
For traders who want to experiment with breakout strategies.
For visual learners who want to study past breakouts with performance metrics.
As a template to develop your own logic on top of Faytterro Bands.
⚠ Notes:
This is a strategy-like visual indicator, not an automated backtest.
It doesn't use strategy.* commands, so you can still use alerts and visuals.
You can tweak the logic to create your own backtest-ready strategy.
Unlike the original Faytterro Bands, this script does not repaint and is fully stable on closed candles.
Frahm Factor Position Size CalculatorThe Frahm Factor Position Size Calculator is a powerful evolution of the original Frahm Factor script, leveraging its volatility analysis to dynamically adjust trading risk. This Pine Script for TradingView uses the Frahm Factor’s volatility score (1-10) to set risk percentages (1.75% to 5%) for both Margin-Based and Equity-Based position sizing. A compact table on the main chart displays Risk per Trade, Frahm Factor, and Average Candle Size, making it an essential tool for traders aligning risk with market conditions.
Calculates a volatility score (1-10) using true range percentile rank over a customizable look-back window (default 24 hours).
Dynamically sets risk percentage based on volatility:
Low volatility (score ≤ 3): 5% risk for bolder trades.
High volatility (score ≥ 8): 1.75% risk for caution.
Medium volatility (score 4-7): Smoothly interpolated (e.g., 4 → 4.3%, 5 → 3.6%).
Adjustable sensitivity via Frahm Scale Multiplier (default 9) for tailored volatility response.
Position Sizing:
Margin-Based: Risk as a percentage of total margin (e.g., $175 for 1.75% of $10,000 at high volatility).
Equity-Based: Risk as a percentage of (equity - minimum balance) (e.g., $175 for 1.75% of ($15,000 - $5,000)).
Compact 1-3 row table shows:
Risk per Trade with Frahm score (e.g., “$175.00 (Frahm: 8)”).
Frahm Factor (e.g., “Frahm Factor: 8”).
Average Candle Size (e.g., “Avg Candle: 50 t”).
Toggles to show/hide Frahm Factor and Average Candle Size rows, with no empty backgrounds.
Four sizes: XL (18x7, large text), L (13x6, normal), M (9x5, small, default), S (8x4, tiny).
Repositionable (9 positions, default: top-right).
Customizable cell color, text color, and transparency.
Set Frahm Factor:
Frahm Window (hrs): Pick how far back to measure volatility (e.g., 24 hours). Shorter for fast markets, longer for chill ones.
Frahm Scale Multiplier: Set sensitivity (1-10, default 9). Higher makes the score jumpier; lower smooths it out.
Set Margin-Based:
Total Margin: Enter your account balance (e.g., $10,000). Risk auto-adjusts via Frahm Factor.
Set Equity-Based:
Total Equity: Enter your total account balance (e.g., $15,000).
Minimum Balance: Set to the lowest your account can go before liquidation (e.g., $5,000). Risk is based on the difference, auto-adjusted by Frahm Factor.
Customize Display:
Calculation Method: Pick Margin-Based or Equity-Based.
Table Position: Choose where the table sits (e.g., top_right).
Table Size: Select XL, L, M, or S (default M, small text).
Table Cell Color: Set background color (default blue).
Table Text Color: Set text color (default white).
Table Cell Transparency: Adjust transparency (0 = solid, 100 = invisible, default 80).
Show Frahm Factor & Show Avg Candle Size: Check to show these rows, uncheck to hide (default on).
Wyckoff Smart Signals (Long + Short)- Wycoff Smart signals made by Melik
Using Wycoff fundamentals and volume confirmation to form a bias
Position Size CalculatorIt calculates the risk per trade using two methods: Margin-Based (percentage of total Account Balance) or Equity-Based (percentage of Total Balance minus minimum balance). Displayed as a compact, customizable label on the main chart, it’s perfect for traders seeking quick, precise risk calculations.
Key Features
Two Calculation Options:
Margin-Based: Risk as a percentage (0-5%) of your total account balance.
Equity-Based: Risk as a percentage (0-50%) of (Total balance - Minimum balance).
Flexible Risk Input: Manually enter any risk percentage with 0.01% precision (e.g., 1.75%).
Customizable Display:
Repositionable table (9 positions, e.g., top-right, middle-center).
Four table sizes (XL, L, M, S) with text scaling (large, normal, small, tiny).
Adjustable cell color, text color, and transparency
Margin-Based Risk Calculation:
Set “Total Margin” (e.g., $10,000).
Enter “Risk Percentage (%)” (0 to 5%, e.g., 1.75%).
Equity-Based Risk Calculation:
Set “Total Equity” (e.g., $15,000).
Set “Minimum Balance” (e.g., $5,000).
Enter “Equity Risk Percentage (%)” (0 to 50%, e.g., 1.75%).
Display Settings:
Choose “Calculation Method” (Margin-Based or Equity-Based).
Select “Table Position” (e.g., top_right).
Select “Table Size” (XL, L, M, S; default M).
Customize “Table Cell Color”, “Table Text Color”, and “Table Cell Transparency”.
MVWAP 5/21/50 + LWMA 400Moving vwap de 5,21,50 y media movil ponderada de 400
se puede utilizar con cruces
Gattsreal EMASummary
The Gattsreal EMA indicator is a complete technical analysis tool designed to provide a clear and immediate view of the market trend and momentum across multiple timeframes. It combines long-term Exponential Moving Averages (EMAs) with a short-term EMA "ribbon," allowing traders to quickly identify the direction of the main trend and the strength of short-term movements.
Indicator Components
The Gattsreal EMA is composed of two main elements, both fully customizable:
Long-Term EMAs (Thick Lines):
EMA 200 (White): Considered the definitive line between a bull market and a bear market. Prices above the 200 EMA are generally considered to be in a long-term uptrend.
EMA 50 (Blue): An important medium-term trend line, often used as a dynamic level of support or resistance.
Short-Term EMA Ribbon:
Consists of a set of 9 EMAs (periods 9, 10, 15, 20, 25, 30, 35, 40, and 45).
The "ribbon" expands when volatility increases and contracts when volatility decreases.
The color of the ribbon's fill changes to indicate short-term momentum:
Green: The ribbon is in an uptrend (fastest EMA above the slowest), suggesting buying pressure.
Red: The ribbon is in a downtrend (fastest EMA below the slowest), suggesting selling pressure.
How to Use the Indicator
The Gattsreal EMA can be used in various ways to enhance your analysis and decision-making:
Main Trend Identification: The price's position relative to the 200 and 50 EMAs helps define your operational bias. It is preferable to trade in the direction of the main trend.
Entry and Exit Signals: The crossing of the price through the EMA ribbon can be used as a signal. For example, when the price crosses and closes above the entire ribbon and it turns green, it can be a buy signal.
Momentum Confirmation: The color and expansion of the ribbon serve as excellent confirmation of the strength of a move. A green and expanding ribbon confirms strong bullish momentum.
Dynamic Support and Resistance: All 11 EMAs can act as dynamic levels of support (in an uptrend) or resistance (in a downtrend).
This indicator is a powerful tool for traders of all levels looking for a visual and effective way to analyze market trends.
LiliALHUNTERSystemLibrary "LiliALHUNTERSystem"
HUNTER System Library - Powerful target management for Pine Script
ema_calc(len, source)
Parameters:
len (simple int)
source (float)
rma_calc(len, source)
Parameters:
len (simple int)
source (float)
supertrend_calc(length, factor)
Parameters:
length (simple int)
factor (float)
createTargets(config, state, source1A, source1B, source2A, source2B)
Parameters:
config (TargetConfig)
state (TargetState)
source1A (float)
source1B (float)
source2A (float)
source2B (float)
showDashboard(state, dashLoc, textSize)
Parameters:
state (TargetState)
dashLoc (string)
textSize (string)
TargetConfig
Fields:
enableTarget1 (series bool)
enableTarget2 (series bool)
isLong1 (series bool)
isLong2 (series bool)
target1Condition (series string)
target2Condition (series string)
target1Color (series color)
target2Color (series color)
target1Style (series string)
target2Style (series string)
distTarget1 (series float)
distTarget2 (series float)
distOptions1 (series string)
distOptions2 (series string)
showLabels (series bool)
showDash (series bool)
TargetState
Fields:
target1LineV (series line)
target1LineH (series line)
target2LineV (series line)
target2LineH (series line)
target1Lbl (series label)
target2Lbl (series label)
target1Active (series bool)
target2Active (series bool)
target1Value (series float)
target2Value (series float)
countTargets1 (series int)
countTgReached1 (series int)
countTargets2 (series int)
countTgReached2 (series int)
Holy GrailThis is a long-only educational strategy that simulates what happens if you keep adding to a position during pullbacks and only exit when the asset hits a new All-Time High (ATH). It is intended for learning purposes only — not for live trading.
🧠 How it works:
The strategy identifies pullbacks using a simple moving average (MA).
When price dips below the MA, it begins monitoring for the first green candle (close > open).
That green candle signals a potential bottom, so it adds to the position.
If price goes lower, it waits for the next green candle and adds again.
The exit happens after ATH — it sells on each red candle (close < open) once a new ATH is reached.
You can adjust:
MA length (defines what’s considered a pullback)
Initial buy % (how much to pre-fill before signals start)
Buy % per signal (after pullback green candle)
Exit % per red candle after ATH
📊 Intended assets & timeframes:
This strategy is designed for broad market indices and long-term appreciating assets, such as:
SPY, NASDAQ, DAX, FTSE
Use it only on 1D or higher timeframes — it’s not meant for scalping or short-term trading.
⚠️ Important Limitations:
Long-only: The script does not short. It assumes the asset will eventually recover to a new ATH.
Not for all assets: It won't work on assets that may never recover (e.g., single stocks or speculative tokens).
Slow capital deployment: Entries happen gradually and may take a long time to close.
Not optimized for returns: Buy & hold can outperform this strategy.
No slippage, fees, or funding costs included.
This is not a performance strategy. It’s a teaching tool to show that:
High win rate ≠ high profitability
Patience can be deceiving
Many signals = long capital lock-in
🎓 Why it exists:
The purpose of this strategy is to demonstrate market psychology and risk overconfidence. Traders often chase strategies with high win rates without considering holding time, drawdowns, or opportunity cost.
This script helps visualize that phenomenon.
SymFlex Band No1. - Momentum Weighted Volatility BandsSymFlex Band No1 – Momentum-Weighted Adaptive Volatility Band
Overview
The SymFlex Band No1 is a custom-built volatility band that fuses momentum and volatility into a flexible, asymmetric envelope.
It adapts dynamically to market conditions using RSI-based momentum weighting and a selection of smoothing algorithms, making it responsive to both trend shifts and volatility expansions.
Key Features
📊 Momentum-Weighted Width
The band expands or contracts based on RSI momentum. When the RSI is above 50, the upper band becomes more sensitive; when below 50, the lower band responds more dynamically.
🔁 Asymmetric Adaptation
Unlike traditional Bollinger Bands or Keltner Channels, the upper and lower bands of the SymFlex system are independently adjusted based on momentum conditions, creating a non-linear envelope structure.
⚙️ Selectable Smoothing Methods
You can choose among the following methods to control the volatility smoothing:
EMA (Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
ZeroLag EMA v0 (double EMA difference method)
ZeroLag EMA v1 (lag-compensated input)
🛠 Fully Customizable Inputs
RSI Length
Band Multiplier
Band Length
Smoothing Type
How It Works
RSI is calculated over a defined length and normalized to a weight between -1 and +1.
Standard deviation (volatility) of the close price is computed and smoothed.
The band centerline is a Simple Moving Average (SMA).
The band boundaries are then:
Upper = Middle + (1 + momentum_weight) × multiplier × smoothed_volatility
Lower = Middle - (1 + momentum_weight) × multiplier × smoothed_volatility
Use Cases
Detect momentum-driven breakouts
Spot compressions before expansions
Adapt to volatile or trending markets more effectively than fixed bands
Disclaimer
This script is for educational and research purposes only. It is not financial advice. Use with discretion and always validate with additional signals and proper risk management.
Crypto Pulse Strategy ActiveCrypto Pulse Strategy Active
Short-term crypto strategy for 1h-4h charts. Uses RSI, Bollinger Bands, and VWAP to spot buy/sell signals. Buy above VWAP with low BB or RSI < 25; sell below VWAP with high BB or RSI > 75. Risks 1% per trade with 1.5% stop-loss and 1.5x profit. Test on BTC/ETH first!
Chaikin Money Flow (CMF) [ParadoxAlgo]OVERVIEW
This indicator implements the Chaikin Money Flow oscillator as an overlay on the price chart, designed to help traders identify institutional money flow patterns. The Chaikin Money Flow combines price and volume data to measure the flow of money into and out of a security, making it particularly useful for detecting accumulation and distribution phases.
WHAT IS CHAIKIN MONEY FLOW?
Chaikin Money Flow was developed by Marc Chaikin and measures the amount of Money Flow Volume over a specific period. The indicator oscillates between +1 and -1, where:
Positive values indicate money flowing into the security (accumulation)
Negative values indicate money flowing out of the security (distribution)
Values near zero suggest equilibrium between buying and selling pressure
CALCULATION METHOD
Money Flow Multiplier = ((Close - Low) - (High - Close)) / (High - Low)
Money Flow Volume = Money Flow Multiplier × Volume
CMF = Sum of Money Flow Volume over N periods / Sum of Volume over N periods
KEY FEATURES
Big Money Detection:
Identifies significant institutional activity when CMF exceeds user-defined thresholds
Requires volume confirmation (volume above average) to validate signals
Uses battery icon (🔋) for institutional buying and lightning icon (⚡) for institutional selling
Visual Elements:
Background coloring based on money flow direction
Support and resistance levels calculated using Average True Range
Real-time dashboard showing current CMF value, volume strength, and signal status
Customizable Parameters:
CMF Period: Calculation period for the money flow (default: 20)
Signal Smoothing: EMA smoothing applied to reduce noise (default: 5)
Big Money Threshold: CMF level required to trigger institutional signals (default: 0.15)
Volume Threshold: Volume multiplier required for signal confirmation (default: 1.5x)
INTERPRETATION
Signal Types:
🔋 (Battery): Indicates strong institutional buying when CMF > threshold with high volume
⚡ (Lightning): Indicates strong institutional selling when CMF < -threshold with high volume
Background color: Green tint for positive money flow, red tint for negative money flow
Dashboard Information:
CMF Value: Current Chaikin Money Flow reading
Volume: Current volume as a multiple of 20-period average
Big Money: Status of institutional activity (BUYING/SELLING/QUIET)
Signal: Strength assessment (STRONG/MEDIUM/WEAK)
TRADING APPLICATIONS
Trend Confirmation: Use CMF direction to confirm price trends
Divergence Analysis: Look for divergences between price and money flow
Volume Validation: Confirm breakouts with corresponding money flow
Accumulation/Distribution: Identify phases of institutional activity
PARAMETER RECOMMENDATIONS
Day Trading: CMF Period 14-21, higher sensitivity settings
Swing Trading: CMF Period 20-30, moderate sensitivity
Position Trading: CMF Period 30-50, lower sensitivity for major trends
ALERTS
Optional alert system notifies users when:
Big money buying is detected (CMF above threshold with volume confirmation)
Big money selling is detected (CMF below negative threshold with volume confirmation)
LIMITATIONS
May generate false signals in low-volume conditions
Best used in conjunction with other technical analysis tools
Effectiveness varies across different market conditions and timeframes
EDUCATIONAL PURPOSE
This open-source indicator is provided for educational purposes to help traders understand money flow analysis. It demonstrates the practical application of the Chaikin Money Flow concept with visual enhancements for easier interpretation.
TECHNICAL SPECIFICATIONS
Overlay indicator (displays on price chart)
No repainting - all calculations are based on closed bar data
Suitable for all timeframes and asset classes
Minimal resource usage for optimal performance
DISCLAIMER
This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and consider risk management before making trading decisions.
Machine Learning Key Levels [AlgoAlpha]🟠 OVERVIEW
This script plots Machine Learning Key Levels on your chart by detecting historical pivot points and grouping them using agglomerative clustering to highlight price levels with the most past reactions. It combines a pivot detection, hierarchical clustering logic, and an optional silhouette method to automatically select the optimal number of key levels, giving you an adaptive way to visualize price zones where activity concentrated over time.
🟠 CONCEPTS
Agglomerative clustering is a bottom-up method that starts by treating each pivot as its own cluster, then repeatedly merges the two closest clusters based on the average distance between their members until only the desired number of clusters remain. This process creates a hierarchy of groupings that can flexibly describe patterns in how price reacts around certain levels. This offers an advantage over K-means clustering, since the number of clusters does not need to be predefined. In this script, it uses an average linkage approach, where distance between clusters is computed as the average pairwise distance of all contained points.
The script finds pivot highs and lows over a set lookback period and saves them in a buffer controlled by the Pivot Memory setting. When there are at least two pivots, it groups them using agglomerative clustering: it starts with each pivot as its own group and keeps merging the closest pairs based on their average distance until the desired number of clusters is left. This number can be fixed or chosen automatically with the silhouette method, which checks how well each point fits in its cluster compared to others (higher scores mean cleaner separation). Once clustering finishes, the script takes the average price of each cluster to create key levels, sorts them, and draws horizontal lines with labels and colors showing their strength. A metrics table can also display details about the clusters to help you understand how the levels were calculated.
🟠 FEATURES
Agglomerative clustering engine with average linkage to merge pivots into level groups.
Dynamic lines showing each cluster’s price level for clarity.
Labels indicating level strength either as percent of all pivots or raw counts.
A metrics table displaying pivot count, cluster count, silhouette score, and cluster size data.
Optional silhouette-based auto-selection of cluster count to adaptively find the best fit.
🟠 USAGE
Add the indicator to any chart. Choose how far back to detect pivots using Pivot Length and set Pivot Memory to control how many are kept for clustering (more pivots give smoother levels but can slow performance). If you want the script to pick the number of levels automatically, enable Auto No. Levels ; otherwise, set Number of Levels . The colored horizontal lines represent the calculated key levels, and circles show where pivots occurred colored by which cluster they belong to. The labels beside each level indicate its strength, so you can see which levels are supported by more pivots. If Show Metrics Table is enabled, you will see statistics about the clustering in the corner you selected. Use this tool to spot areas where price often reacts and to plan entries or exits around levels that have been significant over time. Adjust settings to better match volatility and history depth of your instrument.
