DEMACROSSOVA BY FLACODouble EMAs for entry signals
ATR Bands for stoploss
Fibonacci bollinger bands for early exit confirmation
Tìm kiếm tập lệnh với "bands"
Easy Move & Squeeze Alerts1. Overview
The Easy Move & Squeeze Alerts indicator combines two proven techniques to help you anticipate major price swings and spot volatility compressions (long/short squeezes) early on. It offers:
Automated Alerts via TradingView’s alert engine
On-chart Visual Cues for immediate context
Flexible Inputs to fine-tune sensitivity, lookback length, and display options
2. TTM Squeeze (Volatility Compression)
Core Concept: Compares Bollinger Bands (standard deviation channels) with Keltner Channels (ATR-based channels).
Squeeze On: BBs lie completely inside Keltner Channels → volatility is compressed, signaling a potential buildup.
Squeeze Off: BBs break outside Keltner Channels → typically the start of a strong directional move.
Alert: When the squeeze releases, the indicator fires an alert:
💥 Squeeze Release – Volatility incoming!
Chart Label: A small, purple “🔒 Squeeze” label appears above the high of each bar while compression persists, giving you a real-time visual flag.
3. ATR Breakouts (Detecting Large Moves)
Core Concept: Builds a dynamic price channel around an EMA using ATR (Average True Range) multiplied by your chosen factor.
Cross Events:
Price crosses above the upper ATR band → potential bullish breakout.
Price crosses below the lower ATR band → potential bearish breakdown.
Alert Conditions: Separate alert triggers for “🚀 Move Up” and “📉 Move Down” fire the moment the close breaches the ATR-based bounds.
4. Visualization & Usage
Channel Plots:
Bollinger Bands in blue
Keltner Channels in orange
ATR Channels in aqua (optional)
Toggle all channel plots on or off with the showZones input.
Background Highlight: During a squeeze, the chart background lightly tints purple for quick visual confirmation.
Alerts Setup:
Simply click Create Alert in TradingView, select this indicator, and choose the event(s) you want (squeeze release, ATR breakouts).
You can route notifications via email, webhook, SMS, or platform pop-ups.
5. Deployment & Customization
Timeframes: Effective across all timeframes; most popular for day- and swing-trading.
Parameter Tuning:
Increase the len value to smooth channels and focus on only the most significant compressions/moves.
Adjust the ATR or BB multipliers to make alerts more or less sensitive.
With this indicator, you gain a clear, actionable framework for spotting both volatility squeezes and breakouts before they unfold—empowering you to enter trades ahead of the crowd. Enjoy customizing and putting it to work!
Euclidean Range [InvestorUnknown]The Euclidean Range indicator visualizes price deviation from a moving average using a geometric concept Euclidean distance. It helps traders identify trend strength, volatility shifts, and potential overextensions in price behavior.
Euclidean Distance
Euclidean distance is a fundamental concept in geometry and machine learning. It measures the "straight-line distance" between two points in space. In time series analysis, it can be used to measure how far one sequence deviates from another over a fixed window.
euclidean_distance(src, ref, len) =>
var float sum_sq_diff = na
sum_sq_diff := 0.0
for i = 0 to len - 1
diff = src - ref
sum_sq_diff += diff * diff
math.sqrt(sum_sq_diff)
In this script, we calculate the Euclidean distance between the price (source) and a smoothed average (reference) over a user-defined window. This gives us a single scalar that reflects the overall divergence between price and trend.
How It Works
Moving Average Calculation: You can choose between SMA, EMA, or HMA as your reference line. This becomes the "baseline" against which the actual price is compared.
Distance Band Construction: The Euclidean distance between the price and the reference is calculated over the Window Length. This value is then added to and subtracted from the average to form dynamic upper and lower bands, visually framing the range of deviation.
Distance Ratios and Z-Scores: Two distance ratios are computed: dist_r = distance / price (sensitivity to volatility); dist_v = price / distance (sensitivity to compression or low-volatility states)
Both ratios are normalized using a Z-score to standardize their behavior and allow for easier interpretation across different assets and timeframes.
Z-Score Plots: Z_r (white line) highlights instances of high volatility or strong price deviation; Z_v (red line) highlights low volatility or compressed price ranges.
Background Highlighting (Optional): When Z_v is dominant and increasing, the background is colored using a gradient. This signals a possible build-up in low volatility, which may precede a breakout.
Use Cases
Detect volatile expansions and calm compression zones.
Identify mean reversion setups when price returns to the average.
Anticipate breakout conditions by observing rising Z_v values.
Use dynamic distance bands as adaptive support/resistance zones.
Notes
The indicator is best used with liquid assets and medium-to-long windows.
Background coloring helps visually filter for squeeze setups.
Disclaimer
This indicator is provided for speculative analysis and educational purposes only. It is not financial advice. Always backtest and evaluate in a simulated environment before live trading.
TrendMaster Pro 2.3 with Alerts
Hello friends,
A member of the community approached me and asked me how to write an indicator that would achieve a particular set of goals involving comprehensive trend analysis, risk management, and session-based trading controls. Here is one example method of how to create such a system:
Core Strategy Components
Multi-Moving Average System - Uses configurable MA types (EMA, SMA, SMMA) with short-term (9) and long-term (21) periods for primary signal generation through crossovers
Higher Timeframe Trend Filter - Optional trend confirmation using a separate MA (default 50-period) to ensure trades align with broader market direction
Band Power Indicator - Dynamic high/low bands calculated using different MA types to identify price channels and volatility zones
Advanced Signal Filtering
Bollinger Bands Volatility Filter - Prevents trading during low-volatility ranging markets by requiring sufficient band width
RSI Momentum Filter - Uses customizable thresholds (55 for longs, 45 for shorts) to confirm momentum direction
MACD Trend Confirmation - Ensures MACD line position relative to signal line aligns with trade direction
Stochastic Oscillator - Adds momentum confirmation with overbought/oversold levels
ADX Strength Filter - Only allows trades when trend strength exceeds 25 threshold
Session-Based Trading Management
Four Trading Sessions - Asia (18:00-00:00), London (00:00-08:00), NY AM (08:00-13:00), NY PM (13:00-18:00)
Individual Session Limits - Separate maximum trade counts for each session (default 5 per session)
Automatic Session Closure - All positions close at specified market close time
Risk Management Features
Multiple Stop Loss Options - Percentage-based, MA cross, or band-based SL methods
Risk/Reward Ratio - Configurable TP levels based on SL distance (default 1:2)
Auto-Risk Calculation - Dynamic position sizing based on dollar risk limits ($150-$250 range)
Daily Limits - Stop trading after reaching specified TP or SL counts per day
Support & Resistance System
Multiple Pivot Types - Traditional, Fibonacci, Woodie, Classic, DM, and Camarilla calculations
Flexible Timeframes - Auto-adjusting or manual timeframe selection for S/R levels
Historical Levels - Configurable number of past S/R levels to display
Visual Customization - Individual color and display settings for each S/R level
Additional Features
Alert System - Customizable buy/sell alert messages with once-per-bar frequency
Visual Trade Management - Color-coded entry, SL, and TP levels with fill areas
Session Highlighting - Optional background colors for different trading sessions
Comprehensive Filtering - All signals must pass through multiple confirmation layers before execution
This approach demonstrates how to build a professional-grade trading system that combines multiple technical analysis methods with robust risk management and session-based controls, suitable for algorithmic trading across different market sessions.
Good luck and stay safe!
Commodity Trend Reactor [BigBeluga]
🔵 OVERVIEW
A dynamic trend-following oscillator built around the classic CCI, enhanced with intelligent price tracking and reversal signals.
Commodity Trend Reactor extends the traditional Commodity Channel Index (CCI) by integrating trend-trailing logic and reactive reversal markers. It visualizes trend direction using a trailing stop system and highlights potential exhaustion zones when CCI exceeds extreme thresholds. This dual-level system makes it ideal for both trend confirmation and mean-reversion alerts.
🔵 CONCEPTS
Based on the CCI (Commodity Channel Index) oscillator, which measures deviation from the average price.
Trend bias is determined by whether CCI is above or below user-defined thresholds.
Trailing price bands are used to lock in trend direction visually on the main chart.
Extreme values beyond ±200 are treated as potential reversal zones.
🔵 FEATURES\
CCI-Based Trend Shifts:
Triggers a bullish bias when CCI crosses above the upper threshold, and bearish when it crosses below the lower threshold.
Adaptive Trailing Stops:
In bullish mode, a trailing stop tracks the lowest price; in bearish mode, it tracks the highest.
Top & Bottom Markers:
When CCI surpasses +200 or drops below -200, it plots colored squares both on the oscillator and on price, marking potential reversal zones.
Background Highlights:
Each time a trend shift occurs, the background is softly colored (lime for bullish, orange for bearish) to highlight the change.
🔵 HOW TO USE
Use the oscillator to monitor when CCI crosses above or below threshold values to detect trend activation.
Enter trades in the direction of the trailing band once the trend bias is confirmed.
Watch for +200 and -200 square markers as warnings of potential mean reversals.
Use trailing stop areas as dynamic support/resistance to manage stop loss and exit strategies.
The background color changes offer clean confirmation of trend transitions on chart.
🔵 CONCLUSION
Commodity Trend Reactor transforms the simple CCI into a complete trend-reactive framework. With real-time trailing logic and clear reversal alerts, it serves both momentum traders and contrarian scalpers alike. Whether you’re trading breakouts or anticipating mean reversions, this indicator provides clarity and structure to your decision-making.
Multi-EnvelopeRMA Multi-Envelope Indicator
The RMA Multi-Envelope Indicator is a technical analysis tool designed for TradingView, utilizing Pine Script v6. It creates eight customizable envelope bands around a 200-period Running Moving Average (RMA) on a 5-minute timeframe, based on current market measurements. Each band has independent upper and lower percentage deviations, preset to: Band 1 (0.42%, 0.46%), Band 2 (0.78%, 0.69%), Band 3 (1.01%, 1.03%), Band 4 (1.36%, 1.39%), Band 5 (1.80%, 1.62%), Band 6 (2.15%, 2.13%), Band 7 (2.93%, 2.81%), and Band 8 (4.65%, 4.18%). Users can adjust the timeframe, moving average type (RMA, SMA, or EMA), length, and colors for the basis line and bands via hex codes (e.g., #FF6D00 for the basis and Band 8) with semi-transparent color.rgb fills. Ideal for identifying support/resistance, overbought/oversold conditions, or trend boundaries on a 5-minute chart.
RDBRB Strategy with Filters + Cooldowns + LabelsRDBRB Strategy with Filters + Cooldowns
This script implements the RDBRB (Rally-Drop-Base-Retest-Breakout) strategy, a classic price action setup designed to identify structured trade opportunities using volume, volatility bands, and trend alignment. It’s ideal for traders looking for clean, rule-based entries across any timeframe.
🧠 Core Components
Rally & Drop Detection
Identifies short-term momentum shifts using moving average crossovers:
✅ Ra = Rally (bullish crossover)
🔻 Dr = Drop (bearish crossunder)
Base Formation
A statistical base is defined using a moving average with a standard deviation envelope (Upper/Lower BB). This forms the foundation for breakout or retest setups.
Retest Zone (RT)
When price returns to the lower band (but stays below the base), it suggests a potential re-accumulation or reaction zone before a breakout.
Breakout Confirmation (BO)
A breakout is validated when:
Price crosses above the upper band
Volume exceeds the 20-bar average by a threshold multiplier
RSI is above a bullish momentum level
Price is trending above the longer-term EMA
⏱️ Smart Cooldown Logic
Each signal (Rally, Drop, Retest, Breakout) has an independent cooldown timer to prevent multiple triggers within a short range, filtering out noise and duplicate signals:
Customizable cooldown periods via input settings
Ensures signals are meaningful and not clustered
💡 Visual Markers
All signals are shown as small, color-coded labels:
Ra : Green label below bar
Dr : Red label above bar
RT : Yellow label below bar
BO : Green breakout label below bar
Bands and base are plotted for structure reference.
🛠️ Customizable Settings
Cooldown periods for each signal type
MA lengths, volume and RSI thresholds
Trend filter and base calculation inputs
This script is ideal for price action traders who want a clean, structured method to trade consolidations and trend continuations while avoiding over-signaling. Use it on any timeframe and combine with higher-timeframe confirmation for best results.
Relative Performance Spread**Relative Performance Spread Indicator – Overview**
This indicator compares the **relative performance between two stocks** by normalizing their prices and calculating the **spread**, **area under the curve (AUC)**, or **normalized price ratio**.
### **How It Works**
* **Input**: Select a second stock (`ticker2`) and a moving average window.
* **Normalization**: Each stock is normalized by its own moving average → `norm = close / MA`.
* **Spread**: The difference `spread = norm1 - norm2` reflects which stock is outperforming.
* **AUC**: Cumulative spread over time shows prolonged dominance or underperformance.
* **Bounds**: Bollinger-style bands are drawn around the spread to assess deviation extremes.
### **Usage**
* **Plot Type Options**:
* `"Spread"`: Spot outperformance; crossing bands may signal rotation.
* `"AUC"`: Track long-term relative trend dominance.
* `"Normalized"`: Directly compare scaled price movements.
Use this tool for **pair trading**, **relative momentum**, or **rotation strategies**. It adapts well across assets with different price scales.
The Ultimate Buy and Sell Indicator: Unholy Grail Edition"You see, Watson, the market is not random—it simply whispers in a code too complex for the average trader. Lucky for you, I am not average."
They searched for the Holy Grail of trading for decades—promises, false prophets, and overpriced PDFs.
But they were all looking in the wrong place.
This isn’t a relic buried in the desert.
This is the Unholy Grail — a machine-forged fusion of logic, engineering, and tactical overkill .
Built by Sherlock Macgyver , this is not a mystical object. It’s a surveillance system for trend detection, signal validation, and precision entries .
⚠️ Important: This script draws its own candles.
To see it properly, disable regular candles by turning off "Body", "Wick" and "Border" colors.
🔧 What You’re Looking At
This overlay plots confirmed Buy/Sell signals , momentum-based “watch” zones , adaptive candle coloring , SuperTrend bias detection , dual Bollinger Bands , and a moving average ribbon .
It’s not “minimalist” —it’s comprehensive .
📍 Configuring the Tool: Follow the Breadcrumbs
Every setting includes a tooltip — read them . They're not filler. They explain exactly how each feature functions so you can dial this thing in like you're tuning a surveillance rig in a Cold War bunker .
If you skip them, you're walking blind in a minefield .
🕰️ Timeframes: The Signal Sweet Spot
Each asset has a tempo . You need to find the one where signals align with clarity —not chaos .
Start with 4H or 1H —work up or down from there.
Too many fakeouts? → Higher timeframe
Too slow? → Drop to 15m or 5m —but expect more noise and adjust settings accordingly.
The signals scale with time, but you must find the rhythm that best fits your asset—and your trading lifestyle .
♻️ RSI Cycle = Signal Sensitivity
This is the heart of the system . It controls how reactive the RSI engine is.
Adjust based on noise level and how often you can actually monitor your charts.
Short cycle (14–24): More signals, more speed, more noise
Longer cycle (36–64): Smoother entries, better for swing traders
Tip: If your signals feel too jittery, increase the cycle. If they lag too much, reduce it.
📉 SuperTrend: Your Trend Bias Compass
This isn’t your average SuperTrend. It adapts with RSI overlay logic and detects market “silence” via EMA compression— turning white right before the chaos . That said, you still control its aggression.
ATR Length = how many bars to average
ATR Factor = how tight or loose it hugs price
Lower = more sensitive (more trades, more noise)
Higher = confirmation only (fewer, but stronger signals)
Tweak until it feels like a sniper rifle.
No, you won’t get it perfect on the first try.
Yes, it’s worth it.
🛠️ Modular Signals: Why Things Fire (or Don’t)
Buy/Sell entries require conditions to align. The logic is modular, and that’s on purpose.
RSI signals only fire if RSI crosses its smoothed MA outside the dead zone and a “Watch” condition is active.
SuperTrend signals can be enabled to act on crossovers, optionally ignoring the Watch filter .
Watch conditions (colored squares) act as early recon and hint at possible upcoming trades.
Background color changes are “pre-signal warnings” and will repaint . Use them as leading signals, not gospel.
Want more trades? Loosen your filters .
Want sniper entries? Lock them down .
🌈 Candles and MAs: Visual Market Structure
Candles adapt in real-time to MA structure:
Green = bullish (above both fast/slow MAs)
Yellow = indecision (between)
Red = bearish (below both)
Buy/Sell signals override candles with bright orange and fuchsia —because subtlety doesn’t win wars .
You can also enable up to 8 customizable moving averages —great for confluence , trend confirmation , or just looking like a wizard .
🧠 Pro Usage Tips (TL;DR for Smart People):
Use tooltips in the settings menu —every toggle and slider is explained
Test timeframes until signal frequency and reliability match your goals
Adjust RSI cycle to reduce noise or speed up signals based on how frequently you trade
Tweak SuperTrend factor and ATR to fit volatility on your asset
Start with visual confirmation :
• Are watch signals lining up with trend zones?
• Are backgrounds firing before price moves?
• Are candle colors agreeing with signal direction?
📣 Alerts & Integration
Alerts are available for:
Buy/Sell entries (confirmed or advanced background)
Watch signals
Full band agreement (both Bollinger bands bullish or bearish)
Use these with webhook systems , bots , or your own trade journals .
Created by Sherlock Macgyver
Because sometimes the best trade…
is knowing exactly when not to take one.
IU Mean Reversion SystemDESCRIPTION
The IU Mean Reversion System is a dynamic mean reversion-based trading framework designed to identify optimal reversal zones using a smoothed mean and a volatility-adjusted band. This system captures price extremes by combining exponential and running moving averages with the Average True Range (ATR), effectively identifying overextended price action that is likely to revert back to its mean. It provides precise long and short entries with corresponding exit conditions, making it ideal for range-bound markets or phases of low volatility.
USER INPUTS :
Mean Length – Controls the smoothness of the mean; default is 9.
ATR Length – Defines the lookback period for ATR-based band calculation; default is 100.
Multiplier – Determines how wide the upper and lower bands are from the mean; default is 3.
LONG CONDITION :
A long entry is triggered when the closing price crosses above the lower band, indicating a potential upward mean reversion.
A position is taken only if there is no active long position already.
SHORT CONDITION :
A short entry is triggered when the closing price crosses below the upper band, signaling a potential downward mean reversion.
A position is taken only if there is no active short position already.
LONG EXIT :
A long position exits when the high price crosses above the mean, implying that price has reverted back to its average and may no longer offer favorable long risk-reward.
SHORT EXIT :
A short position exits when the low price crosses below the mean, indicating the mean reversion has occurred and the downside opportunity has likely played out.
WHY IT IS UNIQUE:
Uses a double smoothing approach (EMA + RMA) to define a stable mean, reducing noise and false signals.
Adapts dynamically to volatility using ATR-based bands, allowing it to handle different market conditions effectively.
Implements a state-aware entry system using persistent variables, avoiding redundant entries and improving clarity.
The logic is clear, concise, and modular, making it easy to modify or integrate with other systems.
HOW USER CAN BENEFIT FROM IT :
Traders can easily identify reversion opportunities in sideways or mean-reverting environments.
Entry and exit points are visually labeled on the chart, aiding in clarity and trade review.
Helps maintain discipline and consistency by using a rule-based framework instead of subjective judgment.
Can be combined with other trend filters, momentum indicators, or higher time frame context for enhanced results.
Range Breakout [BigBeluga]Range Breakout is a dynamic channel-based indicator designed to identify breakout opportunities and price reactions within defined ranges. It automatically creates upper and lower bands with a midline, helping traders spot breakout zones, retests, and potential fakeouts.
🔵 Key Features:
Dynamic Channel Formation:
Automatically plots upper and lower channel bands with a midline based on ATR calculations.
Channels adjust upon breakout events or after a predefined number of bars to reflect new price ranges.
Breakout Detection:
Green circles appear when price breaks above the upper channel edge.
Red circles appear when price breaks below the lower channel edge.
A new channel is formed after each breakout, allowing traders to monitor evolving price ranges.
Retest Signals:
Upward-pointing green triangles signal a retest of the lower band, indicating potential support.
Downward-pointing red triangles indicate a retest of the upper band, suggesting possible resistance.
Filter Signals by Trends (New Feature):
Optional toggle to filter ▲ and ▼ signals based on channel breakout conditions.
When enabled:
In a bullish channel (confirmed by a green circle breakout), only ▲ signals are displayed.
In a bearish channel (confirmed by a red circle breakout), only ▼ signals are displayed.
Helps traders align retest signals with the prevailing trend for higher-quality trade setups.
Fakeout Identification:
'X' symbols appear when price breaks the upper or lower edge of the channel and quickly returns back inside.
Helps traders identify and avoid false breakouts.
🔵 Usage:
Breakout Trading: Use the green and red circle signals to identify potential breakout trades.
Retest Confirmation: Look for triangle markers to confirm retests of key levels, aiding in entry or exit decisions.
Fakeout Alerts: Utilize the 'X' signals to spot and avoid potential trap moves.
Dynamic Range Monitoring: Stay aware of changing market conditions with automatically updating channels.
Range Breakout is an essential tool for traders seeking to capitalize on range breakouts, retests, and fakeout scenarios. Its dynamic channels and clear visual signals provide a comprehensive view of market structure and potential trade setups.
[COG]StochRSI Zenith📊 StochRSI Zenith
This indicator combines the traditional Stochastic RSI with enhanced visualization features and multi-timeframe analysis capabilities. It's designed to provide traders with a comprehensive view of market conditions through various technical components.
🔑 Key Features:
• Advanced StochRSI Implementation
- Customizable RSI and Stochastic calculation periods
- Multiple moving average type options (SMA, EMA, SMMA, LWMA)
- Adjustable signal line parameters
• Visual Enhancement System
- Dynamic wave effect visualization
- Energy field display for momentum visualization
- Customizable color schemes for bullish and bearish signals
- Adaptive transparency settings
• Multi-Timeframe Analysis
- Higher timeframe confirmation
- Synchronized market structure analysis
- Cross-timeframe signal validation
• Divergence Detection
- Automated bullish and bearish divergence identification
- Customizable lookback period
- Clear visual signals for confirmed divergences
• Signal Generation Framework
- Price action confirmation
- SMA-based trend filtering
- Multiple confirmation levels for reduced noise
- Clear entry signals with customizable display options
📈 Technical Components:
1. Core Oscillator
- Base calculation: 13-period RSI (adjustable)
- Stochastic calculation: 8-period (adjustable)
- Signal lines: 5,3 smoothing (adjustable)
2. Visual Systems
- Wave effect with three layers of visualization
- Energy field display with dynamic intensity
- Reference bands at 20/30/50/70/80 levels
3. Confirmation Mechanisms
- SMA trend filter
- Higher timeframe alignment
- Price action validation
- Divergence confirmation
⚙️ Customization Options:
• Visual Parameters
- Wave effect intensity and speed
- Energy field sensitivity
- Color schemes for bullish/bearish signals
- Signal display preferences
• Technical Parameters
- All core calculation periods
- Moving average types
- Divergence detection settings
- Signal confirmation criteria
• Display Settings
- Chart and indicator signal placement
- SMA line visualization
- Background highlighting options
- Label positioning and size
🔍 Technical Implementation:
The indicator combines several advanced techniques to generate signals. Here are key components with code examples:
1. Core StochRSI Calculation:
// Base RSI calculation
rsi = ta.rsi(close, rsi_length)
// StochRSI transformation
stochRSI = ((ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) != 0) ?
(100 * (rsi - ta.lowest(rsi, stoch_length))) /
(ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) : 0
2. Signal Generation System:
// Core signal conditions
crossover_buy = crossOver(sk, sd, cross_threshold)
valid_buy_zone = sk < 30 and sd < 30
price_within_sma_bands = close <= sma_high and close >= sma_low
// Enhanced signal generation
if crossover_buy and valid_buy_zone and price_within_sma_bands and htf_allows_long
if is_bullish_candle
long_signal := true
else
awaiting_bull_confirmation := true
3. Multi-Timeframe Analysis:
= request.security(syminfo.tickerid, mtf_period,
)
The HTF filter looks at a higher timeframe (default: 4H) to confirm the trend
It only allows:
Long trades when the higher timeframe is bullish
Short trades when the higher timeframe is bearish
📈 Trading Application Guide:
1. Signal Identification
• Oversold Opportunities (< 30 level)
- Look for bullish crosses of K-line above D-line
- Confirm with higher timeframe alignment
- Wait for price action confirmation (bullish candle)
• Overbought Conditions (> 70 level)
- Watch for bearish crosses of K-line below D-line
- Verify higher timeframe condition
- Confirm with bearish price action
2. Divergence Trading
• Bullish Divergence
- Price makes lower lows while indicator makes higher lows
- Most effective when occurring in oversold territory
- Use with support levels for entry timing
• Bearish Divergence
- Price makes higher highs while indicator shows lower highs
- Most reliable in overbought conditions
- Combine with resistance levels
3. Wave Effect Analysis
• Strong Waves
- Multiple wave lines moving in same direction indicate momentum
- Wider wave spread suggests increased volatility
- Use for trend strength confirmation
• Energy Field
- Higher intensity in trading zones suggests stronger moves
- Use for momentum confirmation
- Watch for energy field convergence with price action
The energy field is like a heat map that shows momentum strength
It gets stronger (more visible) when:
Price is in oversold (<30) or overbought (>70) zones
The indicator lines are moving apart quickly
A strong signal is forming
Think of it as a "strength meter" - the more visible the energy field, the stronger the potential move
4. Risk Management Integration
• Entry Confirmation
- Wait for all signal components to align
- Use higher timeframe for trend direction
- Confirm with price action and SMA positions
• Stop Loss Placement
- Consider placing stops beyond recent swing points
- Use ATR for dynamic stop calculation
- Account for market volatility
5. Position Management
• Partial Profit Taking
- Consider scaling out at overbought/oversold levels
- Use wave effect intensity for exit timing
- Monitor energy field for momentum shifts
• Trade Duration
- Short-term: Use primary signals in trading zones
- Swing trades: Focus on divergence signals
- Position trades: Utilize higher timeframe signals
⚠️ Important Usage Notes:
• Avoid:
- Trading against strong trends
- Relying solely on single signals
- Ignoring higher timeframe context
- Over-leveraging based on signals
Remember: This tool is designed to assist in analysis but should never be used as the sole decision-maker for trades. Always maintain proper risk management and combine with other forms of analysis.
Optimized Dynamic SupertrendDetailed Explanation of the Optimized Dynamic Supertrend Script
This Supertrend script is designed to dynamically adapt to different market conditions using ATR expansion, volume confirmation, and trend filtering. Below is a step-by-step breakdown of how it works and its functions.
1 ATR-Based Supertrend Calculation
📌 Key Purpose:
The script calculates an adaptive ATR-based Supertrend line, which acts as a dynamic support or resistance level for trend direction.
📌 How it Works:
ATR (Average True Range) is used to measure market volatility.
A dynamic ATR multiplier is applied based on price standard deviation (instead of a fixed value).
The Supertrend is calculated as:
Upper Band: SMA(close, ATR length) + (ATR Multiplier * ATR Value)
Lower Band: SMA(close, ATR length) - (ATR Multiplier * ATR Value)
The Supertrend flips when price crosses and holds beyond the Supertrend line.
🔹 Dynamic Adjustment:
Instead of using a fixed ATR multiplier, the script adjusts it using:
pinescript
Copy
Edit
dynamicFactor = ta.stdev(close, atrLength) / ta.sma(close, atrLength)
atrMultiplier = input(1.5, title="Base ATR Multiplier") * dynamicFactor
High volatility → Wider Supertrend bands (to avoid false signals).
Low volatility → Tighter Supertrend bands (for faster detection).
2 Trend Detection Logic
📌 Key Purpose:
Determines if the market is in a bullish or bearish trend based on price action.
Uses volume sensitivity and ATR expansion to reduce false signals.
📌 How it Works:
pinescript
Copy
Edit
var float supertrend = na
supertrend := close > nz(supertrend , lowerBand) ? lowerBand : upperBand
The Supertrend value updates dynamically.
If price is above the Supertrend line, the trend is bullish (green).
If price is below the Supertrend line, the trend is bearish (red).
3 Volume Sensitivity Confirmation
📌 Key Purpose:
Avoid false trend flips by confirming with volume (approximated using a CVD proxy).
📌 How it Works:
pinescript
Copy
Edit
priceChange = close - close
volumeWeightedTrend = priceChange * volume // Approximate CVD Behavior
trendConfirmed = volumeWeightedTrend > 0 ? close > supertrend : close < supertrend
Positive price change + High volume → Confirms bullish momentum.
Negative price change + High volume → Confirms bearish momentum.
If there’s low volume, the trend change is ignored to avoid false breakouts.
4 Noise Reduction (Final Trend Confirmation)
📌 Key Purpose:
Filter out weak or choppy price movements using ATR expansion.
📌 How it Works:
pinescript
Copy
Edit
trendUp = trendConfirmed and ta.atr(atrLength) > ta.atr(atrLength)
trendDown = not trendUp
Trend only flips when confirmed by volume + ATR expansion.
If ATR is not expanding, the script ignores weak price movements.
This ensures Supertrend signals align with strong market moves.
5 Can This Be Used on All Timeframes?
✅ YES! This Supertrend is adaptive, meaning it adjusts dynamically based on:
Volatility: Uses ATR expansion to adjust for different market conditions.
Timeframe Sensitivity: Works on any timeframe (1M, 5M, 15M, 1H, 4H, 1D, 1W).
Market Structure: Confirms trend flips using volume & price movement strength.
🚀 Best Timeframes for Trading:
For Scalping (1M - 15M) → Quick execution, best with order flow confirmation.
For Swing Trading (1H - 4H - 1D) → Stronger trend signals, reduced noise.
For High Timeframes (3D - 1W) → Identifies major market shifts.
🔥 Advantages & Disadvantages in Your Trading Setup
✅ Advantages:
✔ Fully Dynamic & Adaptive → Adjusts to different timeframes & volatility.
✔ Reduces False Signals → Uses ATR expansion & volume confirmation.
✔ Precise Trend Reversals → Labels LONG & SHORT entries clearly.
✔ Works on Any Market → Crypto, Forex, Stocks, Commodities.
✔ No Extra Indicators → Pure Supertrend-based (fits your setup).
❌ Disadvantages:
⚠ Lagging Indicator → ATR & volume confirmation add slight delay.
⚠ Needs High Volume to Confirm → Weak volume → no trend flip.
⚠ Choppy Market = Late Entries → Sideways movement can cause delays.
🚀 Final Thoughts:
It’s fully dynamic & adaptive (unlike traditional static Supertrends).
No extra indicators → Uses only Supertrend logic
Refines entry points using volume & ATR confirmation (removes noise).
This ensures you get high-probability trend signals while filtering out weak breakouts! 🎯
Institutional Moves DetectorIndicator Name: Institutional Pattern Detector
What It Does:
Trend Following: It uses a Moving Average (MA) to understand the general direction of the price. The MA is like a smoothed-out line of the price over time, showing if the price trend is going up or down.
Volatility Measurement: The script employs Bollinger Bands (BB) to see how much the price is fluctuating. Bollinger Bands create an upper and lower "channel" around the price, which gets wider or narrower based on how volatile the price is.
Volume Check: It looks at trading volume to find times when there's unusually high activity, which could mean big players (institutions like banks or funds) are trading. It flags this when the volume is 1.5 times more than the average volume of the last 100 bars.
Pattern Detection for Trading Signals:
Entry Signal ("IN"): When there's high volume and the price is above the upper Bollinger Band, it suggests there might be strong buying from big institutions. This could mean the price might keep going up.
EXIT Signal ("OUT"): If there's high volume and the price falls below the lower Bollinger Band, it indicates possible strong selling pressure from institutions, suggesting the price might go down.
Visual Cues:
An orange label "IN" appears below the price bar for entry signals.
A red label "OUT" appears above the price bar for exit signals.
The moving average line is plotted on the chart in orange to help you see the trend.
Alerts: The script can alert you when these entry or exit signals occur, so you can get notifications without needing to stare at the chart all day.
For New Traders:
This indicator helps you spot when big traders might be influencing the market, potentially giving you a clue about when to enter or exit.
Remember, this is one tool among many. You should not base your trading solely on this; combine it with other analysis methods.
It's always wise to practice with a demo account before using real money to get a feel for how these signals work in actual market conditions.
Hull Suite by MRS**Hull Suite by MRS Strategy Indicator**
The Hull Suite by MRS Strategy is a technical analysis tool designed to provide insights into market trends using variations of the Hull Moving Average (HMA). This strategy aims to help traders identify optimal entry points for both long and short positions by utilizing multiple types of Hull-based indicators.
### Key Features:
1. **Hull Moving Average Variations**: The indicator offers three different Hull Moving Average variants:
- **HMA (Hull Moving Average)**: A fast-moving average that minimizes lag and reacts quickly to price changes.
- **EHMA (Enhanced Hull Moving Average)**: A smoother version of HMA with reduced noise, offering a clearer view of market trends.
- **THMA (Triple Hull Moving Average)**: A more complex Hull average that aims to provide a stronger confirmation of trend direction.
2. **Customizable Parameters**:
- **Source Selection**: Allows traders to choose the source for calculation (e.g., closing prices).
- **Length**: A configurable parameter to adjust the period over which the moving average is calculated (e.g., 55-period for swing entries).
- **Trend Coloring**: Users can enable automatic color-coding of the Hull moving average to reflect whether the market is in an uptrend (green) or downtrend (red).
- **Candle Color**: Option to color candles based on Hull's trend, further improving the visual clarity of trend direction.
3. **Entry and Exit Signals**:
- **Buy Signal**: Generated when the Hull moving average crosses above its historical value, indicating a potential upward price movement.
- **Sell Signal**: Triggered when the Hull moving average crosses below its historical value, signaling a potential downward price movement.
- The strategy can be customized to work with long, short, or both directions, making it adaptable for various market conditions.
4. **Visual Representation**:
- **Hull Bands**: The indicator can plot the Hull moving average as bands, with customizable transparency to suit individual preferences.
- **Band Filler**: The area between the two Hull moving averages is filled, making it easier to identify trends at a glance.
5. **Backtesting and Strategy Execution**: This strategy can be tested on historical data with adjustable backtest start and stop dates, providing traders with a better understanding of its performance before live trading.
### Purpose:
The Hull Suite by MRS Strategy is designed to assist traders in determining the optimal time to enter and exit the market based on robust Hull moving averages. With its flexibility, it can be used for trend-following, swing trading, or other strategic applications.
Top G indicator [BigBeluga]Top G Indicator is a straightforward yet powerful tool designed to identify market extremes, helping traders spot potential tops and bottoms effectively.
🔵 Key Features:
High Probability Signals:
𝔾 Label: Indicates high-probability market bottoms based on specific conditions such as low volatility and momentum shifts.
Top Label: Highlights high-probability market tops using key price action dynamics.
Simple Signals for Potential Extremes:
^ (Caret): Marks potential bottom areas with less certainty than 𝔾 labels.
v (Inverted Caret): Signals potential top areas with less certainty than Top labels.
Midline Visualization:
A smoothed midline helps identify the center of the current range, providing additional context for trend and range trading.
Range Highlighting:
Dynamic bands around the highest and lowest points of the selected period, color-coded for easy identification of the market range.
🔵 Usage:
Spot Extremes: Use 𝔾 and Top labels to identify high-probability reversal points for potential entries or exits.
Monitor Potential Reversals: Leverage ^ and v marks for additional signals on potential turning points, especially during range-bound conditions.
Range Analysis: Use the midline and dynamic bands to determine the market's range and its center, aiding in identifying consolidation or breakout scenarios.
Confirmation Tool: Combine this indicator with other tools to confirm reversal or trend continuation setups.
Top G Indicator is a simple yet effective tool for spotting market extremes, designed to assist traders in making timely decisions by identifying potential tops and bottoms with clarity.
Directional Volume IndexDirectional Volume Index (DVI) (buying/selling pressure)
This index is adapted from the Directional Movement Index (DMI), but based on volume instead of price movements. The idea is to detect building directional volume indicating a growing amount of orders that will eventually cause the price to follow. (DVI is not displayed by default)
The rough algorithm for the Positive Directional Volume Index (green bar):
calculate the delta to the previous green bar's volume
if the delta is positive (growing buying pressure) add it to an SMA, else add 0 (also for red bars)
divide these average deltas by the average volume
the result is the Positive Directional Volume Index (DVI+) (vice versa for DVI-)
Differential Directional Volume Index (DDVI) (relative pressure)
Creating the difference of both Directional Volume Indexes (DVI+ - DVI-) creates the Differential Directional Volume Index (DDVI) with rising values indicating a growing buying pressure, falling values a growing selling pressure. (DDVI is displayed by default, smoothed by a custom moving average)
Average Directional Volume Index (ADVX) (pressure strength)
Putting the relative pressure (DDVI) in relation to the total pressure (DVI+ + DVI-) we can determine the strength and duration of the currently building volume change / trend. For the DMI/ADX usually 20 is an indicator for a strong trend, values above 50 suggesting exhaustion and approaching reversals. (ADVX is not displayed by default, smoothed by a custom moving average)
Divergences of the Differential Directional Volume Index (DDVI) (imbalances)
By detecting divergences we can detect situations where e.g. bullish volume starts to build while price is in a downtrend, suggesting that there is growing buying pressure indicating an imminent bullish pullback/order block or reversal. (strong and hidden divergences are displayed by default)
Divergences Overview:
strong bull: higher lows on volume, lower lows on price
medium bull: higher lows on volume, equal lows on price
weak bull: equal lows on volume, lower lows on price
hidden bull: lower lows on volume, higher lows on price
strong bear: lower highs on volume, higher highs on price
medium bear: lower highs on volume, equal highs on price
weak bear: equal highs on volume, higher highs on price
hidden bear: higher highs on volume, lower highs on price
DDVI Bands (dynamic overbought/oversold levels)
Using Bollinger Bands with DDVI as source we receive an averaged relative pressure with stdev band offsets. This can be used as dynamic overbought/oversold levels indicating reversals on sharp crossovers.
Alerts
As of now there are no alerts built in, but all internal data is exposed via plot and plotshape functions, so it can be used for custom crossover conditions in the alert dialog. This is still a personal research project, so if you find good setups, please let me know.
FIR Low Pass Filter Suite (FIR)The FIR Low Pass Filter Suite is an advanced signal processing indicator that applies finite impulse response (FIR) filtering techniques to price data. At its core, the indicator uses windowed-sinc filtering, which provides optimal frequency response characteristics for separating trend from noise in financial data.
The indicator offers multiple window functions including Kaiser, Kaiser-Bessel Derived (KBD), Hann, Hamming, Blackman, Triangular, and Lanczos. Each window type provides different trade-offs between main-lobe width and side-lobe attenuation, allowing users to fine-tune the frequency response characteristics of the filter. The Kaiser and KBD windows provide additional control through an alpha parameter that adjusts the shape of the window function.
A key feature is the ability to operate in either linear or logarithmic space. Logarithmic filtering can be particularly appropriate for financial data due to the multiplicative nature of price movements. The indicator includes an envelope system that can adaptively calculate bands around the filtered price using either arithmetic or geometric deviation, with separate controls for upper and lower bands to account for the asymmetric nature of market movements.
The implementation handles edge effects through proper initialization and offers both centered and forward-only filtering modes. Centered mode provides zero phase distortion but introduces lag, while forward-only mode operates causally with no lag but introduces some phase distortion. All calculations are performed using vectorized operations for efficiency, with carefully designed state management to handle the filter's warm-up period.
Visual feedback is provided through customizable color gradients that can reflect the current trend direction, with optional glow effects and background fills to enhance visibility. The indicator maintains high numerical precision throughout its calculations while providing smooth, artifact-free output suitable for both analysis and visualization.
Torus Visualization-Secret Geometry-AYNETExplanation:
Outer and Inner Circles:
The script draws two main circles: the outer boundary and the inner boundary of the Torus.
Bands Between Circles:
Additional concentric circles are drawn to create the illusion of a Torus structure.
Customizable Inputs:
You can control the outer radius, inner radius, number of segments for smoother circles, and the number of bands to improve visualization.
Parameters:
center_x and center_y define the center of the Torus on the chart.
outer_radius and inner_radius control the size of the Torus.
segments define the resolution of the circles (more segments = smoother appearance).
Visualization:
The Torus appears as a series of concentric circles, giving a 2D approximation of the 3D structure.
This script can be visualized on any chart, and the Torus will adjust its position based on the specified center and radius values.
VWAP2 --ClaireIndicator Release Notes
I am excited to introduce a powerful multi-timeframe Volume Weighted Average Price (VWAP) indicator. This tool helps traders analyze market trends and identify key support and resistance levels across various timeframes. Below are the main features and usage guidelines for this indicator:
Key Features
Open Price for Each Timeframe
The "Open" option represents the opening price for each specific timeframe, such as daily, weekly, monthly, etc.
Previous vs. Current Levels
Levels prefixed with 'P' (e.g., pwval) are calculated for the previous period, while those without 'P' (e.g., wval) represent the current period. For instance, pwval is the VWAP-calculated Value Area Low (VAL) for the previous week, whereas wval applies to the current week.
VWAP Calculation Standards
VWAP can be calculated using a standard deviation (S) or a percentage (P). The "Multiplier" indicates how many standard deviations are applied, with a default setting of S (standard deviation) and a multiplier of 1.
Data Source Default
The default data source for calculations is hlc3, which is the average of high, low, and close prices. This can be adjusted if needed.
Merge Function
The Merge option visually groups data that is closely aligned within a specified range, allowing for a clearer representation of critical price levels.
Viewing Recommendations
When analyzing higher dimensions, it is recommended to enable Quarter (Q) and Year (Y) settings to identify important price levels near the current price. For detailed attention, you can disable levels that are significantly distant from the current price.
Data Limitations
Free TradingView accounts can pull data from up to 20,000 candles. This means the indicator is most accurate and comprehensive on 1-hour and 4-hour timeframes, given these data constraints.
Usage Guidelines
Trend Analysis: Utilize VWAP and bands across different timeframes to identify market trend continuations or reversals.
Support and Resistance Identification: Use the calculated upper and lower bands as potential support or resistance levels to optimize entry and exit points in your trading.
Combined Application: It is recommended to use this indicator alongside other technical analysis tools to improve the accuracy of your analysis and the reliability of your trading decisions.
I believe this versatile and highly customizable VWAP indicator will become an essential part of your trading toolkit, helping you to better understand market dynamics and make more precise trading decisions.
Fibonacci BandsDescription
This indicator dynamically calculates Fibonacci retracement levels based on the highest high and lowest low over a specified lookback period. The key Fibonacci levels (0.236, 0.382, 0.5, 0.618, and 0.786) are plotted on the chart, with shaded areas between these levels for visual guidance.
How it works
The script computes the highest high (hh) and the lowest low (ll) over the defined length.
It calculates the price range (delta) as the difference between the highest high and the lowest low.
Fibonacci levels are then determined using the formula: ℎℎ − (delta × Fibonacci ratio)
Each Fibonacci level is then plotted as a line with a specific color.
Key Features
Customizable Length: Users can adjust the lookback period to suit their trading strategy.
Multiple Fibonacci Levels: Includes common Fibonacci retracement levels, providing traders with a comprehensive view of potential support and resistance areas.
Visual Fillings: The script includes customizable shading between levels, which helps traders quickly identify key zones (like the "Golden Zone" between 0.5 and 0.618).
Unique Points
Fibonacci Focus: This script is specifically designed around Fibonacci retracement levels, which are popular among technical traders for identifying potential reversal points.
Dynamic Range Calculation: The use of the highest high and lowest low within a user-defined period offers a dynamic approach to adapting to changing market conditions.
How to use it
Adjust the length parameter (default is 60) to determine how many bars back the indicator will calculate the highest high and lowest low. A longer length may provide a broader perspective of price action, while a shorter length may react more quickly to recent price changes.
Observe the plotted Fibonacci levels: 0.236, 0.382, 0.5, 0.618, and 0.786. These levels often act as potential support and resistance points. Pay attention to how price interacts with these levels.
When the price approaches a Fibonacci level, consider it a potential reversal point. The filled areas between the Fibonacci levels indicate zones where price might consolidate or reverse. The "Golden Zone" (between 0.5 and 0.618) is particularly significant; many traders watch this area closely for potential entry points in an uptrend or exit points in a downtrend.
Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
Hullinger Percentile Oscillator [AlgoAlpha]🚀 Introducing the Hullinger Percentile Oscillator by AlgoAlpha! 🚀
This versatile Pine Script™ indicator is designed to help you identify swing trends and potential reversals with precision. Whether you're looking to catch market swings or spot divergences, the Hullinger Percentile Oscillator offers a comprehensive suite of features to enhance your trading strategy.
Key Features
🎯 Customizable Hullinger Settings: Adjust the main length, source, and standard deviation multipliers to fine-tune the indicator to your preferred trading style.
🔄 Dynamic Oscillator Modes: Switch between "Swing" mode for trend identification and "Contrarian" mode for reversal spotting, adapting the indicator to your market view.
📉 Divergence Detection: The indicator includes parameters to control the sensitivity and confirmation of divergence signals, helping to filter out noise and highlight significant market moves.
🌈 Color-Coded Visuals: Easily distinguish between bullish and bearish signals with customizable color settings for a clear visual representation on your chart.
🔔 Alert Integration: Stay ahead of the market with built-in alerts for key conditions, including strong and weak reversals, as well as bullish and bearish swings.
Quick Guide to Using the Hullinger Percentile Oscillator
Maximize your trading edge with the Hullinger Percentile Oscillator by following these steps! 📈✨
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon ⭐. Customize settings like Main Length, Oscillator Mode, and Appearance to fit your trading needs.
📊 Market Analysis: Use "Swing" mode to track trends and "Contrarian" mode to spot reversals. Watch for divergence signals to catch potential trend changes.
🔔 Alerts: Set up alerts to be notified of significant market movements without constantly monitoring your chart.
How It Works
The Hullinger Percentile Oscillator calculates its signals by applying a modified standard deviation approach to the Hull Moving Average (HMA) of a selected price source. It creates both inner and outer bands based on different multipliers. The oscillator then measures the position of the price relative to these bands, smoothing the result for swing trend detection. Depending on the chosen mode, the oscillator either highlights swing trends or potential reversals. Divergences are detected by comparing recent pivot highs and lows in both price and the oscillator, allowing you to spot bullish or bearish divergence setups. Alerts are triggered based on key crossovers or when specific conditions are met, ensuring that you are always informed of crucial market developments.
