Machine Learning-Inspired Supply & Demand Zones [AlgoPoint]This indicator is a Smart Supply & Demand Zone tool, developed with principles inspired by Machine Learning (ML). It intelligently filters out market noise, allowing you to focus only on the most significant zones where institutional order flow is likely present.
💡 How It Works: Why Is This Indicator "Smart"?
Unlike traditional indicators that only measure simple price movements, this script uses an algorithm that asks the same critical questions an experienced market analyst would to qualify a zone:
- 1. Price Imbalance: How fast and aggressively did the price leave the zone? Our algorithm measures the body size of the "departure candle" relative to the current market volatility (ATR). A zone is only considered if it was formed by an explosive move that is statistically significant, indicating a major imbalance between buyers and sellers.
- 2. Volume Confirmation: Did the "smart money" participate in this move? The script checks if the volume on the departure candle was significantly higher than the recent average volume. A spike in volume confirms that the move was backed by institutional interest, adding strength and validity to the zone.
- 3. Valid Pivot Structure: Did the zone originate from a meaningful swing high or low? The algorithm first identifies a valid pivot structure, ensuring that zones are not drawn from insignificant or random price fluctuations.
Only when a potential zone passes these three critical tests—our "quality filter"—is it drawn on your chart.
🚀 Features & How to Use
Using the indicator is straightforward. You will see two primary types of boxes on your chart:
* 🟥 Red Box (Supply Zone): An area of potential resistance where selling pressure is likely to be strong. Look for potential shorting opportunities as the price approaches this zone.
* 🟩 Green Box (Demand Zone): An area of potential support where buying pressure is likely to be strong. Look for potential long opportunities as the price pulls back into this zone.
Dynamic Zone Management
This indicator is not static; it lives and breathes with the market:
- Fresh Zone: A newly formed zone appears in its full, vibrant color. These are the highest-probability zones as they have not yet been re-tested.
- Broken / Flipped Zone: You have full control over what happens when a zone is broken! In the settings, you can choose:
- Delete Zone: The zone will be removed completely when the price closes through it.
- Show as Broken (Flip): When broken, the zone will turn gray, stop extending, and remain on your chart. This is extremely useful for identifying Support/Resistance Flips, where a broken demand zone becomes new resistance, or a broken supply zone becomes new support.
⚙️ Settings & Customization
Fine-tune the indicator to match your personal trading style via the settings menu:
- Breakout Behavior: The most powerful feature. Choose between Delete Zone and Show as Broken (Flip) to customize your chart.
- Zone Finding Logic: Control the indicator's sensitivity.
- Selective: Requires both strong imbalance and high volume. Finds fewer, but higher-quality, zones.
- Moderate: Requires either strong imbalance or high volume. Finds more potential zones.
- Sensitivity Settings: Adjust the ATR Multiplier and Volume Multiplier to make the criteria for a "strong" zone stricter or looser.
Indicators and strategies
BE-Fib Channel 2 Sided Trading█ Overview:
"BE-Fib Channel 2 Sided Trading" indicator is built with the thought of 2 profound setups named "Cup & Handle (C&H)" and "Fibonacci Channel Trading (FCT)" with the context of "day trading" or with a minimum holding period.
█ Similarities, Day Trading Context & Error Patterns:
While the known fact is that both C&H and FCT provide setups with lesser risk with bigger returns, they both share the similar "Base Pattern".
Note: Inverse of the above Image shall switch the setups between long vs short.
Since the indicator is designed for smaller time-frame candles, there may be instances where the "base pattern" does not visually resemble a Cup & Handle (C&H) pattern. However, patterns are validated using pivot points. The points labeled "A" and "C" can be equal or slightly slanted. Settings of the Indicator allows traders a flexibility to control the angle of these points to spot the strategies according to set conditions. Therefore, understanding the nuances of these patterns is crucial for effective decision-making.
█ 2 Sided Edge: FCT suggests to take trade closer to the yellow line to get better RR ratio. this leaves a small chance of doubt as to; what if price is intended to break the Yellow line thereby activating the C&H.
Wait for the confirmation is a Big FOMO with a compromised RR.
Hence, This indicator is designed to handle both the patterns based on the strength, FIFO and pattern occurring delay.
█ How to Use this Indicator:
Step 1: Enable the Show Sample Sensitivity option to understand the angle of yellow line shown in the sample image. By enabling this option, On the last bar you shall see 4 lines being plotted depicting the max angle which is acceptable for both long and short trades.
Note: Angle can be controlled via setting "Sensitivity".
Higher Sensitivity --> Higher Setup identification --> can lead to failed setups due to 2 sided trading.
Lower Sensitivity --> Lower Setup identification --> can increase the changes of being right.
Step 2: Adjust the look back & look forward periods which shall be used for identifying patterns.
Note: Smaller values can lead to more setups being identified but can hamper the performance of the indicator while increasing the chances of failures. larger values identifies more significant setup but leads to more waiting period thereby compromising on the RR.
Step 3: Adjust the Base Range.
Note: Smaller values can lead to more setups being identified but can hamper the performance of the indicator while increasing the chances of failures. larger values identifies more significant setup but leads to more Risk on play.
Step 4: set the Entry level for FCT & Set the SL for Both FCT & C&H and Target Reward ratio for C&H.
█ Features of Indicator & How it works:
1. Patterns are being identified using Pivot Points method.
2. Tracks & validates both the setups simultaneously on every candle and traded one at a time based on FIFO, New setups found in-between, Defined Entry Levels while on wait for the other pattern to get activated.
3. Alerts added for trade events.
4. FCT setups are generally traded with trailed SL level and increasing Target level on every completed bar. while C&H has the standard SL & TP level with no Trail SL option.
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorized for our documents, script / strategy, and the information published with them. This informational planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. I am not responsible for any losses you may incur. Please invest wisely.
Happy to receive suggestions and feedback in order to improve the performance of the indicator better.
ATR% | Volatility NormalizerThis indicator measures true volatility by expressing the Average True Range (ATR) as a percentage of price. Unlike basic ATR plots, which show raw values, this version normalizes volatility to make it directly comparable across instruments and timeframes.
How it works:
Uses True Range (High–Low plus gaps) to capture actual market movement.
Normalizes by dividing ATR by the chosen price base (default: Close).
Multiplies by 100 to output a clean ATR% line.
Smoothing is flexible: choose from RMA, SMA, EMA, or WMA.
Optional Feature:
For comparison, you can toggle an auxiliary line showing the average absolute close-to-close % move, highlighting the difference between simplified and true volatility.
Why use it:
Track regime shifts: identify when volatility expands or contracts in % terms.
Compare volatility across different markets (equities, crypto, forex, commodities).
Integrate into risk management: position sizing, stop placement, or volatility filters for entries.
Interpretation:
Rising ATR% → expanding volatility, potential breakouts or unstable ranges.
Falling ATR% → contracting volatility, possible consolidation or range-bound conditions.
Sudden spikes → market “shocks” worth paying attention to.
EMA/VWAP SuiteEMA/VWAP Suite
Overview
The EMA/VWAP Suite is a versatile and customizable Pine Script indicator designed for traders who want to combine Exponential Moving Averages (EMAs) and Volume Weighted Average Prices (VWAPs) in a single, powerful tool. It overlays up to eight EMAs and six VWAPs (three anchored, three rolling) on the chart, each with percentage difference labels to show how far the current price is from these key levels. This indicator is perfect for technical analysis, supporting strategies like trend following, mean reversion, and VWAP-based trading.
By default, the indicator displays eight EMAs and a session-anchored VWAP (AVWAP 1, in fuchsia) with their respective percentage difference labels, keeping the chart clean yet informative. Other VWAPs and their bands are disabled by default but can be enabled and customized as needed. The suite is designed to minimize clutter while providing maximum flexibility for traders.
Features
- Eight Customizable EMAs: Plot up to eight EMAs with user-defined lengths (default: 3, 9, 19, 38, 50, 65, 100, 200), each with a unique color for easy identification.
- EMA Percentage Difference Labels: Show the percentage difference between the current price and each EMA, displayed only for visible EMAs when enabled.
- Three Anchored VWAPs: Plot VWAPs anchored to the start of a session, week, or month, with customizable source, offset, and band multipliers. AVWAP 1 (session-anchored, fuchsia) is enabled by default.
- Three Rolling VWAPs: Plot VWAPs calculated over fixed periods (default: 20, 50, 100), with customizable source, offset, and band multipliers.
- VWAP Bands: Optional upper and lower bands for each VWAP, based on standard deviation with user-defined multipliers.
- VWAP Percentage Difference Labels: Display the percentage difference between the current price and each VWAP, shown only for visible VWAPs. Enabled by default to show the AVWAP 1 label.
- Customizable Colors: Each VWAP has a user-defined color via input settings, with labels matching the VWAP line colors (e.g., AVWAP 1 defaults to fuchsia).
Flexible Display Options: Toggle individual EMAs, VWAPs, bands, and labels on or off to reduce chart clutter.
Settings
The indicator is organized into intuitive setting groups:
EMA Settings
Show EMA 1–8 : Toggle each EMA on or off (default: all enabled).
EMA 1–8 Length : Set the period for each EMA (default: 3, 9, 19, 38, 50, 65, 100, 200).
Show EMA % Difference Labels : Enable/disable percentage difference labels for all EMAs (default: enabled).
EMA Label Font Size (8–20) : Adjust the font size for EMA labels (default: 10, mapped to “tiny”).
Anchored VWAP 1–3 Settings
Show AVWAP 1–3 : Toggle each anchored VWAP on or off (default: AVWAP 1 enabled, others disabled).
AVWAP 1–3 Color : Set the color for each VWAP line and its label (default: fuchsia for AVWAP 1, purple for AVWAP 2, teal for AVWAP 3).
AVWAP 1–3 Anchor : Choose the anchor period (“Session,” “Week,” “Month”; default: Session for AVWAP 1, Week for AVWAP 2, Month for AVWAP 3).
AVWAP 1–3 Source : Select the price source (default: hlc3).
AVWAP 1–3 Offset : Set the horizontal offset for the VWAP line (default: 0).
Show AVWAP 1–3 Bands : Toggle upper/lower bands (default: disabled).
AVWAP 1–3 Band Multiplier : Adjust the standard deviation multiplier for bands (default: 1.0).
Rolling VWAP 1–3 Settings
Show RVWAP 1–3 : Toggle each rolling VWAP on or off (default: disabled).
RVWAP 1–3 Color : Set the color for each VWAP line and its label (default: navy for RVWAP 1, maroon for RVWAP 2, fuchsia for RVWAP 3).
RVWAP 1–3 Period Length : Set the period for the rolling VWAP (default: 20, 50, 100).
RVWAP 1–3 Source : Select the price source (default: hlc3).
RVWAP 1–3 Offset : Set the horizontal offset (default: 0).
Show RVWAP 1–3 Bands : Toggle upper/lower bands (default: disabled).
RVWAP 1–3 Band Multiplier : Adjust the standard deviation multiplier for bands (default: 1.0).
VWAP Label Settings
Show VWAP % Difference Labels : Enable/disable percentage difference labels for all VWAPs (default: enabled, showing AVWAP 1 label).
VWAP Label Font Size (8–20) : Adjust the font size for VWAP labels (default: 10, mapped to “tiny”).
How It Works
EMAs : Calculated using ta.ema(close, length) for each user-defined period. Percentage differences are computed as ((close - ema) / close) * 100 and displayed as labels for visible EMAs when show_ema_labels is enabled.
Anchored VWAPs : Calculated using ta.vwap(source, anchor, 1), where the anchor is determined by the selected timeframe (Session, Week, or Month). Bands are computed using the standard deviation from ta.vwap.
Rolling VWAPs : Calculated using ta.vwap(source, length), with bands based on ta.stdev(source, length).
Labels : Updated on each new bar (ta.barssince(ta.change(time) != 0) == 0) to show percentage differences. Labels are only displayed for visible EMAs/VWAPs to avoid clutter.
Color Matching: VWAP labels use the same color as their corresponding VWAP lines, set via input settings (e.g., avwap1_color for AVWAP 1).
Example Use Cases
- Trend Following: Use longer EMAs (e.g., 100, 200) to identify trends and shorter EMAs (e.g., 3, 9) for entry/exit signals.
- Mean Reversion: Monitor percentage difference labels to spot overbought/oversold conditions relative to EMAs or VWAPs.
- VWAP Trading: Use the default session-anchored AVWAP 1 for intraday trading, adding weekly/monthly VWAPs or rolling VWAPs for broader context.
- Intraday Analysis: Leverage the session-anchored AVWAP 1 (enabled by default) for day trading, with bands as support/resistance zones.
BTC/USD 3-Min Binary Prediction [v7.2 EN]BTC/USD 3-Minute Binary Prediction Indicator v7.2 - Complete Guide
Overview
This is an advanced technical analysis indicator designed for Bitcoin/USD binary options trading with 3-minute expiration times. The system aims for an 83% win rate by combining multiple analysis layers and pattern recognition.
How It Works
Core Prediction Logic
- Timeframe: Predicts whether BTC price will be ±$25 higher (HIGH) or lower (LOW) after 3 minutes
- Entry Signals: Generates HIGH/LOW signals when confidence exceeds threshold (default 75%)
- Verification: Automatically tracks and displays win/loss statistics in real-time
5-Layer Filter System
The indicator uses a sophisticated scoring system (0-100 points):
1. Trend Filter (25 points) - Analyzes EMA alignments and price momentum
2. Leading Indicators (25 points) - RSI and MACD divergence analysis
3. Volume Confirmation (20 points) - Detects unusual volume patterns
4. Support/Resistance (15 points) - Identifies key price levels
5. Momentum Alignment (15 points) - Measures acceleration and deceleration
Pattern Recognition
Automatically detects and visualizes:
- Double Tops/Bottoms - Reversal patterns
- Triangles - Ascending, descending, symmetrical
- Channels - Trending price channels
- Candlestick Patterns - Engulfing, hammer, hanging man
Multi-Timeframe Analysis
- Uses 1-minute and 5-minute data for confirmation
- Aligns multiple timeframes for higher probability trades
- Monitors trend consistency across timeframes
Key Features
Display Panels
1. Statistics Panel (Top Right)
- Overall win rate percentage
- Hourly performance (wins/losses)
- Daily performance
- Current system status
2. Analysis Panel (Left Side)
- Market trend analysis
- RSI status (overbought/oversold)
- Volume conditions
- Filter scores for each component
- Final HIGH/LOW/WAIT decision
Visual Signals
- Green Triangle (↑) = HIGH prediction
- Red Triangle (↓) = LOW prediction
- Yellow Background = Entry opportunity
- Blue Background = Waiting for result
Configuration Options
Basic Settings
- Range Width: Target price movement (default $50 = ±$25)
- Min Confidence: Minimum confidence to enter (default 75%)
- Max Daily Trades: Risk management limit (default 5)
Filters (Can be toggled on/off)
- Trend Filter
- Volume Confirmation
- Support/Resistance Filter
- Momentum Alignment
Display Options
- Show/hide signals, statistics, analysis
- Minimal Mode for cleaner charts
- EMA line visibility
Important Risk Warnings
Binary Options Trading Risks:
1. High Risk Product - Binary options are extremely risky and banned in many countries
2. Not Investment Advice - This tool is for educational/analytical purposes only
3. No Guaranteed Returns - Past performance doesn't predict future results
4. Capital at Risk - You can lose your entire investment in seconds
Technical Limitations:
- Requires stable internet connection
- Performance varies with market conditions
- High volatility can reduce accuracy
- Not suitable for news events or low liquidity periods
Best Practices
1. Paper Trade First - Test thoroughly on demo accounts
2. Risk Management - Never risk more than 1-2% per trade
3. Market Conditions - Works best in normal volatility conditions
4. Avoid Major Events - Don't trade during major news releases
5. Monitor Performance - Track your actual results vs displayed statistics
Setup Instructions
1. Add to TradingView chart (BTC/USD preferred)
2. Use 30-second or 1-minute chart timeframe
3. Adjust settings based on your risk tolerance
4. Monitor F-Score (should be >65 for entries)
5. Wait for clear HIGH/LOW signals with high confidence
Alert Configuration
The indicator provides three alert types:
- HIGH Signal alerts
- LOW Signal alerts
- General entry opportunity alerts
Legal Disclaimer
Binary options trading may not be legal in your jurisdiction. Many countries including the USA, Canada, and EU nations have restrictions or outright bans on binary options. Always check local regulations and consult with financial advisors before trading.
Remember: This is a technical analysis tool, not a money-printing machine. Successful trading requires discipline, risk management, and continuous learning. The displayed statistics are historical and don't guarantee future performance.
Volatility % Bands (O→C)Volatility % Bands (O→C) is an indicator designed to visualize the percentage change from Open to Close of each candle, providing a clear view of short-term momentum and volatility.
**Histogram**: Displays bar-by-bar % change (Close vs Open). Green bars indicate positive changes, while red bars indicate negative ones, making momentum shifts easy to identify.
**Moving Average Line**: Plots the Simple Moving Average (SMA) of the absolute % change, helping traders track the average volatility over a chosen period.
**Background Bands**: Based on the user-defined Level Step, ±1 to ±5 zones are highlighted as shaded bands, allowing quick recognition of whether volatility is low, moderate, or extreme.
**Label**: Shows the latest candle’s % change and the current SMA value as a floating label on the right, making it convenient for real-time monitoring.
This tool can be useful for volatility breakout strategies, day trading, and short-term momentum analysis.
Ranges by TraderHaroThis indicator highlights a custom price range for a selected date/time period on your chart. It draws key levels (0.00, 0.25, 0.50, 0.75, 1.00) within the range, visually marking the Premium Zone (upper range) and Discount Zone (lower range).
Features:
- Define a specific date/time range for the analysis.
- Optional fill between top and bottom levels with customizable color and transparency.
- Shows mid-levels (0.25, 0.50, 0.75) for additional guidance.
- Lines and fill can be extended to the right side of the chart.
- Labels for levels can be displayed or hidden.
Use Case:
Quickly identify where price is trading relative to a defined range, visualize potential zones of premium (resistance) and discount (support), and make better-informed trading decisions.
Benchmark Relative Performance BRPBenchmark Relative Performance (BRP) is a comprehensive technical analysis tool that compares any stock's performance against a chosen benchmark (QQQ, SPY, IWM, etc.) to identify outperformance and underperformance patterns.
Key Features:
Dual-line visualization: Shows both ticker and relative strength performance
Dynamic color coding: 5-level color system indicating performance strength
Customizable benchmark: Choose from any ticker via TradingView's symbol picker
Volume weighting: Optional volume analysis for stronger signal confirmation
Performance zones: Visual thresholds for strong/moderate performance levels
Compact info table: Real-time performance status and values
What It Shows:
Benchmark Performance Line (Blue): Shows your chosen benchmark's percentage performance
Relative Strength Line (Color-coded): Shows how much the ticker outperforms/underperforms
Fill Area: Visual gap between ticker and benchmark performance
Performance Zones: Dotted lines marking significant performance thresholds
Color System:
Green: Strong outperformance (above custom threshold)
Lime: Standard outperformance
Yellow: Neutral/Equal performance
Orange: Standard underperformance
Red: Strong underperformance (below custom threshold)
Best Used For:
Stock selection and rotation strategies
Sector/ETF relative strength analysis
Identifying momentum shifts vs benchmarks
Portfolio performance evaluation
Market timing based on relative performance
Settings:
Customizable lookback period (default: 20)
Adjustable strong performance threshold (default: 5%)
Optional volume weighting factor
Full table customization (position, colors, fonts)
Performance display (percentage or decimal)
Perfect for traders and investors who want to identify stocks showing relative strength or weakness compared to major market benchmarks.
BTC Power-Law Decay Channel Oscillator (0–100)🟠 BTC Power-Law Decay Channel Oscillator (0–100)
This indicator calculates Bitcoin’s position inside its long-term power-law decay channel and normalizes it into an easy-to-read 0–100 oscillator.
🔎 Concept
Bitcoin’s long-term price trajectory can be modeled by a log-log power-law channel.
A baseline is fitted, then an upper band (excess/euphoria) and a lower band (capitulation/fear).
The oscillator shows where the current price sits between those bands:
0 = near the lower band (historical bottoms)
100 = near the upper band (historical tops)
📊 How to Read
Oscillator > 80 → euphoric excess, often cycle tops
Oscillator < 20 → capitulation, often cycle bottoms
Works best on weekly or bi-weekly timeframes.
⚙️ Adjustable Parameters
Anchor date: starting point for the power-law fit (default: 2011).
Smoothing days: moving average applied to log-price (default: 365 days).
Upper / Lower multipliers: scale the bands to align with historical highs and lows.
✅ Best Use
Combine with other cycle signals (dominance ratios, macro indicators, sentiment).
Designed for long-term cycle analysis, not intraday trading.
PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
" Date: " + date_str + " " + time_str +
" Trade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
" Rank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
" Percentile: " + str.tostring(percentile, "#.#") + "%" +
" Magnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
Machine Learning Z-Score Buy and Sell [SS]Hey everyone,
Releasing this Z-Score based buy and sell indicator.
What it does
This indicator:
Uses Z-score and trend to identify potential buy and sell areas.
Signals those buy and sell areas and provides a target price based on the mean.
Plots the target price for buy and sell signals as a red line (for sell signals) or green line (for buy signals).
Has some "machine learning" aspects, namely, it is able to auto select its lookback length based on its analysis of the trend using Pienscript's trend correlation function iterated over multiple lengths, in order for the indicator to identify:
a) The strongest trend; and
b) The correct target price
What is Z-Score
Z-Score is a measure of the mean. Thus, this is a mean reverting type strategy, as it uses z-score to determine price's distance from the mean (or a Z-Score of 0) and then it looks at historic deviations from the mean to signal the buy and sell signals (i.e. how far has price traditionally drifted from the mean before reverting).
Z-Score is a powerful tool in this sense, and if you folow my other indicators, you will know how much I love Z-score!
How to use the indicator
If you want to use the full Machine Learning capabilities of the indicator, its best to just leave all default settings. These default settings will automatically adjust the mean target price and buy and sell signals to align with the current price action.
If you want to be more aggressive in your
Target Price; and
Signals
Then you can opt to manually input a lookback length and mean reversion standard deviation. However, I generally suggest to avoid this as you are then making your own determination of trend by qualitative assessment. It can work, but its just not suggested.
In the input menu, you will see the option to "Manually select lookback" thus over-riding the auto-determination of trend and targets.
You will also see "manual pullback" enabler and "Pullback Standard Deviation". You can set your pullback standard deviation if you want to be more aggressive. The indicator will naturally shift to conservative target prices based on a neutral mean. However, if you want to increase the aggressiveness of the target price, you can increase or decrease the pullback standard deviation.
General Tips about Manually Adjusting Pullback Target
Here are some tips if you want to manually adjust the pullback targets:
The pullback target needs to be in a standard deviation value, this can be anywhere from 0 to 4 or 0 to -4 (you can theoretically go higher but its not really realistic). You can also do decimals, so 1.5 or 1.25 etc.
To determine whether you should be doing negative or positive standard deviation, you should determine the trend. If it is a downtrend and you are looking to short the rips, you will want to select a negative number, like -1.
If it is an uptrend and you want to buy the dips, you should be selecting a positive number, like 1 or 1.5.
Again, I do suggest leaving the indicator to decide for itself, but the options are there for those who wish.
Overall strategy
This is a mean reverting strategy. So if you are a mean reversion trader, this may be of particular interest to you.
Optional
Optionally, you can have the indicator plot the target prices or not, simply toggle this functionality off or on in the settings menu.
Concluding remarks
That is the indicator in a nutshell!
I hope you enjoy it and find it helpful.
Feel free to check out my other Z-Score based indicators if you find this interesting or want to learn more about the power of Z-Score in trading!
Thanks all and safe trades!
Support and Resistance levels from Options DataINTRODUCTION
This script is designed to visualize key support and resistance levels derived from options data on TradingView charts. It overlays lines, labels, and boxes to highlight levels such as Put Walls (gamma support), Call Walls (gamma resistance), Gamma Flip points, Vanna levels, and more.
These levels are intended to help traders identify potential areas of price magnetism, reversal, or breakout based on options market dynamics. All calculations and visualizations are based on user-provided data pasted into the input field, as Pine Script cannot directly fetch external options data due to platform limitations (explained below).
For convenience, my website allows users to interact with a bot that will generate the string for up to 30 tickers at once getting nearly real-time data on demand (data is cached for 15min). With the output string pasted into this indicator, it's a bliss to shuffle through your portfolio and see those levels for each ticker.
The script is open-source under TradingView's terms, allowing users to study, modify, and improve it. It draws inspiration from common options-derived metrics like gamma exposure and vanna, which are widely discussed in financial literature. No external code is copied without rights; all logic is original or based on standard mathematical formulas.
How the Options Levels Are Calculated
The levels displayed by this script are not computed within Pine Script itself—instead, they rely on pre-calculated values provided by the user (via a pasted data string). These values are derived from options chain data fetched from financial APIs (e.g., using libraries like yfinance in Python). Here's a step-by-step overview of how these levels are generally calculated externally before being input into the script:
Fetching Options Data:
Historical and current options chain data for a ticker (e.g., strikes, open interest, volume, implied volatility, expirations) is retrieved for near-term expirations (e.g., up to 90 days).
Current stock price is obtained from recent history.
Gamma Support (Put Wall) and Resistance (Call Wall):
Gamma Calculation: For each option, gamma (the rate of change of delta) is computed using the Black-Scholes formula:
gamma = N'(d1) / (S * sigma * sqrt(T))
where S is the stock price, K is the strike, T is time to expiration (in years), sigma is implied volatility, r is the risk-free rate (e.g., 0.0445), and N'(d1) is the normal probability density function.
Weighted gamma is multiplied by open interest and aggregated by strike.
The Put Wall is the strike below the current price with the highest weighted gamma from puts (acting as support).
The Call Wall is the strike above the current price with the highest weighted gamma from calls (acting as resistance).
Short-term versions focus on strikes closer to the money (e.g., within 10-15% of the price).
Gamma Flip Level:
Net dealer gamma exposure (GEX) is calculated across all strikes:
GEX = sum (gamma * OI * 100 * S^2 * sign * decay)
where sign is +1 for calls/-1 for puts, and decay is 1 / sqrt(T).
The flip point is the price where net GEX changes sign (from positive to negative or vice versa), interpolated between strikes.
Vanna Levels:
Vanna (sensitivity of delta to volatility) is calculated:
vanna = -N'(d1) * d2 / sigma
where d2 = d1 - sigma * sqrt(T).
Weighted by open interest, the highest positive and negative vanna strikes are identified.
Other Levels:
S1/R1: Significant strikes with high combined open interest and volume (80% OI + 20% volume), below/above price for support/resistance.
Implied Move: ATM implied volatility scaled by S * sigma * sqrt(d/365) (e.g., for 7 days).
Call/Put Ratio: Total call contracts divided by put contracts (OI + volume).
IV Percentage: Average ATM implied volatility.
Options Activity Level: Average contracts per unique strike, binned into levels (0-4).
Stop Loss: Dynamically set below the lowest support (e.g., Put Wall, Gamma Flip), adjusted by IV (tighter in low IV).
Fib Target: 1.618 extension from Put Wall to Call Wall range.
Previous day levels are stored for comparison (e.g., to detect Call Wall movement >2.5% for alerts).
Effect as Support and Resistance in Technical Trading
Options levels like gamma walls influence price action due to market maker hedging:
Put Wall (Gamma Support): High put gamma below price creates a "magnet" effect—market makers buy stock as price falls, providing support. Traders might look for bounces here as entry points for longs.
Call Wall (Gamma Resistance): High call gamma above price leads to selling pressure from hedging, acting as resistance. Rejections here could signal trims, sells or even shorts.
Gamma Flip: Where gamma exposure flips sign, often a volatility pivot—crossing it can accelerate moves (bullish above, bearish below).
Vanna Levels: Positive/negative vanna indicate volatility sensitivity; crosses may signal regime shifts.
Implied Move: Shows expected range; prices outside suggest overextension.
S1/R1 and Fib Target: Volume/OI clusters act as classic S/R; Fib extensions project upside targets post-breakout.
In trading, these are not guarantees—combine with TA (e.g., volume, trends). High activity levels imply stronger effects; low CP ratio suggests bearish sentiment. Alerts trigger on proximities/crosses for awareness, not advice.
Limitations of the TradingView Platform for Data Pulling
TradingView's Pine Script is sandboxed for security and performance:
No direct internet access or API calls (e.g., can't fetch yfinance data in-script).
Limited to chart data/symbol info; no real-time options chains.
Inputs are static per load; updates require manual pasting.
Caching isn't persistent across sessions.
This prevents dynamic data pulling, ensuring scripts remain lightweight but requiring external tools for fresh data.
Creative Solution for On-Demand Data Pulling
To overcome these limitations, users can use external tools or scripts (e.g., Python-based) to fetch and compute levels on demand. The tool processes tickers, generates a formatted string (e.g., "TICKER:level1,level2,...;TIMESTAMP:unix;"), and users paste it into the script's input. This keeps data fresh without violating platform rules, as computation happens off-platform. For example, run a local script to query APIs and output the string—adaptable for any ticker.
Script Functionality Breakdown
Inputs: Custom data string (parsed for levels/timestamp); toggles for short-term/previous/Vanna/stop loss; style options (colors, transparency).
Parsing: Extracts levels for the chart symbol; gets timestamp for "updated ago" display.
Drawing: Lines/labels for levels; boxes for gamma zones/implied move; clears old elements on updates.
Info Panel: Top-right summary with metrics (CP ratio, IV, distances, activity); emojis for quick status.
Alerts: Conditions for proximities, crosses, bounces (e.g., 0.5% bounce from Put Wall).
Performance: Uses vars for persistence; efficient for real-time.
This script is educational—test thoroughly. Not financial advice; past performance isn't indicative of future results. Feedback welcome via TradingView comments.
Draw Trend LinesSometimes the simplest indicators help traders make better decisions. This indicator draws simple trend lines, the same lines you would draw manually.
To trade with an edge, traders need to interpret the recent price action, whether it's noisy or choppy, or it's trending. Trend Lines will help traders with that interpretation.
The lines drawn are:
1. lower tops
2. higher bottoms
Because trends are defined as higher lows, or lower highs.
When you see "Wedges", formed by prices chopping between top and bottom trend lines, that's noisy environment not to be traded. When you learn to "stop yourself", you already have an edge.
Often when you see a trend, it's still not too late. Trend will continue until it doesn't. But the caveat is a very steep trend is unlikely to continue, because buying volume is extremely unbalanced to cause the steep trend, and that volume will run out of energy. (Same on the sell side of course)
Trends can reverse, and when price action breaks the trend line, Breakout/Breakdown traders can take this as an entry signal.
Enjoy, and good trading!
Volume Profile + Pivot Levels [ChartPrime]⯁ OVERVIEW
Volume Profile + Pivot Levels combines a rolling volume profile with price pivots to surface the most meaningful levels in your selected lookback window. It builds a left-side profile from traded volume, highlights the session’s Point of Control (PoC) , and then filters pivot highs/lows so only those aligned with significant profile volume are promoted to chart levels. Each promoted level extends forward until price retests it—so your chart stays focused on levels that actually matter.
⯁ KEY FEATURES
Rolling Volume Profile (Period & Resolution)
Calculates a profile over the last Period bars (default 200). The profile is discretized into Volume Profile Resolution bins (default 50) between the highest high and lowest low inside the window. Each bin accumulates traded volume and is drawn as a smooth left-side polyline for compact, lightweight rendering.
HL = array.new()
// collect highs/lows over 'start' bars to define profile range
for i = 0 to start - 1
HL.push(high ), HL.push(low )
H = HL.max(), L = HL.min()
bin_size = (H - L) / bins
// accumulate per-bin volume
for i = 0 to bins - 1
for j = 0 to start - 1
if close >= (L + bin_sizei) - bin_size and close < (L + bin_size*(i+1)) + bin_size
Bins += volume
Delta-Aware Coloring
The script tracks up-minus-down volume across all period to compute a net Delta . The profile, PoC line, and PoC label adopt a teal tone when net positive, and maroon when net negative—an immediate read on buyer/seller dominance inside the window.
Point of Control (PoC) + Volume Label
Automatically marks the highest-volume bin as the PoC . A horizontal PoC line extends to the last bar, and a label shows the absolute volume at the PoC. Toggle visibility via PoC input.
Pivot Detection with Volume Filter
Identifies raw pivots using Length (default 10) on both sides of the bar. Each candidate pivot is then validated against the profile: only pivots that land within their bin and meet or exceed the Filter % threshold (percentage of PoC volume) are promoted to chart levels. This removes weak, low-participation pivots.
// pivot promotion when volume% >= pivotFilter
if abs(mid - p.value) <= bin_size and volPercent >= pivotFilter
// draw labeled pivot level
line.new(p.index - pivotLength, p.value, p.index + pivotLength, p.value, width = 2)
Forward-Extending, Self-Stopping Levels
Promoted pivot levels extend forward as dotted rays. As soon as price intersects a level (high/low straddles it), that level stops extending—so your chart doesn’t clutter with stale zones.
Concise Level Labels (Volume + %)
Each promoted pivot prints a compact label at the pivot bar with its bin’s absolute volume and percentage of PoC volume (ordering flips for highs vs. lows for quick read).
Lightweight Visuals
The volume profile is rendered as a smooth polyline rather than dozens of boxes, keeping charts responsive even at higher resolutions.
⯁ SETTINGS
Volume Profile → Period : Lookback window used to compute the profile (max 500).
Volume Profile → Resolution : Number of bins; higher = finer structure.
Volume Profile → PoC : Toggle PoC line and volume label.
Pivots → Display : Show/hide volume-validated pivot levels.
Pivots → Length : Pivot detection left/right bars.
Pivots → Filter % 0–100 : Minimum bin strength (as % of PoC) required to promote a pivot level.
⯁ USAGE
Read PoC direction/color for a quick net-flow bias within your window.
Prioritize promoted pivot levels —they’re backed by meaningful participation.
Watch for first retests of promoted levels; the line will stop extending once tested.
Adjust Period / Resolution to match your timeframe (scalps → higher resolution, shorter period; swings → lower resolution, longer period).
Tighten or loosen Filter % to control how selective the level promotion is.
⯁ WHY IT’S UNIQUE
Instead of plotting every pivot or every profile bar, this tool cross-checks pivots against the profile’s internal volume weighting . You only see levels where price structure and liquidity overlap—clean, data-driven levels that self-retire after interaction, so you can focus on what the market actually defends.
Pivot Points mura visionWhat it is
A clean, single-set pivot overlay that lets you choose the pivot type (Traditional/Fibonacci), the anchor timeframe (Daily/Weekly/Monthly/Quarterly, or Auto), and fully customize colors, line width/style , and labels . The script never draws duplicate sets—exactly one pivot pack is displayed for the chosen (or auto-detected) anchor.
How it works
Pivots are computed with ta.pivot_point_levels() for the selected anchor timeframe .
The script supports the standard 7 levels: P, R1/S1, R2/S2, R3/S3 .
Lines span exactly one anchor period forward from the current bar time.
Label suffix shows the anchor source: D (Daily), W (Weekly), M (Monthly), Q (Quarterly).
Auto-anchor logic
Intraday ≤ 15 min → Daily pivots (D)
Intraday 20–120 min → Weekly pivots (W)
Intraday > 120 min (3–4 h) → Monthly pivots (M)
Daily and above → Quarterly pivots (Q)
This keeps the chart readable while matching the most common trader expectations across timeframes.
Inputs
Pivot Type — Traditional or Fibonacci.
Pivots Timeframe — Auto, Daily (1D), Weekly (1W), Monthly (1M), Quarterly (3M).
Line Width / Line Style — width 1–10; style Solid, Dashed, or Dotted.
Show Labels / Show Prices — toggle level tags and price values.
Colors — user-selectable colors for P, R*, S* .
How to use
Pick a symbol/timeframe.
Leave Pivots Timeframe = Auto to let the script choose; or set a fixed anchor if you prefer.
Toggle labels and prices to taste; adjust line style/width and colors for your theme.
Read the market like a map:
P often acts as a mean/rotation point.
R1/S1 are common first reaction zones; R2/S2 and R3/S3 mark stronger extensions.
Confluence with S/R, trendlines, session highs/lows, or volume nodes improves context.
Good practices
Use Daily pivots for intraday scalps (≤15m).
Use Weekly/Monthly for swing bias on 1–4 h.
Use Quarterly when analyzing on Daily and higher to frame larger cycles.
Combine with trend filters (e.g., EMA/KAMA 233) or volatility tools for entries and risk.
Notes & limitations
The script shows one pivot pack at a time by design (prevents clutter and duplicates).
Historical values follow TradingView’s standard pivot definitions; results can vary across assets/exchanges.
No alerts are included (levels are static within the anchor period).
PulseMA Oscillator Normalized v2█ OVERVIEW
PulseMA Oscillator Normalized v2 is a technical indicator designed for the TradingView platform, assisting traders in identifying potential trend reversal points based on price dynamics derived from moving averages. The indicator is normalized for easier interpretation across various market conditions, and its visual presentation with gradients and signals facilitates quick decision-making.
█ CONCEPTS
The core idea of the indicator is to analyze trend dynamics by calculating an oscillator based on a moving average (EMA), which is then normalized and smoothed. It provides insights into trend strength, overbought/oversold levels, and reversal signals, enhanced by gradient visualizations.
Why use it?
Identifying reversal points: The indicator detects overbought and oversold levels, generating buy/sell signals at their crossovers.
Price dynamics analysis: Based on moving averages, it measures how long the price stays above or below the EMA, incorporating trend slope.
Visual clarity: Gradients, fills, and colored lines enable quick chart analysis.
Flexibility: Configurable parameters, such as moving average lengths or normalization period, allow adaptation to various strategies and markets.
How it works?
Trend detection: Calculates a base exponential moving average (EMA with PulseMA Length) and measures how long the price stays above or below it, multiplied by the slope for the oscillator.
Normalization: The oscillator is normalized based on the minimum and maximum values over a lookback period (default 150 bars), scaling it to a range from -100 to 100: (oscillator - min) / (max - min) * 200 - 100. This ensures values are comparable across different instruments and timeframes.
Smoothing: The main line (PulseMA) is the normalized oscillator (oscillatorNorm). The PulseMA MA line is a smoothed version of PulseMA, calculated using an SMA with the PulseMA MA length. As PulseMA MA is smoothed, it reacts more slowly and can be used as a noise filter.
Signals: Generates buy signals when crossing the oversold level upward and sell signals when crossing the overbought level downward. Signals are stronger when PulseMA MA is in the overbought or oversold zone (exceeding the respective thresholds for PulseMA MA).
Visualization: Draws lines with gradients for PulseMA and PulseMA MA, levels with gradients, gradient fill to the zero line, and signals as triangles.
Alerts: Built-in alerts for buy and sell signals.
Settings and customization
PulseMA Length: Length of the base EMA (default 20).
PulseMA MA: Length of the SMA for smoothing PulseMA MA (default 20).
Normalization Lookback Period: Normalization period (default 150, minimum 10).
Overbought/Oversold Levels: Levels for the main line (default 100/-100) and thresholds for PulseMA MA, indicating zones where PulseMA MA exceeds set values (default 50/-50).
Colors and gradients: Customize colors for lines, gradients, and levels; options to enable/disable gradients and fills.
Visualizations: Show PulseMA MA, gradients for overbought/oversold/zero levels, and fills.
█ OTHER SECTIONS
Usage examples
Trend analysis: Observe PulseMA above 0 for an uptrend or below 0 for a downtrend. Use different values for PulseMA Length and PulseMA MA to gain a clearer trend picture. PulseMA MA, being smoothed, reacts more slowly and can serve as a noise filter to confirm trend direction.
Reversal signals: Look for buy triangles when PulseMA crosses the oversold level, especially when PulseMA MA is in the oversold zone. Similarly, look for sell triangles when crossing the overbought level with PulseMA MA in the overbought zone. Such confirmation increases signal reliability.
Customization: Test different values for PulseMA Length and PulseMA MA on a given instrument and timeframe to minimize false signals and tailor the indicator to market specifics.
Notes for users
Combine with other tools, such as support/resistance levels or other oscillators, for greater accuracy.
Test different settings for PulseMA Length and PulseMA MA on the chosen instrument and timeframe to find optimal values.
Wick Pressure Zones [BigBeluga]
The Wick Pressure Zones indicator highlights areas where extreme wick activity occurred, signaling strong buy or sell pressure. By measuring unusually long upper or lower wicks and mapping them into gradient volume zones , the tool helps traders identify levels where liquidity was absorbed, leaving behind footprints of supply and demand imbalances. These zones often act as support, resistance, or liquidity sweep magnets .
🔵 CONCEPTS
Extreme Wicks : Large upper or lower shadows indicate aggressive rejection — upper wicks suggest selling pressure, lower wicks suggest buying pressure.
Volumatic Gradient Zones : From each detected wick, the indicator projects a layered gradient zone, proportional to the wick’s size, showing where most pressure occurred.
Liquidity Footprints : These zones mark levels where significant buy/sell volume was executed, often becoming reaction points on future retests.
Automatic Expiration : Zones persist until price decisively trades through them, after which they are cleared to keep the chart clean.
🔵 FEATURES
Automatic Wick Detection : Identifies extreme upper and lower wick events using percentile filtering and Realative Strength Index.
Gradient Zone Visualization : Builds a 10-layer zone from the wick top/bottom, shading intensity according to pressure strength.
Volume Labels : Each zone is annotated with the bar’s volume at the origin point for added context.
Dynamic Zone Extension : Zones extend to the right as long as they remain relevant; once price closes through them, they are removed.
Support & Resistance Mapping : Upper wick zones (red) behave like supply/resistance, lower wick zones (green) like demand/support.
Clutter Control : Limits the number of active zones (default 10) to keep charts responsive.
Background Highlighting : Optional background shading when new wick zones appear (red for sell, green for buy).
🔵 HOW TO USE
Look for Upper Wick Zones (red) : Indicate strong selling pressure; watch for resistance, reversals, or liquidity sweeps above.
Look for Lower Wick Zones (green) : Indicate strong buying pressure; watch for support or liquidity sweeps below.
Trade Retests : When price returns to a zone, expect a reaction (bounce or rejection) due to leftover liquidity.
Combine with Context : Align wick pressure zones with HTF support/resistance, order blocks, or volume profile for stronger signals.
Use Volume Labels : High-volume wicks indicate more significant liquidity events, making the zone more likely to act as a strong reaction point.
🔵 CONCLUSION
The Wick Pressure Zones is a powerful way to visualize hidden liquidity and aggressive rejections. By mapping extreme wick events into dynamic, volume-annotated zones, it shows traders where the market absorbed heavy buy/sell pressure. These levels frequently act as magnets or turning points, making them valuable for timing entries, stop placement, or fade strategies.
Commodity Channel Index DualThe CCI Dual is a custom TradingView indicator built in Pine Script v5, designed to help traders identify potential buy and sell signals using two Commodity Channel Index (CCI) oscillators. It combines a shorter-period CCI (default: 14) for quick momentum detection with a longer-period CCI (default: 50) for confirmation, focusing on mean-reversion opportunities in overbought or oversold conditions.
This setup is particularly suited for volatile markets like cryptocurrencies on higher timeframes (e.g., 3-day charts), where it highlights reversals by requiring both CCIs to cross out of extreme zones within a short window (default: 3 bars).
The indicator plots the CCIs, customizable bands (inner: 100, OB/OS: 175, outer: 200), dynamic fills for visual emphasis, background highlights for signals, and alert conditions for notifications.
How It Works
The indicator calculates two CCIs based on user-defined lengths and source (default: close price):
CCI Calculation: CCI measures price deviation from its average, using the formula: CCI = (Typical Price - Simple Moving Average) / (0.015 * Mean Deviation). The short CCI reacts faster to price changes, while the long CCI provides smoother, trend-aware confirmation.
Overbought/Oversold Levels: Customizable thresholds define extremes (Overbought at +175, Oversold at -175 by default). Bands are plotted at inner (±100), mid (±175 dashed), and outer (±200) levels, with gray fills for the outer zones.
Dynamic Fills: The longer CCI is used to shade areas beyond OB/OS levels in red (overbought) or green (oversold) for quick visual cues.
Signals:
Buy Signal: Triggers when both CCIs cross above the Oversold level (-175) within the signal window (3 bars). This suggests a potential upward reversal from an oversold state.
Sell Signal: Triggers when both cross below the Overbought level (+175) within the window, indicating a possible downward reversal.
Visuals and Alerts: Buy signals highlight the background green, sells red. Separate alertconditions allow setting TradingView alerts for buys or sells independently.
Customization: Adjust lengths, levels, and window via inputs to fit your timeframe or asset—e.g., higher OB/OS for crypto volatility.
This logic reduces noise by requiring dual confirmation, but like all oscillators, it can produce false signals in strong trends where prices stay extended.
To mitigate false signals (e.g., in trending markets), layer the CCI Dual with MACD (default: 12,26,9) and RSI (default: 14) for multi-indicator confirmation:
With MACD: Only take CCI buys if the MACD line is above the signal line (or histogram positive), confirming bullish momentum. For sells, require MACD bearish crossover. This filters counter-trend signals by aligning with trend strength—e.g., ignore CCI sells if MACD shows upward momentum.
With RSI: Confirm CCI oversold buys only if RSI is below 30 and rising (or shows bullish divergence). For overbought sells, RSI above 70 and falling. This adds overextension validation, reducing whipsaws in crypto trends.
I made this customizable for you to find what works best for your asset you are trading. I trade the 6 hour and 3 day timeframe mainly on major cryptocurrency pairs. I hope you enjoy this script and it serves you well.
Peak Reversal v3# Peak Reversal v3
## Summary
Peak Reversal v3 adds new configurability, clearer visuals, and a faster trader workflow. The release introduces a new Squeeze Detector , expanded Keltner Channels , and streamlined Momentum signals , with no repaints and improved performance. The menus have been reorganized and simplified. Color swatches have been added for better customization. All other colors will be derived from these swatches.
## Highlights
New Squeeze Detector to mark low-volatility periods and prepare for breakouts.
New: Bands are now fully configurable with independent MA length, ATR length, and multipliers.
Five moving average bases for bands: EMA (from v2), SMA, RMA, VMA, HMA.
Simplified color system: three swatches drive candles, on-chart marks, and band fill.
Reorganized menu with focused sections and tooltips for each parameter making the entire trader experience more intuitive.
No repaints and faster performance across calculations.
## Overview
Configuration : Pick from three color swatches and apply them to candles, plotted characters, and band fill for consistent chart context. Use the reorganized menu to reach Keltner settings, momentum signals, and squeeze detection without extra clicks; tooltips clarify each input.
Bands and averages: Choose the band basis from EMA, SMA, RMA, VMA, or HMA to match your strategy. Configure two bands independently by setting MA length, ATR length, and band multipliers for the inner and outer envelopes.
Signals : Select the band responsible for momentum signals. Choose wick or close as the price source for entries and exits. Control the window for extreme momentum with “Max Momentum Bars,” a setting now exposed in v3 for direct tuning.
Squeeze detection : The Squeeze Detector normalizes band width and uses percentile ranking to highlight volatility compression. When the market falls below a user-defined threshold, the indicator colors the region with a gradient to signal potential expansion.
## Details about major features and changes
### New
Squeeze Detector to highlight low-volatility conditions.
Five MA bases for bands: EMA, SMA, RMA, VMA, HMA.
“Max Momentum Bars” to cap the bars used for extreme momentum.
### Keltner channel improvements
Refactored Keltner settings for flexible inner and outer band control.
MA type selection added; band calculations updated for consistency.
Removed the third Keltner band to reduce noise and simplify setup.
### Display and signals
Gradient fills for band breakouts, mean deviations, and squeeze periods.
“Show Mean EMA?” set to true and default “Signal Band” set to “Inner.”
Clearer tooltips and input descriptions.
### Reliability and performance
No more repaints. The indicator waits for confirmation before drawing occurs.
Faster execution through targeted refactors.
All algorithms have been reviewed and now use a consistent logic, naming, and structure.
Advanced Range Analyzer ProAdvanced Range Analyzer Pro – Adaptive Range Detection & Breakout Forecasting
Overview
Advanced Range Analyzer Pro is a comprehensive trading tool designed to help traders identify consolidations, evaluate their strength, and forecast potential breakout direction. By combining volatility-adjusted thresholds, volume distribution analysis, and historical breakout behavior, the indicator builds an adaptive framework for navigating sideways price action. Instead of treating ranges as noise, this system transforms them into opportunities for mean reversion or breakout trading.
How It Works
The indicator continuously scans price action to identify active range environments. Ranges are defined by volatility compression, repeated boundary interactions, and clustering of volume near equilibrium. Once detected, the indicator assigns a strength score (0–100), which quantifies how well-defined and compressed the consolidation is.
Breakout probabilities are then calculated by factoring in:
Relative time spent near the upper vs. lower range boundaries
Historical breakout tendencies for similar structures
Volume distribution inside the range
Momentum alignment using auxiliary filters (RSI/MACD)
This creates a live probability forecast that updates as price evolves. The tool also supports range memory, allowing traders to analyze the last completed range after a breakout has occurred. A dynamic strength meter is displayed directly above each consolidation range, providing real-time insight into range compression and breakout potential.
Signals and Breakouts
Advanced Range Analyzer Pro includes a structured set of visual tools to highlight actionable conditions:
Range Zones – Gradient-filled boxes highlight active consolidations.
Strength Meter – A live score displayed in the dashboard quantifies compression.
Breakout Labels – Probability percentages show bias toward bullish or bearish continuation.
Breakout Highlights – When a breakout occurs, the range is marked with directional confirmation.
Dashboard Table – Displays current status, strength, live/last range mode, and probabilities.
These elements update in real time, ensuring that traders always see the current state of consolidation and breakout risk.
Interpretation
Range Strength : High scores (70–100) indicate strong consolidations likely to resolve explosively, while low scores suggest weak or choppy ranges prone to false signals.
Breakout Probability : Directional bias greater than 60% suggests meaningful breakout pressure. Equal probabilities indicate balanced compression, favoring mean-reversion strategies.
Market Context : Ranges aligned with higher timeframe trends often resolve in the dominant direction, while counter-trend ranges may lead to reversals or liquidity sweeps.
Volatility Insight : Tight ranges with low ATR imply imminent expansion; wide ranges signal extended consolidation or distribution phases.
Strategy Integration
Advanced Range Analyzer Pro can be applied across multiple trading styles:
Breakout Trading : Enter on probability shifts above 60% with confirmation of volume or momentum.
Mean Reversion : Trade inside ranges with high strength scores by fading boundaries and targeting equilibrium.
Trend Continuation : Focus on ranges that form mid-trend, anticipating continuation after consolidation.
Liquidity Sweeps : Use failed breakouts at boundaries to capture reversals.
Multi-Timeframe : Apply on higher timeframes to frame market context, then execute on lower timeframes.
Advanced Techniques
Combine with volume profiles to identify areas of institutional positioning within ranges.
Track sequences of strong consolidations for trend development or exhaustion signals.
Use breakout probability shifts in conjunction with order flow or momentum indicators to refine entries.
Monitor expanding/contracting range widths to anticipate volatility cycles.
Custom parameters allow fine-tuning sensitivity for different assets (crypto, forex, equities) and trading styles (scalping, intraday, swing).
Inputs and Customization
Range Detection Sensitivity : Controls how strictly ranges are defined.
Strength Score Settings : Adjust weighting of compression, volume, and breakout memory.
Probability Forecasting : Enable/disable directional bias and thresholds.
Gradient & Fill Options : Customize range visualization colors and opacity.
Dashboard Display : Toggle live vs last range, info table size, and position.
Breakout Highlighting : Choose border/zone emphasis on breakout events.
Why Use Advanced Range Analyzer Pro
This indicator provides a data-driven approach to trading consolidation phases, one of the most common yet underutilized market states. By quantifying range strength, mapping probability forecasts, and visually presenting risk zones, it transforms uncertainty into clarity.
Whether you’re trading breakouts, fading ranges, or mapping higher timeframe context, Advanced Range Analyzer Pro delivers a structured, adaptive framework that integrates seamlessly into multiple strategies.
BBMA Enhanced Pro - Multi-Timeframe Band Breakout StrategyShort Title : BBMA Pro
Overview
The BBMA Enhanced Pro is a professional-grade trading indicator that builds on the Bollinger Bands Moving Average (BBMA) strategy, pioneered by Omar Ali , a Malaysian forex trader and educator. Combining Bollinger Bands with Weighted Moving Averages (WMA) , this indicator identifies high-probability breakout and reversal opportunities across multiple timeframes. With advanced features like multi-timeframe Extreme signal detection, eight professional visual themes, and a dual-mode dashboard, it’s designed for traders seeking precision in trending and consolidating markets. Optimized for dark chart backgrounds, it’s ideal for forex, stocks, and crypto trading.
History
The BBMA strategy was developed by Omar Ali (BBMA Oma Ally) in the early 2010s, gaining popularity in the forex trading community, particularly in Southeast Asia. Building on John Bollinger’s Bollinger Bands, Omar Ali integrated Weighted Moving Averages and a multi-timeframe approach to create a structured system for identifying reversals, breakouts, and extreme conditions. The BBMA Enhanced Pro refines this framework with modern features like real-time dashboards and customizable visualizations, making it accessible to both novice and experienced traders.
Key Features
Multi-Timeframe Extreme Signals : Detects Extreme signals (overbought/oversold conditions) on both current and higher timeframes simultaneously, a rare feature that enhances signal reliability through trend alignment.
Professional Visual Themes : Eight distinct themes (e.g., Neon Contrast, Fire Gradient) optimized for dark backgrounds.
Dual-Mode Dashboard : Choose between Full Professional (detailed metrics) or Simplified Trader (essential info with custom notes).
Bollinger Band Squeeze Detection : Identifies low volatility periods (narrow bands) signaling potential sideways markets or breakouts.
Confirmation Labels : Displays labels when current timeframe signals align with recent higher timeframe signals, highlighting potential consolidations or squeezes.
Timeframe Validation : Prevents selecting the same timeframe for current and higher timeframe analysis.
Customizable Visualization : Toggle signal dots, EMA 50, and confirmation labels for a clean chart experience.
How It Works
The BBMA Enhanced Pro combines Bollinger Bands (20-period SMA, ±2 standard deviations) with WMA (5 and 10 periods) to generate trade signals:
Buy Signal : WMA 5 Low crosses above the lower Bollinger Band, indicating a recovery from an oversold condition (Extreme buy).
Sell Signal : WMA 5 High crosses below the upper Bollinger Band, signaling a rejection from an overbought condition (Extreme sell).
Extreme Signals : Occur when prices or WMAs move significantly beyond the Bollinger Bands (±2σ), indicating statistically rare overextensions. These often coincide with Bollinger Band Squeezes (narrow bands, low standard deviation), signaling potential sideways markets or impending breakouts.
Multi-Timeframe Confirmation : The indicator’s unique strength is its ability to detect Extreme signals on both the current and higher timeframe (HTF) within the same chart. When the HTF generates an Extreme signal (e.g., buy), and the current timeframe follows with an identical signal, it suggests the lower timeframe is aligning with the HTF’s trend, increasing reliability. Labels appear only when this alignment occurs within a user-defined lookback period (default: 50 bars), highlighting periods of band contraction across timeframes.
Bollinger Band Squeeze : Narrow bands (low standard deviation) indicate reduced volatility, often preceding consolidation or breakouts. The indicator’s dashboard tracks band width, helping traders anticipate these phases.
Why Multi-Timeframe Extremes Matter
The BBMA Enhanced Pro’s multi-timeframe approach is rare and powerful. When the higher timeframe shows an Extreme signal followed by a similar signal on the current timeframe, it suggests the market is following the HTF’s trend or entering a consolidation phase. For example:
HTF Sideways First : If the HTF Bollinger Bands are shrinking (low volatility, low standard deviation), it signals a potential sideways market. Waiting for the current timeframe to show a similar Extreme signal confirms this consolidation, reducing the risk of false breakouts.
Risk Management : By requiring HTF confirmation, the indicator encourages traders to lower risk during uncertain periods, waiting for both timeframes to align in a low-volatility state before acting.
Usage Instructions
Select Display Mode :
Current TF Only : Shows Bollinger Bands and WMAs on the chart’s timeframe.
Higher TF Only : Displays HTF bands and WMAs.
Both Timeframes : Combines both for comprehensive analysis.
Choose Higher Timeframe : Select from 1min to 1D (e.g., 15min, 1hr). Ensure it differs from the current timeframe to avoid validation errors.
Enable Signal Dots : Visualize buy/sell Extreme signals as dots, sourced from current, HTF, or both timeframes.
Toggle Confirmation Labels : Display labels when current timeframe Extremes align with recent HTF Extremes, signaling potential squeezes or consolidations.
Customize Dashboard :
Full Professional Mode : View metrics like BB width, WMA trend, and last signal.
Simplified Trader Mode : Focus on essential info with custom trader notes.
Select Visual Theme : Choose from eight themes (e.g., Ice Crystal, Royal Purple) for optimal chart clarity.
Trading Example
Setup : 5min chart, HTF set to 1hr, signal dots and confirmation labels enabled.
Buy Scenario : On the 5min chart, WMA 5 Low crosses above the lower Bollinger Band (Extreme buy), confirmed by a recent 1hr Extreme buy signal within 50 bars. The dashboard shows narrow bands (squeeze), and a green label appears.
Action : Enter a long position, targeting the middle band, with a stop-loss below the recent low. The HTF confirmation suggests a strong trend or consolidation phase.
Sell Scenario : WMA 5 High crosses below the upper Bollinger Band on the 5min chart, confirmed by a recent 1hr Extreme sell signal. The dashboard indicates a squeeze, and a red label appears.
Action : Enter a short position, targeting the middle band, with a stop-loss above the recent high. The aligned signals suggest a potential reversal or sideways market.
Customization Options
BBMA Display Mode : Current TF Only, Higher TF Only, or Both Timeframes.
Higher Timeframe : 1min to 1D.
Visual Theme : Eight professional themes (e.g., Neon Contrast, Forest Glow).
Line Style : Smooth or Step Line for HTF plots.
Signal Dots : Enable/disable, select timeframe source (Current, Higher, or Both).
Confirmation Labels : Toggle and set lookback window (1-100 bars).
Dashboard : Enable/disable, choose mode (Full/Simplified), and set position (Top Right, Bottom Left, etc.).
Notes
Extreme Signals and Squeezes : Extreme signals often occur during Bollinger Band contraction (low standard deviation), signaling potential sideways markets or breakouts. Use HTF confirmation to filter false signals.
Risk Management : If the HTF shows a squeeze (narrow bands), wait for the current timeframe to confirm with an Extreme signal to reduce risk in choppy markets.
Limitations : Avoid trading Extremes in highly volatile markets without additional confirmation (e.g., volume, RSI).
Author Enhanced Professional Edition, inspired by Omar Ali’s BBMA strategy
Version : 6.0 Pro - Simplified
Last Updated : September 2025
License : Mozilla Public License 2.0
We’d love to hear your feedback! Share your thoughts or questions in the comments below.
MA Trends — mura visionMA Trends — mura vision is a multi-timeframe trend map that blends two local trend “ribbons” on the current timeframe with higher-timeframe context lines. It helps you read market bias at a glance and align entries with the dominant trend.
What the indicator plots
On the current timeframe
SMA 5/34 — short-term trend ribbon (filled area between SMA5 and SMA34).
EMA 55/89 — swing trend ribbon (filled area between EMA55 and EMA89).
Higher-timeframe context
EMA 233 (4H & 1D) — plotted as lines. Color reflects whether price on the same HTF is above (support) or below (resistance).
KAMA 233 (4H & 1D) — plotted as lines using a custom Kaufman implementation (Efficiency Ratio with fast=2, slow=30; squared smoothing). Color logic is the same as EMA 233.
Optional (disabled by default)
EMA 233 & KAMA 233 on the current TF — toggle on if you want the same 233 anchors on the chart’s timeframe.
Note: All higher-TF series are requested via request.security() with lookahead_off .
How to read it
1 Bias : Use the 4H/1D EMA/KAMA 233 as dynamic anchors.
• Green = price is above the anchor on that HTF (supportive context).
• Red = price is below the anchor on that HTF (resistive context).
2 Alignment : When both ribbons are green (SMA5>34 and EMA55>89) while HTF anchors are green, momentum and context agree (higher-quality trend). The opposite coloring suggests bearish alignment.
3 Pullbacks : Retracements toward the ribbon edges often act as retest zones within the prevailing regime.
Inputs & customization
Visibility toggles for each block:
SMA 5/34 (current TF), EMA 55/89 (current TF), EMA/KAMA 233 for 4H, 1D, and current TF (the latter are off by default).
Colors :
Lines for SMA5/SMA34 and EMA55/EMA89 (plotted with high transparency), fill colors for up/down trend ribbons, and separate support/resistance colors for EMA/KAMA 233.
Line width for all 233 anchors.
MTF behavior & repainting notes
HTF lines (4H/1D) are computed with lookahead_off and update intrabar until the higher-TF candle closes. This is expected on TradingView and not “future-looking”, but values can stabilize only at the close of the 4H/1D bar.
If you require strictly confirmed HTF values, use a “previous bar” approach (e.g., plotting series ) — not included here to keep the display responsive.
Good practices
Determine direction with 4H/1D EMA/KAMA 233, then refine timing with the current-TF ribbons.
For conservative use, favor trades with the color of the dominant HTF anchor.
Combine with your own risk management and confirmation rules.
What this script is / isn’t
✅ Visual analysis tool for multi-timeframe trend context.
❌ Not a strategy: it does not generate orders or calculate P&L.
Credits & license
© trading_mura — Published for educational purposes under the Mozilla Public License 2.0.
KAMA is implemented via a custom Kaufman method (ER with fast=2, slow=30, squared smoothing), not ta.kama() .
Disclaimer
Trading involves risk. This indicator is provided “as is” for informational/educational use only and is not financial advice. Always test on historical data and use proper risk management.
BTC Macro Composite Global liquidity Index -OffsetThis indicator is based on the thesis that Bitcoin price movements are heavily influenced by macro liquidity trends. It calculates a weighted composite index based on the following components:
• Global Liquidity (41%): Sum of central bank balance sheets (Fed , ECB , BoJ , and PBoC ), adjusted to USD.
• Investor Risk Appetite (22%): Derived from the Copper/Gold ratio, inverse VIX (as a risk-on signal), and the spread between High Yield and Investment Grade bonds (HY vs IG OAS).
• Gold Sensitivity (15–20%): Combines the XAUUSD price with BTC/Gold ratio to reflect the historical influence of gold on Bitcoin pricing.
Each component is normalized and then offset forward by 90 days to attempt predictive alignment with Bitcoin’s price.
The goal is to identify macro inflection points with high predictive value for BTC. It is not a trading signal generator but rather a macro trend context indicator.
❗ Important: This script should be used with caution. It does not account for geopolitical shocks, regulatory events, or internal BTC market structure (e.g., miner behavior, on-chain metrics).
💡 How to use:
• Use on the 1D timeframe.
• Look for divergences between BTC price and the macro index.
• Apply in confluence with other technical or fundamental frameworks.
🔍 Originality:
While similar components exist in macro dashboards, this script combines them uniquely using time-forward offsets and custom weighting specifically tailored for BTC behavior.
