MA DerivativesMA Derivatives basicly using Ichimoku Cloud and some additional moving averages for traders.
A. ICHIMOKU
Tenkan-sen (Conversion Line): (9-period high + 9-period low)/2
On a daily chart , this line is the midpoint of the 9-day high-low range, which is almost two weeks.
Kijun-sen (Base Line): (26-period high + 26-period low)/2
On a daily chart , this line is the midpoint of the 26-day high-low range, which is almost one month.
Senkou Span A (Leading Span A): (Conversion Line + Base Line)/2
This is the midpoint between the Conversion Line and the Base Line. The Leading Span A forms one of the two Cloud boundaries. It is referred to as “Leading” because it is plotted 26 periods in the future and forms the faster Cloud boundary.
Senkou Span B (Leading Span B): (52-period high + 52-period low)/2
On the daily chart , this line is the midpoint of the 52-day high-low range, which is a little less than 3 months. The default calculation setting is 52 periods, but it can be adjusted. This value is plotted 26 periods in the future and forms the slower Cloud boundary.
Chikou Span: Represents the closing price and is plotted 26 days back.
Kumo Cloud: Kumo cloud between Senkuo Span A and Senkou Span B lines. It can be green or red. Color can be change with the trend.
You can use Ichimoku for buy&sell strategy
For Buying Strategy
- Tenkansen (Conversion Line) should crossover Kijunsen (Base line) above the highest line of cloud
- Price should be above the highest line of cloud
- Chikouspan should be above the cloud
For Selling Strategy
- Kijunsen (Base Line) should crossover Tenkansen (Conversion Line) below the lowest line of cloud
- Price should be below the lowest line of cloud
- Chikouspan should be below the cloud
B. SIMPLE MOVING AVERAGES
The indicator has some of Simple Moving Averages
It includes:
-Simple Moving Average 50
-Simple Moving Average 100
-Simple Moving Average 200
C. EXPONENTIAL MOVING AVERAGES
The indicator has some of Simple Moving Averages
It includes:
-Exponential Moving Average 9
-Exponential Moving Average 21
-Exponential Moving Average 50
D. BOLLINGER BAND
Bollinger Bands are a type of price envelope developed by John BollingerOpens in a new window. (Price envelopes define upper and lower price range levels.) Bollinger Bands are envelopes plotted at a standard deviation level above and below a simple moving average of the price. Because the distance of the bands is based on standard deviation, they adjust to volatility swings in the underlying price.
Bollinger Bands use 2 parameters, Period and Standard Deviations, StdDev. The default values are 20 for period, and 2 for standard deviations, although you may customize the combinations.
Bollinger bands help determine whether prices are high or low on a relative basis. They are used in pairs, both upper and lower bands and in conjunction with a moving average. Further, the pair of bands is not intended to be used on its own. Use the pair to confirm signals given with other indicators.
How this indicator works
When the bands tighten during a period of low volatility, it raises the likelihood of a sharp price move in either direction. This may begin a trending move. Watch out for a false move in opposite direction which reverses before the proper trend begins.
When the bands separate by an unusual large amount, volatility increases and any existing trend may be ending.
Prices have a tendency to bounce within the bands' envelope, touching one band then moving to the other band. You can use these swings to help identify potential profit targets. For example, if a price bounces off the lower band and then crosses above the moving average, the upper band then becomes the profit target.
Price can exceed or hug a band envelope for prolonged periods during strong trends. On divergence with a momentum oscillator, you may want to do additional research to determine if taking additional profits is appropriate for you.
A strong trend continuation can be expected when the price moves out of the bands. However, if prices move immediately back inside the band, then the suggested strength is negated.
Calculation
First, calculate a simple moving average. Next, calculate the standard deviation over the same number of periods as the simple moving average. For the upper band, add the standard deviation to the moving average. For the lower band, subtract the standard deviation from the moving average.
Typical values used:
Short term: 10 day moving average, bands at 1.5 standard deviations. (1.5 times the standard dev. +/- the SMA)
Medium term: 20 day moving average, bands at 2 standard deviations.
Long term: 50 day moving average, bands at 2.5 standard deviations.
E. ADJUSTABLE MOVING AVERAGES
And this script has also 2 adjustable moving average
- 1 Adjustable Simple Moving Average
- 1 Adjustable Exponential Moving Average
You can just change the length for using this tool.
在腳本中搜尋"high low"
Ease of Movement WatcherHere’s a handy Ease of Movement(EMV) Indicator. I tried to include detailed comments so that anyone that’s learning pine can follow along.
The Ease of Movement Indicator is a volume based oscillator that is designed to measure the ease (or movability) of price movement for a security. The EMV is a centered oscillator, meaning that values can fluctuate above and below zero.
To understand how to use and interpret the EMV Indicator, its crucial to first understand its two main calculations :
Distance Moved = ((high + low) / 2) - ((high + low ) / 2)
-This is the difference between the current period’s midpoint and the previous period’s
midpoint.
Box Ratio = (volume / 100,000) / (high - low)
-When calculating the Box Ratio, it is common to divide the volume by 100,000 for a clearer visualization of the data. However, users can choose
to modify this value with the ‘volumeDiv’ input.
The Ease of Movement Value is then pretty simple to calculate:
EMV = (Distance Moved / Box Ratio)
The indicator then plots a SMA of the previous 24 EMV Values.
Looking at the formula, we know that combining low volume with a large {high, low} range will result in a relatively small box ratio value. Thus, we know that the EMV value for that period will be higher since EMV is found by dividing the Distance Moved by the Box Ratio.
Here’s a simple guide to interpreting the EMV:
- If (EMV > 0)
then price is increasing with relative ease.
-If (EMV < 0)
then price is decreasing with relative ease.
- If high-low range is large and volume is low
then ease of movement is high.
-If high-low range is small and volume is high
then ease of movement is low.
The Chart:
-The histogram represents the Simple Moving Average of EMV Values. The default length is 24, but users can adjust this value at the inputs menu(I've
found 24 works best).
-The teal and pink dotted lines represent the standard deviation of the SMA of EMV values multiplied by 2.5.
-The histogram turns dark green when the EMV SMA is greater than the top teal dotted standard deviations line.
-The histogram turns maroon when the EMV SMA falls below the bottom pink standard deviation line.
How To Use:
Enter a long position when the most recent EMV SMA value was below the lower pink stand. dev. line and the current EMV SMA value rises above that
same pink line. That means the previous bar was maroon and the current bar is not.
If the user enables the option to show entry points, a green dot will be plotted when it is time to enter a long position.
Exit the long position when the most recent EMV SMA value was above the upper green standard deviation line and the current EMV SMA value falls
below that same line. If this is true, then the previous bar will be dark green, and the current will be light green.
If the ‘showExits’ option is enabled, then a red dot will be plotted when it is time to exit the long position.
Input Options:
- 'volumeDiv' : Integer. Used in the calculation of Box Ratio.
- 'lenSMA' : Integer. The length of the Simple Moving Average of Ease of Movement Values.
- 'showStDev' : Bool. If true, dotted green and red lines will be shown at values equal to 2.5 * standard deviation of emvSMA and -2.5 * standard deviation of
emvSMA.
- 'showEntries' and 'showExits' : Bool. If true, a green circle will be plotted at long entry points and a red circle will be plotted at long exit points.
- 'changeBgColor': Bool. If true, the background color will change to green when it is time to enter a long position and red when it is time to exit.
Alerts:
- When it is time to enter a long position, an alert with the message "EMV Tracker - Enter Long" is sent.
- When it is time to exit a long position, an alert with the message "EMV Tracker - Exit Long" is sent.
NOTE:
- I usually use this indicator to confirm signals from other indicators rather than relying on it solely.
- Most accurate signals are generated on 30 minutes with the default input values I've set in the script.
Shoot me a message if you have any ideas for modifications or questions.
~ Happy Trading ~
Session Candle Hunter 🎯🎯 Session Candle Hunter — Precision Session Mapping for Smart Traders
Session Candle Hunter 🎯 is a powerful tool designed to help traders identify and track the most important session candle of the trading day—commonly used for liquidity grabs, range mapping, volatility zones, and breakout anticipation.
Whether you trade NY session, London session, or custom time windows, this indicator automatically detects the candle at your chosen New York Time, extracts its high and low, and visually projects these levels into the current session.
🔍 What This Indicator Does
1️⃣ Detects the Key Session Candle
You select:
Hour of the candle (NY Time)
Candle timeframe (1H, 4H, 15m, etc.)
The script automatically:
Identifies the candle when it forms
Stores its High/Low
Prepares levels for visual projection
🎨 2️⃣ Highlights the Candle Zone
Optionally displays a colored zone (box) between the candle’s high and low:
Helps visualize the liquidity pocket
Useful for session traps, expansion moves, and fair value interpretation
You can choose:
Zone color
Whether to show it or not
Whether it should update only for the latest candle
📈 3️⃣ Draws High/Low Lines With Extensions
High and Low of the detected candle can be plotted as:
Standard lines
Or infinitely extended to the right
Great for identifying:
Breakouts
Retests
Range boundaries
Session expansion models
Optional labels display exact price levels.
🕐 4️⃣ Delayed Display Logic
The indicator only shows levels after a user-defined NY time.
For example:
Show lines only after 8:30 NY — perfect for traders who want pre-session levels hidden until relevant.
🔄 5️⃣ “Show Only Last” Mode
A clean, uncluttered mode that removes all historical drawings and only displays:
The latest zone
The latest high/low lines
Latest labels
Perfect for minimal-chart traders.
⚠️ 6️⃣ Alert System
Receive alerts the moment the targeted session candle forms:
“New Candle Detected”
🧾 7️⃣ Info Panel (Top-Left Corner)
Displays:
Target session hour
Display start time
Candle timeframe
Stored High/Low
Indicator name
Always visible and automatically updates.
⭐ Why Traders Love This Tool
✔ Helps visualize major liquidity zones
✔ Works on all markets & timeframes
✔ Perfect for ICT-style session concepts
✔ Helps anticipate session expansion
✔ Automates manual level drawing
✔ Clean visuals with optional minimal mode
BB Breakout-Momentum + Reversion Strategies# BB Breakout-Momentum + Reversion Strategies
## Overview
This indicator combines two complementary Bollinger Band trading strategies that automatically adapt to market conditions. Strategy 1 capitalizes on trending markets with breakout-pullback-momentum setups, while Strategy 2 exploits mean reversion in ranging markets. Advanced filtering using ADX and BB Width ensures each strategy only fires in its optimal market environment.
---
## Strategy 1: Breakout → Pullback → Renewed Momentum (Long B / Short B)
### Best Market Conditions
- **Trending Markets**: ADX ≥ 25
- **High Volatility**: BB Width ≥ 1.0× average
- Directional price action with sustained momentum
### Entry Logic
**Long B (Bullish Breakout):**
1. **Initial Breakout**: Price breaks above upper Bollinger Band with strong momentum
2. **Controlled Pullback**: Price pulls back 1-12 bars but holds above lower band (stays in trend)
3. **Defended Zone**: Pullback creates a support zone based on swing lows (validated by multiple touches)
4. **Renewed Momentum**: Price reclaims with green candle, volume confirmation, bullish MACD
5. **Position Check**: Entry must have cushion below upper band and room to reach targets
**Short B (Bearish Breakdown):**
- Mirror logic for downtrends: breakdown below lower band, pullback stays below upper band, renewed selling pressure
### Risk Management
- **Stop Loss**: Lower of (zone floor/previous low) OR (1.5 × ATR from entry)
- **Targets**:
- T1: Entry + 0.85R (0.85 × 1.5 ATR)
- T2: Entry + 1.40R (1.40 × 1.5 ATR)
- T3: Entry + 2.50R (2.50 × 1.5 ATR)
- T4: Entry + 4.50R (4.50 × 1.5 ATR)
- Risk is calculated using ATR (ATRX = 1.5 ATR), stop uses tighter of structural level (ATRL) or ATRX
---
## Strategy 2: Bollinger Band Mean Reversion (Long R / Short R)
### Best Market Conditions
- **Ranging Markets**: ADX ≤ 20
- **Low Volatility**: BB Width ≤ 0.8× average
- Price oscillating around the mean without sustained trend
### Entry Logic
**Long R (Long Reversion):**
1. **Overextension**: Price breaks below lower Bollinger Band (2 consecutive closes)
2. **Snap Back**: Price crosses back above lower band (re-enters the range)
3. **Entry Window**: Within 2 candles of re-entry, look for:
- **Green candle** (close > open) confirming bullish strength
- Close above previous candle (close > close )
4. **Trigger**: First qualifying candle within 2-bar window executes the trade
**Short R (Short Reversion):**
1. **Overextension**: Price breaks above upper Bollinger Band (2 consecutive closes)
2. **Snap Back**: Price crosses back below upper band (re-enters the range)
3. **Entry Window**: Within 2 candles of re-entry, look for:
- **Red candle** (close < open) confirming bearish pressure
- Close below previous candle (close < close )
4. **Trigger**: First qualifying candle within 2-bar window executes the trade
### Risk Management
- **Stop Loss**: Lower of (previous high/low) OR (1.5 × ATR from entry)
- **Targets**: Same as Strategy 1 (0.85R, 1.4R, 2.5R, 4.5R based on 1.5 ATR)
- Betting on return to Bollinger Band basis (mean)
---
## Advanced Filtering System
### ADX Filter (Average Directional Index)
- **Purpose**: Measures trend strength vs choppy/ranging conditions
- **Trending**: ADX ≥ 25 → Enables Strategy 1 (Breakout)
- **Ranging**: ADX ≤ 20 → Enables Strategy 2 (Reversion)
- **Neutral**: ADX 20-25 → No signals (indecisive market)
### BB Width Filter
- **Purpose**: Confirms volatility expansion/contraction
- **Wide Bands**: Current width ≥ 1.0× 50-bar average → Trending environment
- **Narrow Bands**: Current width ≤ 0.8× 50-bar average → Ranging environment
- **Logic**: Both ADX and BB Width must agree on market state before signaling
### Combined Logic
- **Strategy 1 fires**: When BOTH ADX shows trending AND bands are wide
- **Strategy 2 fires**: When BOTH ADX shows ranging AND bands are narrow
- **Visual Display**: Table at bottom-right shows ADX value, BB Width ratio, and current market state
---
## Visual Elements
### Bollinger Bands
- **Gray line**: 20-period SMA (basis/mean)
- **Green line**: Upper band (basis + 2 standard deviations)
- **Red line**: Lower band (basis - 2 standard deviations)
### Strategy 1 Markers
- **Long B**: Green triangle below bar with "Long B" text
- **Short B**: Orange triangle above bar with "Short B" text
- **Defended Zones**: Green/red boxes showing pullback support/resistance areas
- **Targets**: Green/orange crosses showing T1-T4 and stop loss levels
### Strategy 2 Markers
- **Long R**: Blue label below bar with "Long R" text
- **Short R**: Purple label above bar with "Short R" text
- **Trade Levels**: Horizontal lines extending 50 bars forward
- Blue solid = Entry price
- Red dashed = Stop loss
- Green/Orange dotted = Targets (T1-T4)
### Market State Table
- **ADX**: Current value with color coding (green=trending, orange=ranging, gray=neutral)
- **BB Width**: Ratio vs 50-bar average (e.g., "1.15x" = 15% wider than average)
- **State**: TREND / RANGE / NEUTRAL classification
---
## Settings & Customization
### Bollinger Bands
- **BB Length**: 20 (default) - period for moving average
- **BB Std Dev**: 2.0 (default) - standard deviation multiplier
### ATR & Risk
- **ATR Length**: 14 (default) - period for Average True Range calculation
- All stop losses and targets are derived from 1.5 × ATR
### Trend/Range Filters
- **ADX Length**: 14 (default)
- **ADX Trending Threshold**: 25 (higher = stronger trend required)
- **ADX Ranging Threshold**: 20 (lower = tighter ranging condition)
- **BB Width Average Length**: 50 (period for comparing current width)
- **BB Width Trend Multiplier**: 1.0 (width must be ≥ this × average)
- **BB Width Range Multiplier**: 0.8 (width must be ≤ this × average)
- **Use ADX Filter**: Toggle on/off
- **Use BB Width Filter**: Toggle on/off
### Strategy 1 (Breakout-Momentum)
- **Breakout Lookback**: 15 bars (how far back to search for initial breakout)
- **Min Pullback Bars**: 1 (minimum consolidation period)
- **Max Pullback Bars**: 12 (maximum consolidation period)
- **Show Defended Zone**: Display support/resistance boxes
- **Show Signals**: Display Long B / Short B markers
- **Show Targets**: Display stop loss and target levels
### Strategy 2 (Reversion)
- **Show Signals**: Display Long R / Short R markers
- **Show Trade Levels**: Display entry, stop, and target lines
---
## How to Use This Indicator
### Step 1: Identify Market State
- Check the table in bottom-right corner
- **TREND**: Look for Strategy 1 signals (Long B / Short B)
- **RANGE**: Look for Strategy 2 signals (Long R / Short R)
- **NEUTRAL**: Wait for clearer conditions
### Step 2: Wait for Signal
- Signals only fire when ALL conditions are met (structural + momentum + filters + room-to-target)
- Signals are relatively rare but high-probability
### Step 3: Execute Trade
- **Entry**: Close of signal candle
- **Stop Loss**: Shown as red cross (Strategy 1) or red dashed line (Strategy 2)
- **Targets**: Scale out at T1, T2, T3, T4 or hold for maximum R:R
### Step 4: Management
- Consider moving stop to breakeven after T1
- Trail stop using swing lows/highs in Strategy 1
- Exit full position at T2-T3 in Strategy 2 (mean reversion has limited upside)
---
## Key Principles
### Why This Works
1. **Market Adaptation**: Uses right strategy for right conditions (trend vs range)
2. **Confluence**: Multiple confirmations required (structure + momentum + volatility + room)
3. **Risk-Defined**: Every trade has pre-calculated stop and targets based on ATR
4. **Probability**: Filters reduce noise and increase win rate by waiting for ideal setups
### Common Pitfalls to Avoid
- ❌ Taking signals in NEUTRAL market state (indicators disagree)
- ❌ Overriding the stop loss (it's calculated for a reason)
- ❌ Expecting signals on every swing (quality over quantity)
- ❌ Using Strategy 1 in ranging markets or Strategy 2 in trending markets
- ❌ Ignoring the room-to-target check (signal won't fire if targets are blocked)
### Complementary Analysis
This indicator works best when combined with:
- Higher timeframe trend analysis
- Key support/resistance levels
- Volume analysis
- Market structure (swing highs/lows)
- Risk management rules (position sizing, max daily loss, etc.)
---
## Technical Details
### Indicators Used
- **Bollinger Bands**: 20-period SMA ± 2 standard deviations
- **ATR**: 14-period Average True Range for volatility measurement
- **ADX**: 14-period Average Directional Index for trend strength
- **EMA**: 10 and 20-period exponential moving averages (Strategy 1 filter)
- **MACD**: 12/26/9 settings (Strategy 1 momentum confirmation)
- **Volume**: Compared to 15-bar average (Strategy 1 confirmation)
### Calculation Methodology
- **ATRL** (Structural Risk): Previous swing high/low or defended zone boundary
- **ATRX** (ATR Risk): 1.5 × 14-period ATR from entry price
- **Stop Loss**: Minimum of ATRL and ATRX (tightest protection)
- **Targets**: Always calculated from ATRX (consistent R-multiples)
- **BB Width Ratio**: Current BB width ÷ 50-period SMA of BB width
---
## Performance Notes
### Strengths
- Adapts to changing market conditions automatically
- Clear, objective entry and exit criteria
- Pre-defined risk on every trade
- Filters reduce false signals significantly
- Works across multiple timeframes and instruments
### Limitations
- Signals are infrequent (by design - quality over quantity)
- Requires patience to wait for all conditions to align
- May miss explosive moves if pullback doesn't form properly (Strategy 1)
- Ranging markets can transition to trending (Strategy 2 risk)
- Filters may delay entry in fast-moving markets
### Best Timeframes
- **Strategy 1**: 1H, 4H, Daily (needs time for proper pullback structure)
- **Strategy 2**: 15M, 30M, 1H (mean reversion works best intraday)
- Both strategies can work on any timeframe if market conditions are right
### Best Instruments
- **Liquid markets**: Major stocks, indices, forex pairs, liquid crypto
- **Sufficient volatility**: ATR should be meaningful relative to price
- **Clear trend/range cycles**: Markets that respect technical levels
---
## IMPORTANT DISCLAIMER
### Risk Warning
**TRADING INVOLVES SUBSTANTIAL RISK OF LOSS AND IS NOT SUITABLE FOR ALL INVESTORS.**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment advice, trading advice, or any other sort of advice. You should not treat any of the indicator's content as such.
### No Guarantee of Profit
Past performance is not indicative of future results. No trading strategy, including this indicator, can guarantee profits or protect against losses. The market is inherently unpredictable and all trading involves risk.
### User Responsibility
- **Do Your Own Research**: Always conduct your own analysis before making trading decisions
- **Test First**: Backtest and paper trade this strategy before risking real capital
- **Risk Management**: Never risk more than you can afford to lose
- **Position Sizing**: Use appropriate position sizes relative to your account
- **Stop Losses**: Always use stop losses and respect them
- **Market Conditions**: Understand that market conditions change and past behavior may not repeat
### No Liability
The creator of this indicator accepts no liability for any financial losses incurred through the use of this tool. All trading decisions are made at your own risk. You are solely responsible for evaluating the merits and risks associated with the use of any trading systems, signals, or content provided.
### Not Financial Advice
This indicator does not take into account your personal financial situation, investment objectives, risk tolerance, or specific needs. You should consult with a licensed financial advisor before making any investment decisions.
### Technical Limitations
- Indicators can repaint or lag in real-time
- Past signals may look different than real-time signals
- Code bugs or errors may exist despite testing
- TradingView platform limitations may affect functionality
### Market Risks
- Markets can gap, causing stops to be executed at worse prices
- Slippage and commissions can significantly impact results
- High volatility can cause unexpected losses
- Counterparty risk exists in all leveraged products
---
## Version History
- **v1.0**: Initial release combining breakout-momentum and mean reversion strategies
- Includes ADX and BB Width filtering
- ATRL/ATRX risk calculation system
- 2-candle entry window for reversion trades
---
## Credits & License
This indicator combines concepts from classical technical analysis including Bollinger Bands (John Bollinger), ATR (Welles Wilder), and ADX (Welles Wilder). The specific implementation and combination of filters is original work.
**Use at your own risk. Trade responsibly.**
---
*For questions, suggestions, or to report bugs, please comment below or contact the author.*
**Remember: The best indicator is the one between your ears. Use this tool as part of a comprehensive trading plan, not as a standalone solution.**
BAY_PIVOT S/R(4 Full Lines + ALL Labels)//@version=5
indicator("BAY_PIVOT S/R(4 Full Lines + ALL Labels)", overlay=true, max_labels_count=500, max_lines_count=500)
// ────────────────────── TOGGLES ──────────────────────
showPivot = input.bool(true, "Show Pivot (Full Line + Label)")
showTarget = input.bool(true, "Show Target (Full Line + Label)")
showLast = input.bool(true, "Show Last Close (Full Line + Label)")
showPrevClose = input.bool(true, "Show Previous Close (Full Line + Label)")
useBarchartLast = input.bool(true, "Use Barchart 'Last' (Settlement Price)")
showR1R2R3 = input.bool(true, "Show R1 • R2 • R3")
showS1S2S3 = input.bool(true, "Show S1 • S2 • S3")
showStdDev = input.bool(true, "Show ±1σ ±2σ ±3σ")
showFib4W = input.bool(true, "Show 4-Week Fibs")
showFib13W = input.bool(true, "Show 13-Week Fibs")
showMonthHL = input.bool(true, "Show 1M High / Low")
showEntry1 = input.bool(false, "Show Manual Entry 1")
showEntry2 = input.bool(false, "Show Manual Entry 2")
entry1 = input.float(0.0, "Manual Entry 1", step=0.25)
entry2 = input.float(0.0, "Manual Entry 2", step=0.25)
stdLen = input.int(20, "StdDev Length", minval=1)
fib4wBars = input.int(20, "4W Fib Lookback")
fib13wBars = input.int(65, "13W Fib Lookback")
// ────────────────────── DAILY CALCULATIONS ──────────────────────
high_y = request.security(syminfo.tickerid, "D", high , lookahead=barmerge.lookahead_on)
low_y = request.security(syminfo.tickerid, "D", low , lookahead=barmerge.lookahead_on)
close_y = request.security(syminfo.tickerid, "D", close , lookahead=barmerge.lookahead_on)
pivot = (high_y + low_y + close_y) / 3
r1 = pivot + 0.382 * (high_y - low_y)
r2 = pivot + 0.618 * (high_y - low_y)
r3 = pivot + (high_y - low_y)
s1 = pivot - 0.382 * (high_y - low_y)
s2 = pivot - 0.618 * (high_y - low_y)
s3 = pivot - (high_y - low_y)
prevClose = close_y
last = useBarchartLast ? request.security(syminfo.tickerid, "D", close , lookahead=barmerge.lookahead_off) : close
target = pivot + (pivot - prevClose)
// StdDev + Fibs + Monthly (unchanged)
basis = ta.sma(close, stdLen)
dev = ta.stdev(close, stdLen)
stdRes1 = basis + dev
stdRes2 = basis + dev*2
stdRes3 = basis + dev*3
stdSup1 = basis - dev
stdSup2 = basis - dev*2
stdSup3 = basis - dev*3
high4w = ta.highest(high, fib4wBars)
low4w = ta.lowest(low, fib4wBars)
fib382_4w = high4w - (high4w - low4w) * 0.382
fib50_4w = high4w - (high4w - low4w) * 0.500
high13w = ta.highest(high, fib13wBars)
low13w = ta.lowest(low, fib13wBars)
fib382_13w_high = high13w - (high13w - low13w) * 0.382
fib50_13w = high13w - (high13w - low13w) * 0.500
fib382_13w_low = low13w + (high13w - low13w) * 0.382
monthHigh = ta.highest(high, 30)
monthLow = ta.lowest(low, 30)
// ────────────────────── COLORS ──────────────────────
colRed = color.rgb(255,0,0)
colLime = color.rgb(0,255,0)
colYellow = color.rgb(255,255,0)
colOrange = color.rgb(255,165,0)
colWhite = color.rgb(255,255,255)
colGray = color.rgb(128,128,128)
colMagenta = color.rgb(255,0,255)
colPink = color.rgb(233,30,99)
colCyan = color.rgb(0,188,212)
colBlue = color.rgb(0,122,255)
colPurple = color.rgb(128,0,128)
colRed50 = color.new(colRed,50)
colGreen50 = color.new(colLime,50)
// ────────────────────── 4 KEY FULL LINES ──────────────────────
plot(showPivot ? pivot : na, title="PIVOT", color=colYellow, linewidth=3, style=plot.style_linebr)
plot(showTarget ? target : na, title="TARGET", color=colOrange, linewidth=2, style=plot.style_linebr)
plot(showLast ? last : na, title="LAST", color=colWhite, linewidth=2, style=plot.style_linebr)
plot(showPrevClose ? prevClose : na, title="PREV CLOSE",color=colGray, linewidth=1, style=plot.style_linebr)
// ────────────────────── LABELS FOR ALL 4 KEY LEVELS (SAME STYLE AS OTHERS) ──────────────────────
f_label(price, txt, bgColor, txtColor) =>
if barstate.islast and not na(price)
label.new(bar_index, price, txt, style=label.style_label_left, color=bgColor, textcolor=txtColor, size=size.small)
if barstate.islast
showPivot ? f_label(pivot, "PIVOT\n" + str.tostring(pivot, "#.##"), colYellow, color.black) : na
showTarget ? f_label(target, "TARGET\n" + str.tostring(target, "#.##"), colOrange, color.white) : na
showLast ? f_label(last, "LAST\n" + str.tostring(last, "#.##"), colWhite, color.black) : na
showPrevClose ? f_label(prevClose, "PREV CLOSE\n"+ str.tostring(prevClose, "#.##"), colGray, color.white) : na
// ────────────────────── OTHER LEVELS – line stops at label ──────────────────────
f_level(p, txt, tc, lc, w=1) =>
if barstate.islast and not na(p)
lbl = label.new(bar_index, p, txt, style=label.style_label_left, color=lc, textcolor=tc, size=size.small)
line.new(bar_index-400, p, label.get_x(lbl), p, extend=extend.none, color=lc, width=w)
if barstate.islast
if showR1R2R3
f_level(r1, "R1\n" + str.tostring(r1, "#.##"), color.white, colRed)
f_level(r2, "R2\n" + str.tostring(r2, "#.##"), color.white, colRed)
f_level(r3, "R3\n" + str.tostring(r3, "#.##"), color.white, colRed, 2)
if showS1S2S3
f_level(s1, "S1\n" + str.tostring(s1, "#.##"), color.black, colLime)
f_level(s2, "S2\n" + str.tostring(s2, "#.##"), color.black, colLime)
f_level(s3, "S3\n" + str.tostring(s3, "#.##"), color.black, colLime, 2)
if showStdDev
f_level(stdRes1, "+1σ\n" + str.tostring(stdRes1, "#.##"), color.white, colPink)
f_level(stdRes2, "+2σ\n" + str.tostring(stdRes2, "#.##"), color.white, colPink)
f_level(stdRes3, "+3σ\n" + str.tostring(stdRes3, "#.##"), color.white, colPink, 2)
f_level(stdSup1, "-1σ\n" + str.tostring(stdSup1, "#.##"), color.white, colCyan)
f_level(stdSup2, "-2σ\n" + str.tostring(stdSup2, "#.##"), color.white, colCyan)
f_level(stdSup3, "-3σ\n" + str.tostring(stdSup3, "#.##"), color.white, colCyan, 2)
if showFib4W
f_level(fib382_4w, "38.2% 4W\n" + str.tostring(fib382_4w, "#.##"), color.white, colMagenta)
f_level(fib50_4w, "50% 4W\n" + str.tostring(fib50_4w, "#.##"), color.white, colMagenta)
if showFib13W
f_level(fib382_13w_high, "38.2% 13W High\n" + str.tostring(fib382_13w_high, "#.##"), color.white, colMagenta)
f_level(fib50_13w, "50% 13W\n" + str.tostring(fib50_13w, "#.##"), color.white, colMagenta)
f_level(fib382_13w_low, "38.2% 13W Low\n" + str.tostring(fib382_13w_low, "#.##"), color.white, colMagenta)
if showMonthHL
f_level(monthHigh, "1M HIGH\n" + str.tostring(monthHigh, "#.##"), color.white, colRed50, 2)
f_level(monthLow, "1M LOW\n" + str.tostring(monthLow, "#.##"), color.white, colGreen50, 2)
// Manual entries
plot(showEntry1 and entry1 > 0 ? entry1 : na, "Entry 1", color=colBlue, linewidth=2, style=plot.style_linebr)
plot(showEntry2 and entry2 > 0 ? entry2 : na, "Entry 2", color=colPurple, linewidth=2, style=plot.style_linebr)
// Background
bgcolor(close > pivot ? color.new(color.blue, 95) : color.new(color.red, 95))
new_youtube_strategy//@version=5
strategy("Dow + Homma 1m Scalper (15m filter)", overlay=true, margin_long=100, margin_short=100, initial_capital=10000)
//===== INPUTS =====
maLen = input.int(50, "Trend SMA Length", minval=5)
htf_tf = input.timeframe("15", "Higher TF")
priceTolPct = input.float(0.05, "SR tolerance %", step=0.01)
wickFactor = input.float(2.0, "Hammer/ShootingStar wick factor", step=0.1)
dojiThresh = input.float(0.1, "Doji body % of range", step=0.01)
risk_RR = input.float(2.0, "Reward:Risk", step=0.1)
capitalRiskPct = input.float(1.0, "Risk % of equity per trade", step=0.1)
//===== 1m TREND (SMA) =====
sma1 = ta.sma(close, maLen)
sma1Up = sma1 > sma1
sma1Down = sma1 < sma1
uptrend1 = close > sma1 and sma1Up
downtrend1 = close < sma1 and sma1Down
//===== 15m TREND VIA request.security =====
sma15 = request.security(syminfo.tickerid, htf_tf, ta.sma(close, maLen), lookahead=barmerge.lookahead_off)
sma15Up = sma15 > sma15
sma15Down = sma15 < sma15
uptrend15 = close > sma15 and sma15Up
downtrend15 = close < sma15 and sma15Down
//===== SWING HIGHS/LOWS (LOCAL EXTREMA) =====
var int left = 3
var int right = 3
swHigh = ta.pivothigh(high, left, right)
swLow = ta.pivotlow(low, left, right)
//===== SR FLIP LEVELS =====
var float srSupport = na
var float srResistance = na
// when a swing high is broken -> new support
if not na(swHigh)
if close > swHigh
srSupport := swHigh
// when a swing low is broken -> new resistance
if not na(swLow)
if close < swLow
srResistance := swLow
//===== CANDLE METRICS =====
body = math.abs(close - open)
cRange = high - low
upperW = high - math.max(open, close)
lowerW = math.min(open, close) - low
isBull() => close > open
isBear() => close < open
bullHammer() =>
cRange > 0 and
isBull() and
lowerW >= wickFactor * body and
upperW <= body
bearShootingStar() =>
cRange > 0 and
isBear() and
upperW >= wickFactor * body and
lowerW <= body
isDoji() =>
cRange > 0 and body <= dojiThresh * cRange
bullEngulfing() =>
isBear() and isBull() and
open <= close and close >= open
bearEngulfing() =>
isBull() and isBear() and
open >= close and close <= open
//===== SR PROXIMITY =====
tol = priceTolPct * 0.01 * close
nearSupport = not na(srSupport) and math.abs(close - srSupport) <= tol
nearResistance = not na(srResistance) and math.abs(close - srResistance) <= tol
//===== SIGNAL CONDITIONS =====
bullCandle = bullHammer() or isDoji() or bullEngulfing()
bearCandle = bearShootingStar() or isDoji() or bearEngulfing()
longTrendOK = uptrend1 and uptrend15
shortTrendOK = downtrend1 and downtrend15
longSignal = longTrendOK and nearSupport and bullCandle
shortSignal = shortTrendOK and nearResistance and bearCandle
//===== POSITION SIZING (IN RISK UNITS) =====
var float lastEquity = strategy.equity
riskCapital = strategy.equity * (capitalRiskPct * 0.01)
//===== ENTRY / EXIT PRICES =====
longStop = math.min(low, nz(srSupport, low))
longRisk = close - longStop
longTP = close + risk_RR * longRisk
shortStop = math.max(high, nz(srResistance, high))
shortRisk = shortStop - close
shortTP = close - risk_RR * shortRisk
// qty in contracts (approx; assumes price * qty ≈ capital used)
longQty = longRisk > 0 ? riskCapital / longRisk : 0.0
shortQty = shortRisk > 0 ? riskCapital / shortRisk : 0.0
//===== EXECUTION =====
if longSignal and longRisk > 0 and longQty > 0
strategy.entry("Long", strategy.long, qty=longQty)
strategy.exit("Long TP/SL", from_entry="Long", stop=longStop, limit=longTP)
if shortSignal and shortRisk > 0 and shortQty > 0
strategy.entry("Short", strategy.short, qty=shortQty)
strategy.exit("Short TP/SL", from_entry="Short", stop=shortStop, limit=shortTP)
//===== PLOTS =====
plot(sma1, color=color.orange, title="SMA 1m")
plot(sma15, color=color.blue, title="HTF SMA (15m)")
plot(srSupport, "SR Support", color=color.new(color.green, 50), style=plot.style_linebr)
plot(srResistance,"SR Resistance",color=color.new(color.red, 50), style=plot.style_linebr)
// Visual debug for signals
plotshape(longSignal, title="Long Signal", style=shape.triangleup, location=location.belowbar, color=color.lime, size=size.tiny)
plotshape(shortSignal, title="Short Signal", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.tiny)
Omega Correlation [OmegaTools]Omega Correlation (Ω CRR) is a cross-asset analytics tool designed to quantify both the strength of the relationship between two instruments and the tendency of one to move ahead of the other. It is intended for traders who work with indices, futures, FX, commodities, equities and ETFs, and who require something more robust than a simple linear correlation line.
The indicator operates in two distinct modes, selected via the “Show” parameter: Correlation and Anticipation. In Correlation mode, the script focuses on how tightly the current chart and the chosen second asset move together. In Anticipation mode, it shifts to a lead–lag perspective and estimates whether the second asset tends to behave as a leader or a follower relative to the symbol on the chart.
In both modes, the core inputs are the chart symbol and a user-selected second symbol. Internally, both assets are transformed into normalized log-returns: the script computes logarithmic returns, removes short-term mean and scales by realized volatility, then clips extreme values. This normalisation allows the tool to compare behaviour across assets with different price levels and volatility profiles.
In Correlation mode, the indicator computes a composite correlation score that typically ranges between –1 and +1. Values near +1 indicate strong and persistent positive co-movement, values near zero indicate an unstable or weak link, and values near –1 indicate a stable anti-correlation regime. The composite score is constructed from three components.
The first component is a normalized return co-movement measure. After transforming both instruments into normalized returns, the script evaluates how similar those returns are bar by bar. When the two assets consistently deliver returns of similar sign and magnitude, this component is high and positive. When they frequently diverge or move in opposite directions, it becomes negative. This captures short-term co-movement in a volatility-adjusted way.
The second component focuses on high–low swing alignment. Rather than looking only at closes, it examines the direction of changes in highs and lows for each bar. If both instruments are printing higher highs and higher lows together, or lower highs and lower lows together, the swing structure is considered aligned. Persistent alignment contributes positively to the correlation score, while repeated mismatches between the swing directions reduce it. This helps differentiate between superficial price noise and structural similarity in trend behaviour.
The third component is a classical Pearson correlation on closing prices, computed over a longer lookback. This serves as a stabilising backbone that summarises general co-movement over a broader window. By combining normalized return co-movement, swing alignment and standard price correlation with calibrated weights, the Correlation mode provides a richer view than a single linear measure, capturing both short-term dynamic interaction and longer-term structural linkage.
In Anticipation mode, Omega Correlation estimates whether the second asset tends to lead or lag the current chart. The output is again a continuous score around the range. Positive values suggest that the second asset is acting more as a leader, with its past moves bearing informative value for subsequent moves of the chart symbol. Negative values indicate that the second asset behaves more like a laggard or follower. Values near zero suggest that no stable lead–lag structure can be identified.
The anticipation score is built from four elements inspired by quantitative lead–lag and price discovery analysis. The first element is a residual lead correlation, conceptually similar to Granger-style logic. The script first measures how much of the chart symbol’s normalized returns can be explained by its own lagged values. It then removes that component and studies the correlation between the residuals and lagged returns of the second asset. If the second asset’s past returns consistently explain what the chart symbol does beyond its own autoregressive behaviour, this residual correlation becomes significantly positive.
The second element is an asymmetric lead–lag structure measure. It compares the strength of relationships in both directions across multiple lags: the correlation of the current symbol with lagged versions of the second asset (candidate leader) versus the correlation of lagged values of the current symbol with the present values of the second asset. If the forward direction (second asset leading the first) is systematically stronger than the backward direction, the structure is skewed toward genuine leadership of the second asset.
The third element is a relative price discovery score, constructed by building a dynamic hedge ratio between the two prices and defining a spread. The indicator looks at how changes in each asset contribute to correcting deviations in this spread over time. When the chart symbol tends to do most of the adjustment while the second asset remains relatively stable, it suggests that the second asset is taking a greater role in determining the equilibrium price and the chart symbol is adjusting to it. The difference in adjustment intensity between the two instruments is summarised into a single score.
The fourth element is a breakout follow-through causality component. The script scans for breakout events on the second asset, where its price breaks out of a recent high or low range while the chart symbol has not yet done so. It then evaluates whether the chart symbol subsequently confirms the breakout direction, remains neutral, or moves against it. Events where the second asset breaks and the first asset later follows in the same direction add positive contribution, while failed or contrarian follow-through reduce this component. The contribution is also lightly modulated by the strength of the breakout, via the underlying normalized return.
The four elements of the Anticipation mode are combined into a single leading correlation score, providing a compact and interpretable measure of whether the second asset currently behaves as an effective early signal for the symbol you trade.
To aid interpretation, Omega Correlation builds dynamic bands around the active series (correlation or anticipation). It estimates a long-term central tendency and a typical deviation around it, plotting upper and lower bands that highlight unusually high or low values relative to recent history. These bands can be used to distinguish routine fluctuations from genuinely extreme regimes.
The script also computes percentile-based levels for the correlation series and uses them to track two special price levels on the main chart: lost correlation levels and gained correlation levels. When the correlation drops below an upper percentile threshold, the current price is stored as a lost correlation level and plotted as a horizontal line. When the correlation rises above a lower percentile threshold, the current price is stored as a gained correlation level. These levels mark zones where a historically strong relationship between the two markets broke down or re-emerged, and can be used to frame divergence, convergence and spread opportunities.
An information panel summarises, in real time, whether the second asset is behaving more as a leading, lagging or independent instrument according to the anticipation score, and suggests whether the current environment is more conducive to de-alignment, re-alignment or classic spread behaviour based on the correlation regime. This makes the tool directly interpretable even for users who are not familiar with all the underlying statistical details.
Typical applications for Omega Correlation include intermarket analysis (for example, index vs index, commodity vs related equity sector, FX vs bonds), dynamic hedge sizing, regime detection for algorithmic strategies, and the identification of lead–lag structures where a macro driver or benchmark can be monitored as an early signal for the instrument actually traded. The indicator can be applied across intraday and higher timeframes, with the understanding that the strength and nature of relationships will differ across horizons.
Omega Correlation is designed as an advanced analytical framework, not as a standalone trading system. Correlation and lead–lag relationships are statistical in nature and can change abruptly, especially around macro events, regime shifts or liquidity shocks. A positive anticipation reading does not guarantee that the second asset will always move first, and a high correlation regime can break without warning. All outputs of this tool should be combined with independent analysis, sound risk management and, when appropriate, backtesting or forward testing on the user’s specific instruments and timeframes.
The intention behind Omega Correlation is to bring techniques inspired by quantitative research, such as normalized return analysis, residual correlation, asymmetric lead–lag structure, price discovery logic and breakout event studies, into an accessible TradingView indicator. It is intended for traders who want a structured, professional way to understand how markets interact and to incorporate that information into their discretionary or systematic decision-making processes.
لbsm15// This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) creativecommons.org
// © LuxAlgo
//@version=5
indicator("لbsm15", overlay = true, max_lines_count = 500, max_boxes_count = 500, max_bars_back = 3000)
//------------------------------------------------------------------------------
//Settings
//-----------------------------------------------------------------------------{
liqGrp = 'Liquidity Detection'
liqLen = input.int (7, title = 'Detection Length', minval = 3, maxval = 13, inline = 'LIQ', group = liqGrp)
liqMar = 10 / input.float (6.9, 'Margin', minval = 4, maxval = 9, step = 0.1, inline = 'LIQ', group = liqGrp)
liqBuy = input.bool (true, 'Buyside Liquidity Zones, Margin', inline = 'Buyside', group = liqGrp)
marBuy = input.float(2.3, '', minval = 1.5, maxval = 10, step = .1, inline = 'Buyside', group = liqGrp)
cLIQ_B = input.color (color.new(#4caf50, 0), '', inline = 'Buyside', group = liqGrp)
liqSel = input.bool (true, 'Sellside Liquidity Zones, Margin', inline = 'Sellside', group = liqGrp)
marSel = input.float(2.3, '', minval = 1.5, maxval = 10, step = .1, inline = 'Sellside', group = liqGrp)
cLIQ_S = input.color (color.new(#f23645, 0), '', inline = 'Sellside', group = liqGrp)
lqVoid = input.bool (false, 'Liquidity Voids, Bullish', inline = 'void', group = liqGrp)
cLQV_B = input.color (color.new(#4caf50, 0), '', inline = 'void', group = liqGrp)
cLQV_S = input.color (color.new(#f23645, 0), 'Bearish', inline = 'void', group = liqGrp)
lqText = input.bool (false, 'Label', inline = 'void', group = liqGrp)
mode = input.string('Present', title = 'Mode', options = , inline = 'MOD', group = liqGrp)
visLiq = input.int (3, ' # Visible Levels', minval = 1, maxval = 50, inline = 'MOD', group = liqGrp)
//-----------------------------------------------------------------------------}
//General Calculations
//-----------------------------------------------------------------------------{
maxSize = 50
atr = ta.atr(10)
atr200 = ta.atr(200)
per = mode == 'Present' ? last_bar_index - bar_index <= 500 : true
//-----------------------------------------------------------------------------}
//User Defined Types
//-----------------------------------------------------------------------------{
// @type used to store pivot high/low data
//
// @field d (array) The array where the trend direction is to be maintained
// @field x (array) The array where the bar index value of pivot high/low is to be maintained
// @field y (array) The array where the price value of pivot high/low is to be maintained
type ZZ
int d
int x
float y
// @type bar properties with their values
//
// @field o (float) open price of the bar
// @field h (float) high price of the bar
// @field l (float) low price of the bar
// @field c (float) close price of the bar
// @field i (int) index of the bar
type bar
float o = open
float h = high
float l = low
float c = close
int i = bar_index
// @type liquidity object definition
//
// @field bx (box) box maitaing the liquity level margin extreme levels
// @field bxz (box) box maitaing the liquity zone margin extreme levels
// @field bxt (box) box maitaing the labels
// @field brZ (bool) mainains broken zone status
// @field brL (bool) mainains broken level status
// @field ln (line) maitaing the liquity level line
// @field lne (line) maitaing the liquity extended level line
type liq
box bx
box bxz
box bxt
bool brZ
bool brL
line ln
line lne
//-----------------------------------------------------------------------------}
//Variables
//-----------------------------------------------------------------------------{
var ZZ aZZ = ZZ.new(
array.new (maxSize, 0),
array.new (maxSize, 0),
array.new (maxSize, na)
)
bar b = bar.new()
var liq b_liq_B = array.new (1, liq.new(box(na), box(na), box(na), false, false, line(na), line(na)))
var liq b_liq_S = array.new (1, liq.new(box(na), box(na), box(na), false, false, line(na), line(na)))
var b_liq_V = array.new_box()
var int dir = na, var int x1 = na, var float y1 = na, var int x2 = na, var float y2 = na
//-----------------------------------------------------------------------------}
//Functions/methods
//-----------------------------------------------------------------------------{
// @function maintains arrays
// it prepends a `value` to the arrays and removes their oldest element at last position
// @param aZZ (UDT, array, array>) The UDT obejct of arrays
// @param _d (array) The array where the trend direction is maintained
// @param _x (array) The array where the bar index value of pivot high/low is maintained
// @param _y (array) The array where the price value of pivot high/low is maintained
//
// @returns none
method in_out(ZZ aZZ, int _d, int _x, float _y) =>
aZZ.d.unshift(_d), aZZ.x.unshift(_x), aZZ.y.unshift(_y), aZZ.d.pop(), aZZ.x.pop(), aZZ.y.pop()
// @function (build-in) sets the maximum number of bars that is available for historical reference
max_bars_back(time, 1000)
//-----------------------------------------------------------------------------}
//Calculations
//-----------------------------------------------------------------------------{
x2 := b.i - 1
ph = ta.pivothigh(liqLen, 1)
pl = ta.pivotlow (liqLen, 1)
if ph
dir := aZZ.d.get(0)
x1 := aZZ.x.get(0)
y1 := aZZ.y.get(0)
y2 := nz(b.h )
if dir < 1
aZZ.in_out(1, x2, y2)
else
if dir == 1 and ph > y1
aZZ.x.set(0, x2), aZZ.y.set(0, y2)
if per
count = 0
st_P = 0.
st_B = 0
minP = 0.
maxP = 10e6
for i = 0 to maxSize - 1
if aZZ.d.get(i) == 1
if aZZ.y.get(i) > ph + (atr / liqMar)
break
else
if aZZ.y.get(i) > ph - (atr / liqMar) and aZZ.y.get(i) < ph + (atr / liqMar)
count += 1
st_B := aZZ.x.get(i)
st_P := aZZ.y.get(i)
if aZZ.y.get(i) > minP
minP := aZZ.y.get(i)
if aZZ.y.get(i) < maxP
maxP := aZZ.y.get(i)
if count > 2
getB = b_liq_B.get(0)
if st_B == getB.bx.get_left()
getB.bx.set_top(math.avg(minP, maxP) + (atr / liqMar))
getB.bx.set_rightbottom(b.i + 10, math.avg(minP, maxP) - (atr / liqMar))
else
b_liq_B.unshift(
liq.new(
box.new(st_B, math.avg(minP, maxP) + (atr / liqMar), b.i + 10, math.avg(minP, maxP) - (atr / liqMar), bgcolor=color(na), border_color=color(na)),
box.new(na, na, na, na, bgcolor = color(na), border_color = color(na)),
box.new(st_B, st_P, b.i + 10, st_P, text = 'Buyside liquidity', text_size = size.tiny, text_halign = text.align_left, text_valign = text.align_bottom, text_color = color.new(cLIQ_B, 25), bgcolor = color(na), border_color = color(na)),
false,
false,
line.new(st_B , st_P, b.i - 1, st_P, color = color.new(cLIQ_B, 0)),
line.new(b.i - 1, st_P, na , st_P, color = color.new(cLIQ_B, 0), style = line.style_dotted))
)
alert('buyside liquidity level detected/updated for ' + syminfo.ticker)
if b_liq_B.size() > visLiq
getLast = b_liq_B.pop()
getLast.bx.delete()
getLast.bxz.delete()
getLast.bxt.delete()
getLast.ln.delete()
getLast.lne.delete()
if pl
dir := aZZ.d.get (0)
x1 := aZZ.x.get (0)
y1 := aZZ.y.get (0)
y2 := nz(b.l )
if dir > -1
aZZ.in_out(-1, x2, y2)
else
if dir == -1 and pl < y1
aZZ.x.set(0, x2), aZZ.y.set(0, y2)
if per
count = 0
st_P = 0.
st_B = 0
minP = 0.
maxP = 10e6
for i = 0 to maxSize - 1
if aZZ.d.get(i) == -1
if aZZ.y.get(i) < pl - (atr / liqMar)
break
else
if aZZ.y.get(i) > pl - (atr / liqMar) and aZZ.y.get(i) < pl + (atr / liqMar)
count += 1
st_B := aZZ.x.get(i)
st_P := aZZ.y.get(i)
if aZZ.y.get(i) > minP
minP := aZZ.y.get(i)
if aZZ.y.get(i) < maxP
maxP := aZZ.y.get(i)
if count > 2
getB = b_liq_S.get(0)
if st_B == getB.bx.get_left()
getB.bx.set_top(math.avg(minP, maxP) + (atr / liqMar))
getB.bx.set_rightbottom(b.i + 10, math.avg(minP, maxP) - (atr / liqMar))
else
b_liq_S.unshift(
liq.new(
box.new(st_B, math.avg(minP, maxP) + (atr / liqMar), b.i + 10, math.avg(minP, maxP) - (atr / liqMar), bgcolor=color(na), border_color=color(na)),
box.new(na, na, na, na, bgcolor=color(na), border_color=color(na)),
box.new(st_B, st_P, b.i + 10, st_P, text = 'Sellside liquidity', text_size = size.tiny, text_halign = text.align_left, text_valign = text.align_top, text_color = color.new(cLIQ_S, 25), bgcolor=color(na), border_color=color(na)),
false,
false,
line.new(st_B , st_P, b.i - 1, st_P, color = color.new(cLIQ_S, 0)),
line.new(b.i - 1, st_P, na , st_P, color = color.new(cLIQ_S, 0), style = line.style_dotted))
)
alert('sellside liquidity level detected/updated for ' + syminfo.ticker)
if b_liq_S.size() > visLiq
getLast = b_liq_S.pop()
getLast.bx.delete()
getLast.bxz.delete()
getLast.bxt.delete()
getLast.ln.delete()
getLast.lne.delete()
for i = 0 to b_liq_B.size() - 1
x = b_liq_B.get(i)
if not x.brL
x.lne.set_x2(b.i)
if b.h > x.bx.get_top()
x.brL := true
x.brZ := true
alert('buyside liquidity level breached for ' + syminfo.ticker)
x.bxz.set_lefttop(b.i - 1, math.min(x.ln.get_y1() + marBuy * (atr), b.h))
x.bxz.set_rightbottom(b.i + 1, x.ln.get_y1())
x.bxz.set_bgcolor(color.new(cLIQ_B, liqBuy ? 73 : 100))
else if x.brZ
if b.l > x.ln.get_y1() - marBuy * (atr) and b.h < x.ln.get_y1() + marBuy * (atr)
x.bxz.set_right(b.i + 1)
x.bxz.set_top(math.max(b.h, x.bxz.get_top()))
if liqBuy
x.lne.set_x2(b.i + 1)
else
x.brZ := false
for i = 0 to b_liq_S.size() - 1
x = b_liq_S.get(i)
if not x.brL
x.lne.set_x2(b.i)
if b.l < x.bx.get_bottom()
x.brL := true
x.brZ := true
alert('sellside liquidity level breached for ' + syminfo.ticker)
x.bxz.set_lefttop(b.i - 1, x.ln.get_y1())
x.bxz.set_rightbottom(b.i + 1, math.max(x.ln.get_y1() - marSel * (atr), b.l))
x.bxz.set_bgcolor(color.new(cLIQ_S, liqSel ? 73 : 100))
else if x.brZ
if b.l > x.ln.get_y1() - marSel * (atr) and b.h < x.ln.get_y1() + marSel * (atr)
x.bxz.set_rightbottom(b.i + 1, math.min(b.l, x.bxz.get_bottom()))
if liqSel
x.lne.set_x2(b.i + 1)
else
x.brZ := false
if lqVoid and per
bull = b.l - b.h > atr200 and b.l > b.h and b.c > b.h
bear = b.l - b.h > atr200 and b.h < b.l and b.c < b.l
if bull
l = 13
if bull
st = math.abs(b.l - b.l ) / l
for i = 0 to l - 1
array.push(b_liq_V, box.new(b.i - 2, b.l + i * st, b.i, b.l + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_B, 90) ))
else
st = math.abs(b.l - b.h ) / l
for i = 0 to l - 1
if lqText and i == 0
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, text = 'Liquidity Void ', text_size = size.tiny, text_halign = text.align_right, text_valign = text.align_bottom, text_color = na, border_color = na, bgcolor = color.new(cLQV_B, 90) ))
else
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_B, 90) ))
if bear
l = 13
if bear
st = math.abs(b.h - b.h) / l
for i = 0 to l - 1
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_S, 90) ))
else
st = math.abs(b.l - b.h) / l
for i = 0 to l - 1
if lqText and i == l - 1
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, text = 'Liquidity Void ', text_size = size.tiny, text_halign = text.align_right, text_valign = text.align_top, text_color = na, border_color = na, bgcolor = color.new(cLQV_S, 90) ))
else
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_S, 90) ))
if b_liq_V.size() > 0
qt = b_liq_V.size()
for bn = qt - 1 to 0
if bn < b_liq_V.size()
cb = b_liq_V.get(bn)
ba = math.avg(cb.get_bottom(), cb.get_top())
if math.sign(b.c - ba) != math.sign(b.c - ba) or math.sign(b.c - ba) != math.sign(b.l - ba) or math.sign(b.c - ba) != math.sign(b.h - ba)
b_liq_V.remove(bn)
else
cb.set_right(b.i + 1)
if b.i - cb.get_left() > 21
cb.set_text_color(color.new(color.gray, 25))
//-----------------------------------------------------------------------------}
Day-Type Detector — Rejection / FNL / Outside / StopRun (Clean)Day-Type Detector — Rejection / FNL / Outside / Stop-Run (Clean Version)
This indicator identifies four high-impact candlestick day-types commonly used in professional price-action and auction-market trading: Rejection Days, Failed New Low (FNL) Days, Outside Days, and Stop-Run Days. These patterns often precede major directional moves, reversals, and absorption events, making them particularly valuable for swing traders, positional traders, and short-term discretionary traders.
The script is designed to work across all timeframes and is built around volatility-adjusted measurements using Average Daily Range (ADR) for accuracy and consistency.
What This Indicator Detects
1. Rejection Day (Bullish & Bearish)
A Rejection Day is a wide-range bar that rejects a previous extreme.
The indicator identifies rejection based on:
Range > ADR × threshold
Long lower wick (for bullish) or long upper wick (for bearish)
Close located in the strong zone of the day’s range
These conditions highlight areas where aggressive counter-orderflow entered the market.
2. Failed New Low (FNL) / Failed New High
An FNL day traps traders who attempted breakout selling or buying.
The indicator checks for:
A break beyond the previous session’s low or high
Immediate rejection back inside
Midpoint recapture conditions
ADR-normalized range requirements
These days often trigger powerful directional reversals.
3. Outside Day (Bullish & Bearish)
An Outside Day is a statistically significant expansion day that breaks both the previous high and low.
The script validates:
High > previous high and low < previous low
Range > ADR threshold
Close beyond prior session extreme to complete the rejection sequence
Outside Days often represent stop runs, shakeouts, or trend accelerations.
4. Stop-Run Day (Bullish & Bearish)
Stop-Run Days are aggressive volatility expansions and tend to be the largest ranges within short windows.
This detector identifies them using:
Range > ADR × multiplier
Close located near the extreme of the day (top for bullish, bottom for bearish)
Strong body relative to total range
Break above/below previous session extreme
These patterns indicate capitulation or forced liquidation and are often followed by continuation or sharp counter-rotation.
Key Features
✔ Historical Pattern Marking
All qualifying bars are marked on the chart using plotshape() in global scope, ensuring full historical visibility.
✔ Event Logging & Table Display
A table (top-right of the chart) displays the most recent pattern detections, including:
Timestamp
Pattern type
Bar index
This allows users to monitor and study past pattern occurrences without scanning the chart manually.
✔ ADR-Adjusted Detection
Volatility uncertainty is removed by anchoring all thresholds to ADR.
This ensures consistency across:
Different symbols
Different timeframes
Different market regimes
✔ Alerts Included
Alerts are preconfigured for:
Rejection Day Bull / Bear
FNL Bull / Bear
Outside Day Bull / Bear
Stop-Run Bull / Bear
This allows the user to receive real-time notifications when major day-type structures develop.
How to Use
Add the indicator to any timeframe chart.
Enable or disable:
Historical markers
History table
ADR diagnostics
Watch for shape markers or use alerts for real-time signals.
Use the history table to review recent occurrences.
Combine these day-types with:
Market structure levels
High/low volume nodes (LVNs)
Support/resistance zones
Trend context
These day-types are most effective when they occur near meaningful structural levels because they show where strong order-flow entered the market.
Best Practices
Use higher timeframes (1H–1D) for swing entries.
Confirm signals with market structure or volume profile.
Treat these day-types as context, not standalone signals.
Observe follow-through behavior in the next 1–3 bars after detection.
Credits
This script is based on concepts commonly seen in auction-market theory and professional price-action frameworks, such as Rejection Days, Failed New Lows, Outside Days, and Stop-Run behaviors.
All calculations and logic have been rebuilt from scratch to ensure clean, reliable, and optimized Pine Script v6 execution.
DAO - Demand Advanced Oscillator# DAO - Demand Advanced Oscillator
## 📊 Overview
DAO (Demand Advanced Oscillator) is a powerful momentum oscillator that measures buying and selling pressure by analyzing consecutive high-low relationships. It helps identify market extremes, divergences, and potential trend reversals.
**Values range from 0 to 1:**
- **Above 0.70** = Overbought (potential reversal down)
- **Below 0.30** = Oversold (potential reversal up)
- **0.30 - 0.70** = Neutral zone
---
## ✨ Key Features
✅ **Automatic Divergence Detection**
- Bullish divergences (price lower low + DAO higher low)
- Bearish divergences (price higher high + DAO lower high)
- Visual lines connecting divergence points
✅ **Multi-Timeframe Analysis**
- View higher timeframe DAO on current chart
- Perfect for trend alignment strategies
✅ **Signal Line (EMA)**
- Customizable EMA for trend confirmation
- Crossover signals for momentum shifts
✅ **Real-Time Statistics Dashboard**
- Current DAO value
- Market status (Overbought/Oversold/Neutral)
- Trend direction indicator
✅ **Complete Alert System**
- Overbought/Oversold signals
- Bullish/Bearish divergences
- Signal line crosses
- Level crosses
✅ **Fully Customizable**
- Adjustable periods and levels
- Customizable colors and zones
- Toggle features on/off
---
## 📈 Trading Signals
### 1. Divergences (Most Powerful)
**Bullish Divergence:**
- Price makes lower low
- DAO makes higher low
- Signal: Strong reversal up likely
**Bearish Divergence:**
- Price makes higher high
- DAO makes lower high
- Signal: Strong reversal down likely
### 2. Overbought/Oversold
**Overbought (>0.70):**
- Market may be overextended
- Consider taking profits or looking for shorts
- Can remain overbought in strong trends
**Oversold (<0.30):**
- Market may be oversold
- Consider buying opportunities
- Can remain oversold in strong downtrends
### 3. Signal Line Crossovers
**Bullish Cross:**
- DAO crosses above signal line
- Momentum turning positive
**Bearish Cross:**
- DAO crosses below signal line
- Momentum turning negative
### 4. Level Crosses
**Cross Above 0.30:** Exiting oversold zone (potential uptrend)
**Cross Below 0.70:** Exiting overbought zone (potential downtrend)
---
## ⚙️ Default Settings
📊 Oscillator Period: 14
Number of bars for calculation
📈 Signal Line Period: 9
EMA period for signal line
🔴 Overbought Level: 0.70
Upper threshold
🟢 Oversold Level: 0.30
Lower threshold
🎯 Divergence Detection: ON
Auto divergence identification
⏰ Multi-Timeframe: OFF
Higher TF overlay (optional)
All parameters are fully customizable!
---
## 🔔 Alerts
Six pre-configured alerts available:
1. DAO Overbought
2. DAO Oversold
3. DAO Bullish Divergence
4. DAO Bearish Divergence
5. DAO Signal Cross Up
6. DAO Signal Cross Down
**Setup:** Right-click indicator → Add Alert → Choose condition
---
## 💡 How to Use
### Best Practices:
✅ Focus on divergences (strongest signals)
✅ Combine with support/resistance levels
✅ Use multiple timeframes for confirmation
✅ Wait for price action confirmation
✅ Practice proper risk management
### Avoid:
❌ Trading on indicator alone
❌ Fighting strong trends
❌ Ignoring market context
❌ Overtrading
### Recommended Settings by Trading Style:
**Day Trading:** Period 7-10, All alerts ON
**Swing Trading:** Period 14-21, Divergence alerts
**Scalping:** Period 5-7, Signal crosses
**Position Trading:** Period 21-30, Weekly/Daily TF
---
## 🌍 Markets & Timeframes
**Works on all markets:**
- Forex (all pairs)
- Stocks (all exchanges)
- Cryptocurrencies
- Commodities
- Indices
- Futures
**Works on all timeframes:** 1m to Monthly
---
## 📊 How It Works
DAO calculates the ratio of buying pressure to total market pressure:
1. **Calculate Buying Pressure (DemandMax):**
- If current high > previous high: DemandMax = difference
- Otherwise: DemandMax = 0
2. **Calculate Selling Pressure (DemandMin):**
- If previous low > current low: DemandMin = difference
- Otherwise: DemandMin = 0
3. **Apply Smoothing:**
- Calculate SMA of DemandMax over N periods
- Calculate SMA of DemandMin over N periods
4. **Final Formula:**
```
DAO = SMA(DemandMax) / (SMA(DemandMax) + SMA(DemandMin))
```
This produces a normalized value (0-1) representing market demand strength.
---
## 🎯 Trading Strategies
### Strategy 1: Divergence Trading
- Wait for divergence label
- Confirm at support/resistance
- Enter on confirming candle
- Stop loss beyond recent swing
- Target: opposite level or 0.50
### Strategy 2: Overbought/Oversold
- Best for ranging markets
- Wait for extreme readings
- Enter on reversal from extremes
- Target: middle line (0.50)
### Strategy 3: Trend Following
- Identify trend direction first
- Use DAO to time entries in trend direction only
- Enter on pullbacks to oversold (uptrend) or overbought (downtrend)
- Trade with the trend
### Strategy 4: Multi-Timeframe
- Enable MTF feature
- Trade only when both timeframes align
- Higher TF = trend direction
- Lower TF = precise entry
---
## 📂 Category
**Primary:** Oscillators
**Secondary:** Statistics, Volatility, Momentum
---
## 🏷️ Tags
dao, oscillator, momentum, overbought-oversold, divergence, reversal, demand-indicator, price-exhaustion, statistics, volatility, forex, stocks, crypto, multi-timeframe, technical-analysis
---
## ⚠️ Disclaimer
**This indicator is for educational purposes only.** It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research, use proper risk management, and consult with financial professionals before making trading decisions. Past performance does not guarantee future results.
---
## 📄 License
Open source - Free to use for personal trading, modify as needed, and share with attribution.
---
**Version:** 1.0
**Status:** Production Ready ✅
**Pine Script:** v5
**Trademark-Free:** 100% Safe to Publish
---
*Made with 💙 for traders worldwide*
[FS] Pivot Measurements# Pivot Measurements
An advanced TradingView indicator that combines LuxAlgo's pivot point detection algorithm with automatic measurement calculations between consecutive pivots.
## Features
### Pivot Detection
- **Regular Pivots**: Detects standard pivot highs and lows using configurable pivot length
- **Missed Pivots**: Identifies missed reversal levels that occurred between regular pivots
- **Visual Indicators**:
- Regular pivot highs: Red downward triangle (▼)
- Regular pivot lows: Teal upward triangle (▲)
- Missed pivots: Ghost emoji (👻)
- **Zigzag Lines**: Connects pivots with colored lines (solid for regular, dashed for missed)
- **Ghost Levels**: Horizontal lines indicating missed pivot levels
### Measurement System
- **Automatic Measurements**: Calculates price movements between consecutive pivots
- **Visual Display**:
- Transparent colored boxes (blue for upward, red for downward movements)
- Measurement labels showing:
- Price change (absolute and percentage)
- Duration (bars, days, hours, minutes)
- Volume approximation
- **Smart Positioning**: Labels positioned outside boxes (above for upward, below for downward)
- **Color Coding**: Blue for positive movements, red for negative movements
## Parameters
### Pivot Detection
- **Pivot Length** (default: 50): Number of bars on each side to identify a pivot point
- **Regular Pivots**: Toggle and colors for regular pivot highs and lows
- **Missed Pivots**: Toggle and colors for missed pivot detection
### Measurements
- **Number of Measurements** (1-10, default: 10): Maximum number of measurements to display
- **Show Measurement Boxes**: Toggle to show/hide measurement boxes and labels
- **Box Transparency** (0-100, default: 90): Transparency level for measurement boxes
- **Border Transparency** (0-100, default: 50): Transparency level for box borders
- **Label Background Transparency** (0-100, default: 30): Transparency level for label backgrounds
- **Label Size**: Size of measurement labels (tiny, small, normal, large)
## Usage
1. Add the indicator to your chart
2. Configure the **Pivot Length** based on your timeframe:
- Lower values for shorter timeframes (e.g., 10-20 for 1-5 min)
- Higher values for longer timeframes (e.g., 50-100 for daily)
3. Adjust pivot colors and visibility as needed
4. Customize measurement display settings:
- Set the number of measurements to display
- Adjust transparency levels for boxes, borders, and labels
- Choose label size
## Technical Details
- **Pine Script Version**: v6
- **Pivot Detection**: Based on () algorithm for detecting regular and missed pivots
- **Measurement Calculation**:
- Measures between consecutive pivots (from most recent to older)
- Calculates price change, percentage change, duration, and approximate volume
- Automatically sorts pivots chronologically
- **Performance**: Optimized with helper functions to reduce code duplication
## Notes
- The indicator automatically limits the number of stored pivots to optimize performance
- Measurements are only created when there are at least 2 pivots detected
- All measurements are recalculated on each bar update
- The indicator uses `max_bars_back=5000` to ensure sufficient historical data
## License
This indicator uses LuxAlgo's pivot detection algorithm from (). Please refer to the original LuxAlgo license for pivot detection components.
LibPvotLibrary "LibPvot"
This is a library for advanced technical analysis, specializing
in two core areas: the detection of price-oscillator
divergences and the analysis of market structure. It provides
a back-end engine for signal detection and a toolkit for
indicator plotting.
Key Features:
1. **Complete Divergence Suite (Class A, B, C):** The engine detects
all three major types of divergences, providing a full spectrum of
analytical signals:
- **Regular (A):** For potential trend reversals.
- **Hidden (B):** For potential trend continuations.
- **Exaggerated (C):** For identifying weakness at double tops/bottoms.
2. **Advanced Signal Filtering:** The detection logic uses a
percentage-based price tolerance (`prcTol`). This feature
enables the practical detection of Exaggerated divergences
(which rarely occur at the exact same price) and creates a
"dead zone" to filter insignificant noise from triggering
Regular divergences.
3. **Pivot Synchronization:** A bar tolerance (`barTol`) is used
to reliably match price and oscillator pivots that do not
align perfectly on the same bar, preventing missed signals.
4. **Signal Invalidation Logic:** Features two built-in invalidation
rules:
- An optional `invalidate` parameter automatically terminates
active divergences if the price or the oscillator breaks
the level of the confirming pivot.
- The engine also discards 'half-pivots' (e.g., a price pivot)
if a corresponding oscillator pivot does not appear within
the `barTol` window.
5. **Stateful Plotting Helpers:** Provides helper functions
(`bullDivPos` and `bearDivPos`) that abstract away the
state management issues of visualizing persistent signals.
They generate gap-free, accurately anchored data series
ready to be used in `plotshape` functions, simplifying
indicator-side code.
6. **Rich Data Output:** The core detection functions (`bullDiv`, `bearDiv`)
return a comprehensive 9-field data tuple. This includes the
boolean flags for each divergence type and the precise
coordinates (price, oscillator value, bar index) of both the
starting and the confirming pivots.
7. **Market Structure & Trend Analysis:** Includes a
`marketStructure` function to automatically identify pivot
highs/lows, classify their relationship (HH, LH, LL, HL),
detect structure breaks, and determine the current trend
state (Up, Down, Neutral) based on pivot sequences.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
bullDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bullish divergences (Regular, Hidden, Exaggerated) based on pivot lows.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `low`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
below the confirming pivot low.
Returns: A tuple containing comprehensive data for a detected bullish divergence.
regBull series bool `true` if a Regular bullish divergence (Class A) is active.
hidBull series bool `true` if a Hidden bullish divergence (Class B) is active.
exgBull series bool `true` if an Exaggerated bullish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot low.
initPivotOsz series float Oscillator value of the initial pivot low.
initPivotBar series int Bar index of the initial pivot low.
lastPivotPrc series float Price value of the last (confirming) pivot low.
lastPivotOsz series float Oscillator value of the last pivot low.
lastPivotBar series int Bar index of the last pivot low.
bearDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bearish divergences (Regular, Hidden, Exaggerated) based on pivot highs.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `high`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
above the confirming pivot high.
Returns: A tuple containing comprehensive data for a detected bearish divergence.
regBear series bool `true` if a Regular bearish divergence (Class A) is active.
hidBear series bool `true` if a Hidden bearish divergence (Class B) is active.
exgBear series bool `true` if an Exaggerated bearish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot high.
initPivotOsz series float Oscillator value of the initial pivot high.
initPivotBar series int Bar index of the initial pivot high.
lastPivotPrc series float Price value of the last (confirming) pivot high.
lastPivotOsz series float Oscillator value of the last pivot high.
lastPivotBar series int Bar index of the last pivot high.
bullDivPos(regBull, hidBull, exgBull, rightLen, yPos)
Calculates the plottable data series for bullish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBull (bool) : series bool The regular bullish divergence flag from `bullDiv`.
hidBull (bool) : series bool The hidden bullish divergence flag from `bullDiv`.
exgBull (bool) : series bool The exaggerated bullish divergence flag from `bullDiv`.
rightLen (int) : series int The same `rightLen` value used in `bullDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `low`).
Returns: A tuple of three `series float` for plotting bullish divergences.
regBullPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBullPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBullPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
bearDivPos(regBear, hidBear, exgBear, rightLen, yPos)
Calculates the plottable data series for bearish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBear (bool) : series bool The regular bearish divergence flag from `bearDiv`.
hidBear (bool) : series bool The hidden bearish divergence flag from `bearDiv`.
exgBear (bool) : series bool The exaggerated bearish divergence flag from `bearDiv`.
rightLen (int) : series int The same `rightLen` value used in `bearDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `high`).
Returns: A tuple of three `series float` for plotting bearish divergences.
regBearPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBearPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBearPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
marketStructure(highSrc, lowSrc, leftLen, rightLen, srcTol)
Analyzes the market structure by identifying pivot points, classifying
their sequence (e.g., Higher Highs, Lower Lows), and determining the
prevailing trend state.
Parameters:
highSrc (float) : series float Price series for pivot high detection (e.g., `high`).
lowSrc (float) : series float Price series for pivot low detection (e.g., `low`).
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
srcTol (float) : series float Percentage tolerance to consider two pivots as 'equal' (default 0.05%).
Returns: A tuple containing detailed market structure information.
pivType series PivType The type of the most recently formed pivot (e.g., `hh`, `ll`).
lastPivHi series float The price level of the last confirmed pivot high.
lastPivLo series float The price level of the last confirmed pivot low.
lastPiv series float The price level of the last confirmed pivot (either high or low).
pivHiBroken series bool `true` if the price has broken above the last pivot high.
pivLoBroken series bool `true` if the price has broken below the last pivot low.
trendState series TrendState The current trend state (`up`, `down`, or `neutral`).
Sunmool's NY Lunch Model BacktestingICT NY Lunch Model Backtesting (12:00–13:00 NY) 🗽🍔
This research indicator tests an ICT narrative using the New York lunch window (12:00–13:00 America/New_York). It records that hour’s high/low and measures, during the post-lunch session (default 13:00–16:00), how often:
⬆️ If the afternoon trends up, the Lunch Low gets swept first.
⬇️ If the afternoon trends down, the Lunch High gets swept first.
It reports these as conditional probabilities, not trade signals. 📈
👀 What it shows
🟦 Lunch Range box (toggle): high/low from 12:00–13:00 NY
🔻🔺 Sweep signals (bar-anchored)
Low sweep: triangle below bar + optional “L”
High sweep: triangle above bar + optional “H”
🧱 Optional small box wrapping the swept candle
📊 Stats table (top-right)
P(L-swept | Up) — % of Up-days where Lunch Low was swept
P(H-swept | Down) — % of Down-days where Lunch High was swept
🔁 Contradictions + sample sizes (Up-days / Down-days)
🎯 Direction logic (Up/Down)
Anchor: 13:00 open (pmOpen) ⏰
Threshold: ATR × multiple or % from 13:00
Close ≥ pmOpen + threshold → Up-day
Close ≤ pmOpen − threshold → Down-day
Tiny moves under the threshold are ignored to reduce noise 🧹
⚙️ Inputs
🌐 Timezone: America/New_York (DST handled)
🍽️ Lunch window: 1200–1300
🕓 Post-lunch window: default 1300–1600 (try 17:00/20:00 for sensitivity)
📐 Trend threshold: ATR / Percent (with length/multiple or % level)
📅 Weekdays-only toggle (FX/Equities style)
👁️ Display toggles: Lunch box / sweep arrows / sweep text / sweep candle box / stats table
🔔 TF hint when chart TF > 15m
🧭 How to use
Use 5–15m charts for accurate lunch range capture.
Scroll ~1 year for meaningful samples.
Run sensitivity checks: vary ATR/% thresholds and the post-lunch end time.
For crypto, compare with vs without weekends. 🚀
🧠 Reading the results
High P(L-swept | Up) with a solid Up-day count ⇒ on up afternoons, lunch low is often swept.
High P(H-swept | Down) ⇒ on down afternoons, lunch high is often swept.
Lower Contradictions = cleaner tendency.
Remember: this is a probabilistic tendency, not a rule. 🎲
📝 Notes & limits
All markers (arrows, text, sweep boxes) are bar-anchored; the lunch range box is a research overlay you can toggle.
Real-time vs historical bar building can differ—interpret on bar close. 🔒
mysourcetypesncsLibrary "mysourcetypes"
Libreria personale per sorgenti estese (Close, Open, High, Low, Median, Typical, Weighted, Average, Average Median Body, Trend Biased, Trend Biased Extreme, Volume Body, Momentum Biased, Volatility Adjusted, Body Dominance, Shadow Biased, Gap Aware, Rejection Biased, Range Position, Adaptive Trend, Pressure Balanced, Impulse Wave)
rclose()
Regular Close
Returns: Close price
ropen()
Regular Open
Returns: Open price
rhigh()
Regular High
Returns: High price
rlow()
Regular Low
Returns: Low price
rmedian()
Regular Median (HL2)
Returns: (High + Low) / 2
rtypical()
Regular Typical (HLC3)
Returns: (High + Low + Close) / 3
rweighted()
Regular Weighted (HLCC4)
Returns: (High + Low + Close + Close) / 4
raverage()
Regular Average (OHLC4)
Returns: (Open + High + Low + Close) / 4
ravemedbody()
Average Median Body
Returns: (Open + Close) / 2
rtrendb()
Trend Biased Regular
Returns: Trend-weighted price
rtrendbext()
Trend Biased Extreme
Returns: Extreme trend-weighted price
rvolbody()
Volume Weighted Body
Returns: Body midpoint weighted by volume intensity
rmomentum()
Momentum Biased
Returns: Price biased towards momentum direction
rvolatility()
Volatility Adjusted
Returns: Price adjusted by candle's volatility
rbodydominance()
Body Dominance
Returns: Emphasizes body over wicks
rshadowbias()
Shadow Biased
Returns: Price biased by shadow length
rgapaware()
Gap Aware
Returns: Considers gap between candles
rrejection()
Rejection Biased
Returns: Emphasizes price rejection levels
rrangeposition()
Range Position
Returns: Where close sits within the candle range (0-100%)
radaptivetrend()
Adaptive Trend
Returns: Adapts based on recent trend strength
rpressure()
Pressure Balanced
Returns: Balances buying/selling pressure within candle
rimpulse()
Impulse Wave
Returns: Detects impulsive moves vs corrections
Auto Fibonacci LevelsAuto Fibonacci Momentum Zones with Visible Range Table
Overview and Originality
The Auto Fibonacci Momentum Zones indicator offers a streamlined, static overlay of Fibonacci retracement levels inspired by extreme RSI momentum thresholds, enhanced with a dynamic table displaying the high and low of the currently visible chart range. This isn't a repackaged RSI oscillator or basic Fib drawer—common in TradingView's library—but a purposeful fusion of geometric harmony (Fibonacci ratios) with momentum psychology (RSI extremes at 35/85), projected as fixed horizontal reference lines on the price chart. The addition of the visible range table, powered by PineCoders' VisibleChart library, provides real-time context for the chart's current view, enabling traders to quickly assess range compression or expansion relative to these zones.
This script's originality stems from its "static momentum mapping": by hardcoding Fib levels on a dynamic chart, it creates universal psychological support/resistance lines that transcend specific assets or timeframes.
Unlike dynamic Fib tools that auto-adjust to price swings (risking noise in ranging markets) or standalone RSI plots (confined to panes), this delivers clean, bias-adjustable overlays for confluence analysis. The visible range table justifies the library integration—it's not a gratuitous add-on but a complementary tool that quantifies the "screen real estate" of price action, helping users correlate Fib touches with actual volatility. Drawn from original code (no auto-generation or public templates), it builds TradingView's body of knowledge by simplifying multi-tool workflows into one indicator, ideal for discretionary traders who value visual efficiency over algorithmic complexity.
How It Works: Underlying Concepts
Fibonacci retracements, derived from the Fibonacci sequence and the golden ratio (≈0.618), identify potential reversal points based on the idea that markets retrace prior moves in predictable proportions: shallow (23.6%, 38.2%), mid (50%), and deep (61.8%, 78.6%).
Adjustable Outputs
1. The "Invert Fibs" toggle (default: true) for bearish/topping bias, can be flipped aligning with trend context.
2. Fibonacci Levels: Seven semi-transparent horizontal lines are drawn using `hline()`:
- 0.0 at high (gray).
- 0.236: high - (range × 0.236) (light cyan, shallow pullback).
- 0.382: high - (range × 0.382) (teal, common retracement).
- 0.5: midpoint average (green, equilibrium).
- 0.618: high - (range × 0.618) (amber, golden pocket for reversals).
- 0.786: high - (range × 0.786) (orange, deep support).
- 1.0 at low (gray).
Colors progress from cool (shallow) to warm (deep) for intuitive scanning.
3. Optional Fib Labels: Right-edge text labels (e.g., "0.618") appear only if enabled, positioned at the last bar + offset for non-cluttering visibility.
4. Visible Range Table: Leveraging the VisibleChart library's `visible.high()` and `visible.low()` functions, a compact 2x2 table (top-right corner) updates on the last bar to show the extrema of bars currently in view. This mashup enhances utility: Fib zones provide fixed anchors, while the table's dynamic values reveal if price is "pinned" to a zone (e.g., visible high hugging 0.382 signals resistance). The library is invoked sparingly for performance, adding value by bridging static geometry with viewport-aware data—unavailable in built-ins without custom code.
How to Use It
1. Setup:
Add to any chart (e.g., 15M for scalps, Daily for swings). As an overlay, lines appear directly on price candles—adjust chart scaling if needed.
2. Input Tweaks:
Invert Fibs: Enable for downtrends (85 top), disable for uptrends (35 bottom).
Show Fibs: Toggle labels for ratio callouts (off for clean charts).
Show Table: Display/hide the visible high/low summary (red for high, green for low, formatted to 2 decimals).
3. Trading Application:
Zone Confluence: Seek price reactions at each fibonacci level—e.g., a doji at 0.618 + rising volume suggests entry; use 0.0/1.0 as invalidation.
Range Context: Check the table: If visible high/low spans <20% of the Fib arc (e.g., both near 0.5), anticipate breakout; wider spans signal consolidation.
Multi-Timeframe: Overlay on higher TF for bias, lower for precision—e.g., Daily Fibs guide 1H entries.
Enhancements: Pair with volume or candlesticks; set alerts on line crosses via TradingView's built-in tools. Backtest on your symbols to validate (e.g., equities favor 0.382, forex the 0.786).
This indicator automates advanced Fibonacci synthesis dynamically, eliminating manual measurement and calculations.
published by ozzy_livin
Ultimate Oscillator (ULTOSC)The Ultimate Oscillator (ULTOSC) is a technical momentum indicator developed by Larry Williams that combines three different time periods to reduce the volatility and false signals common in single-period oscillators. By using a weighted average of three Stochastic-like calculations across short, medium, and long-term periods, the Ultimate Oscillator provides a more comprehensive view of market momentum while maintaining sensitivity to price changes.
The indicator addresses the common problem of oscillators being either too sensitive (generating many false signals) or too slow (missing opportunities). By incorporating multiple timeframes with decreasing weights for longer periods, ULTOSC attempts to capture both short-term momentum shifts and longer-term trend strength, making it particularly valuable for identifying divergences and potential reversal points.
## Core Concepts
* **Multi-timeframe analysis:** Combines three different periods (typically 7, 14, 28) to capture various momentum cycles
* **Weighted averaging:** Assigns higher weights to shorter periods for responsiveness while including longer periods for stability
* **Buying pressure focus:** Measures the relationship between closing price and the true range rather than just high-low range
* **Divergence detection:** Particularly effective at identifying momentum divergences that precede price reversals
* **Normalized scale:** Oscillates between 0 and 100, with clear overbought/oversold levels
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Fast Period | 7 | Short-term momentum calculation | Lower (5-6) for more sensitivity, higher (9-12) for smoother signals |
| Medium Period | 14 | Medium-term momentum calculation | Adjust based on typical swing duration in the market |
| Slow Period | 28 | Long-term momentum calculation | Higher values (35-42) for longer-term position trading |
| Fast Weight | 4.0 | Weight applied to fast period | Higher weight increases short-term sensitivity |
| Medium Weight | 2.0 | Weight applied to medium period | Adjust to balance medium-term influence |
| Slow Weight | 1.0 | Weight applied to slow period | Usually kept at 1.0 as the baseline weight |
**Pro Tip:** The classic 7/14/28 periods with 4/2/1 weights work well for most markets, but consider using 5/10/20 with adjusted weights for faster markets or 14/28/56 for longer-term analysis.
## Calculation and Mathematical Foundation
**Simplified explanation:**
The Ultimate Oscillator calculates three separate "buying pressure" ratios using different time periods, then combines them using weighted averaging. Buying pressure is defined as the close minus the true low, divided by the true range.
**Technical formula:**
```
BP = Close - Min(Low, Previous Close)
TR = Max(High, Previous Close) - Min(Low, Previous Close)
BP_Sum_Fast = Sum(BP, Fast Period)
TR_Sum_Fast = Sum(TR, Fast Period)
Raw_Fast = 100 × (BP_Sum_Fast / TR_Sum_Fast)
BP_Sum_Medium = Sum(BP, Medium Period)
TR_Sum_Medium = Sum(TR, Medium Period)
Raw_Medium = 100 × (BP_Sum_Medium / TR_Sum_Medium)
BP_Sum_Slow = Sum(BP, Slow Period)
TR_Sum_Slow = Sum(TR, Slow Period)
Raw_Slow = 100 × (BP_Sum_Slow / TR_Sum_Slow)
ULTOSC = 100 × / (Fast_Weight + Medium_Weight + Slow_Weight)
```
Where:
- BP = Buying Pressure
- TR = True Range
- Fast Period = 7, Medium Period = 14, Slow Period = 28 (defaults)
- Fast Weight = 4, Medium Weight = 2, Slow Weight = 1 (defaults)
> 🔍 **Technical Note:** The implementation uses efficient circular buffers for all three period calculations, maintaining O(1) time complexity per bar. The algorithm properly handles true range calculations including gaps and ensures accurate buying pressure measurements across all timeframes.
## Interpretation Details
ULTOSC provides several analytical perspectives:
* **Overbought/Oversold conditions:** Values above 70 suggest overbought conditions, below 30 suggest oversold conditions
* **Momentum direction:** Rising ULTOSC indicates increasing buying pressure, falling indicates increasing selling pressure
* **Divergence analysis:** Divergences between ULTOSC and price often precede significant reversals
* **Trend confirmation:** ULTOSC direction can confirm or question the prevailing price trend
* **Signal quality:** Extreme readings (>80 or <20) indicate strong momentum that may be unsustainable
* **Multiple timeframe consensus:** When all three underlying periods agree, signals are typically more reliable
## Trading Applications
**Primary Uses:**
- **Divergence trading:** Identify when momentum diverges from price for reversal signals
- **Overbought/oversold identification:** Find potential entry/exit points at extreme levels
- **Trend confirmation:** Validate breakouts and trend continuations
- **Momentum analysis:** Assess the strength of current price movements
**Advanced Strategies:**
- **Multi-divergence confirmation:** Look for divergences across multiple timeframes
- **Momentum breakouts:** Trade when ULTOSC breaks above/below key levels with volume
- **Swing trading entries:** Use oversold/overbought levels for swing position entries
- **Trend strength assessment:** Evaluate trend quality using momentum consistency
## Signal Combinations
**Strong Bullish Signals:**
- ULTOSC rises from oversold territory (<30) with positive price divergence
- ULTOSC breaks above 50 after forming a base near 30
- All three underlying periods show increasing buying pressure
**Strong Bearish Signals:**
- ULTOSC falls from overbought territory (>70) with negative price divergence
- ULTOSC breaks below 50 after forming a top near 70
- All three underlying periods show decreasing buying pressure
**Divergence Signals:**
- **Bullish divergence:** Price makes lower lows while ULTOSC makes higher lows
- **Bearish divergence:** Price makes higher highs while ULTOSC makes lower highs
- **Hidden bullish divergence:** Price makes higher lows while ULTOSC makes lower lows (trend continuation)
- **Hidden bearish divergence:** Price makes lower highs while ULTOSC makes higher highs (trend continuation)
## Comparison with Related Oscillators
| Indicator | Periods | Focus | Best Use Case |
|-----------|---------|-------|---------------|
| **Ultimate Oscillator** | 3 periods | Buying pressure | Divergence detection |
| **Stochastic** | 1-2 periods | Price position | Overbought/oversold |
| **RSI** | 1 period | Price momentum | Momentum analysis |
| **Williams %R** | 1 period | Price position | Short-term signals |
## Advanced Configurations
**Fast Trading Setup:**
- Fast: 5, Medium: 10, Slow: 20
- Weights: 4/2/1, Thresholds: 75/25
**Standard Setup:**
- Fast: 7, Medium: 14, Slow: 28
- Weights: 4/2/1, Thresholds: 70/30
**Conservative Setup:**
- Fast: 14, Medium: 28, Slow: 56
- Weights: 3/2/1, Thresholds: 65/35
**Divergence Focused:**
- Fast: 7, Medium: 14, Slow: 28
- Weights: 2/2/2, Thresholds: 70/30
## Market-Specific Adjustments
**Volatile Markets:**
- Use longer periods (10/20/40) to reduce noise
- Consider higher threshold levels (75/25)
- Focus on extreme readings for signal quality
**Trending Markets:**
- Emphasize divergence analysis over absolute levels
- Look for momentum confirmation rather than reversal signals
- Use hidden divergences for trend continuation
**Range-Bound Markets:**
- Standard overbought/oversold levels work well
- Trade reversals from extreme levels
- Combine with support/resistance analysis
## Limitations and Considerations
* **Lagging component:** Contains inherent lag due to multiple moving average calculations
* **Complex calculation:** More computationally intensive than single-period oscillators
* **Parameter sensitivity:** Performance varies significantly with different period/weight combinations
* **Market dependency:** Most effective in trending markets with clear momentum patterns
* **False divergences:** Not all divergences lead to significant price reversals
* **Whipsaw potential:** Can generate conflicting signals in choppy markets
## Best Practices
**Effective Usage:**
- Focus on divergences rather than absolute overbought/oversold levels
- Combine with trend analysis for context
- Use multiple timeframe analysis for confirmation
- Pay attention to the speed of momentum changes
**Common Mistakes:**
- Over-relying on overbought/oversold levels in strong trends
- Ignoring the underlying trend direction
- Using inappropriate period settings for the market being analyzed
- Trading every divergence without additional confirmation
**Signal Enhancement:**
- Combine with volume analysis for confirmation
- Use price action context (support/resistance levels)
- Consider market volatility when setting thresholds
- Look for convergence across multiple momentum indicators
## Historical Context and Development
The Ultimate Oscillator was developed by Larry Williams and introduced in his 1985 article "The Ultimate Oscillator" in Technical Analysis of Stocks and Commodities magazine. Williams designed it to address the limitations of single-period oscillators by:
- Reducing false signals through multi-timeframe analysis
- Maintaining sensitivity to short-term momentum changes
- Providing more reliable divergence signals
- Creating a more robust momentum measurement tool
The indicator has become a standard tool in technical analysis, particularly valued for its divergence detection capabilities and its balanced approach to momentum measurement.
## References
* Williams, L. R. (1985). The Ultimate Oscillator. Technical Analysis of Stocks and Commodities, 3(4).
* Williams, L. R. (1999). Long-Term Secrets to Short-Term Trading. Wiley Trading.
HTF Candle Highs and Lows with Labels + High Probability Signals█ OVERVIEW
This indicator overlays Weekly, Daily, and H4 High/Low levels directly onto your chart, allowing traders to visualize key support and resistance zones from higher timeframes. It also includes high probability breakout signals that appear one candle after a confirmed breakout above or below these levels, filtered by volume and candle strength.
Use this tool to identify breakout opportunities with greater confidence and clarity.
█ FEATURES
• Plots Weekly, Daily, and H4 High and Low levels using request.security. • Customizable line colors, widths, and label sizes. • Toggle visibility for each timeframe independently. • Signals appear one candle after a confirmed breakout: • Bullish: Close above HTF High, strong candle, high volume. • Bearish: Close below HTF Low, strong candle, high volume. • Signal shapes match the color of the broken level for visual clarity.
█ HOW TO USE
1 — Enable the timeframes you want to track using the input toggles. 2 — Watch for triangle-shaped signals: • Upward triangle = Bullish breakout. • Downward triangle = Bearish breakout. 3 — Confirm the breakout: • Candle closes beyond the HTF level by at least 0.1%. • Candle body shows momentum (close > open for bullish, close < open for bearish). • Volume exceeds 20-period average. 4 — Enter trade on the candle after the signal. 5 — Use the HTF level as a reference for stop-loss placement. 6 — Combine with other indicators (e.g., RSI, EMA) for confluence.
█ LIMITATIONS
• Signals may lag by one candle due to confirmation logic. • Not optimized for low-volume assets or illiquid markets. • Best used in trending environments; avoid during consolidation. • Does not include automatic alerts (can be added manually).
█ BEST PRACTICES
• Use on H1 or higher timeframes for cleaner signals. • Avoid trading during news events or low volatility. • Backtest thoroughly before live trading. • Adjust breakout percentage and volume filter based on asset volatility. • Maintain a trading journal to track performance.
All Levels This script draws key price levels on your chart, including:
• Previous Day (PD): High, Low, Close
• Day Before Yesterday (DBY): High, Low, Close
• Pre-Market (PM): High and Low
• Today’s levels: High, Low, Open, Close
• Current bar levels: High, Low, Open, Close
Each level is displayed as a horizontal line with a label showing the level value.
It works on any timeframe, including 1-minute charts, and automatically updates as new bars form.
⸻
2. Features
1. Custom Colors
Each type of level has its own color, declared as a const color. For example:
• Previous Day High = red
• Today’s Close = gold
• Pre-Market High = fuchsia
2. Right-Extending Lines
All horizontal levels extend to the right, so you always see them on the chart.
3. Persistent Labels
Every line has a label at the right side showing its name and price. For example:
• PDH 422
• TODL 415.5
4. Dynamic Updates
The script updates automatically whenever a new bar forms, so levels stay accurate.
5. Session-Based Pre-Market
You can define the pre-market session (default “04:00–09:30 EST”). The script calculates the high and low of this session only.
6. Checkbox Inputs
You can enable/disable entire groups of levels:
• Previous Day
• Day Before Yesterday
• Pre-Market
• Today
• Current bar
Session Levels [odnac]This indicator plots the high and low levels of the three main trading sessions—Asia, Europe, and New York—along with the previous day’s high, low, and open. Each session’s time range can be customized using a UTC offset, and the indicator automatically tracks session highs and lows as price develops.
Functions:
Plots session highs and lows for Asia, Europe, and New York.
Shows previous day’s high, low, and open as reference levels.
Session times are fully configurable with hour and minute precision, including UTC offset adjustment.
Each session level is marked with both a line and a label for clarity.
Color customization for each session and previous day levels.
Designed for intraday timeframes (1–60 minutes).
Filter Condition:
When the filter option is enabled, the indicator adjusts how levels are drawn:
A session high above the current close is displayed as a solid line with a visible label.
Once price closes above that high, the line becomes dotted and dimmed, and the label also becomes less emphasized.
Similarly, a session low below the current close is displayed as a solid line and label.
If price closes below that low, the line switches to dotted and dimmed, with the label adjusted accordingly.
This behavior highlights only the most relevant levels for the current market position while still keeping breached levels visible in a subdued style, making it easier to spot active breakout or liquidity zones.
Smart Structure Breaks & Order BlocksOverview (What it does)
The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition.
Main Components
Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points.
BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover.
OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone.
Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states.
Input Parameters
Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings.
Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten.
Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows.
Show Swing Points (default ON): Displays triangles on swing highs/lows.
Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover).
Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF).
Signal Definition & Logic
Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel.
BOS (Break of Structure):
Bullish – close breaks last swing high.
Bearish – close breaks last swing low.
Only one valid BOS per swing (avoids duplicates).
OB Detection:
Bullish BOS → previous bearish candle with lowest low forms the OB.
Bearish BOS → previous bullish candle with highest high forms the OB.
Zones: Bull = green, Bear = red, semi-transparent, extended to the right.
Zone States:
Mitigated: Price touches the zone → border highlighted.
Invalidated:
Bull zone → close below → turns red.
Bear zone → close above → turns green.
Chart Appearance
Swing High: red triangle above bar
Swing Low: green triangle below bar
Bull OB: green zone (border highlighted on touch)
Bear OB: red zone (border highlighted on touch)
Invalid Zones: Bull zones turn reddish, Bear zones turn greenish
Practical Use (Trading Assistance)
Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends.
Focus on First Touch: First mitigation after BOS often has higher reaction probability.
Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.).
Stops/Targets:
Bull – stop below zone, partial take profit at swing high or resistance.
Bear – stop above zone, partial take profit at swing low or support.
Parameter Tuning (per market/timeframe)
Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise.
Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals.
Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments.
Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones.
Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter.
Strengths
Standardizes BOS and OB detection that is usually subjective.
Tracks mitigation and invalidation automatically.
Adaptable: allows body/wick zone switching for different instruments.
Limitations
Pivot-based: Signals appear only after pivots confirm (slight lag).
Zones reflect past balance: Can fail after new events (news, earnings, macro data).
Range-heavy markets: More false BOS; consider stricter settings.
Backtesting: This script is for drawing/visual aid; trading rules must be defined separately.
Workflow Example
Identify higher timeframe trend (4H/Daily).
On lower TF (15–60m), wait for BOS and new OB.
Enter on first mitigation with confirmation candle.
Stop beyond zone; targets based on R multiples and swing points.
FAQ
Q: Why are zones invalidated quickly?
A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise.
Q: What does “tagged” mean?
A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled.
Q: Body or Wick zones?
A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas.
Customization Tips (Code perspective)
Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones.
Automated testing: Add strategy.entry/exit for rule-based backtests.
Multi-timeframe: Use request.security() for higher timeframe swings/BOS.
Visualization: Add labels for BOS bars, tag zones with IDs, count touches.
Summary
This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
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.
Essa - Market Structure Crystal Ball SystemEssa - Market Structure Crystal Ball V2.0
Ever wished you had a glimpse into the market's next move? Stop guessing and start anticipating with the Market Structure Crystal Ball!
This isn't just another indicator that tells you what has happened. This is a comprehensive analysis tool that learns from historical price action to forecast the most probable future structure. It combines advanced pattern recognition with essential trading concepts to give you a unique analytical edge.
Key Features
The Predictive Engine (The Crystal Ball)
This is the core of the indicator. It doesn't just identify market structure; it predicts it.
Know the Odds: Get a real-time probability score (%) for the next structural point: Higher High (HH), Higher Low (HL), Lower Low (LL), or Lower High (LH).
Advanced Analysis: The engine considers the pattern sequence, the speed (velocity) of the move, and its size to find the most accurate historical matches.
Dynamic Learning: The indicator constantly updates its analysis as new price data comes in.
The All-in-One Dashboard
Your command center for at-a-glance information. No need to clutter your screen!
Market Phase: Instantly know if the market is in a "🚀 Strong Uptrend," "📉 Steady Downtrend," or "↔️ Consolidation."
Live Probabilities: See the updated forecasts for HH, HL, LL, and LH in a clean, easy-to-read format.
Confidence Level: The dashboard tells you how confident the algorithm is in its current prediction (Low, Medium, or High).
🎯 Dynamic Prediction Zones
Turn probabilities into actionable price areas.
Visual Targets: Based on the highest probability outcome, the indicator draws a target zone on your chart where the next structure point is likely to form.
Context-Aware: These zones are calculated using recent volatility and average swing sizes, making them adaptive to the current market conditions.
🔍 Fair Value Gap (FVG) Detector
Automatically identify and track key price imbalances.
Price Magnets: FVGs are automatically detected and drawn, acting as potential targets for price.
Smart Tracking: The indicator tracks the status of each FVG (Fresh, Partially Filled, or Filled) and uses this data to refine its predictions.
🌍 Trading Session Analysis
Never lose track of key session levels again.
Visualize Sessions: See the Asia, London, and New York sessions highlighted with colored backgrounds.
Key Levels: Automatically plots the high and low of each session, which are often critical support and resistance levels.
Breakout Alerts: Get notified when price breaks a session high or low.
📈 Multi-Timeframe (MTF) Context
Understand the bigger picture by integrating higher timeframe analysis directly onto your chart.
BOS & MSS: Automatically identifies Breaks of Structure (trend continuation) and Market Structure Shifts (potential reversals) from up to two higher timeframes.
Trade with the Trend: Align your intraday trades with the dominant trend for higher probability setups.
⚙️ How It Works in Simple Terms
1️⃣ It Learns: The indicator first identifies all the past swing points (HH, HL, LL, LH) and analyzes their characteristics (speed, size, etc.).
2️⃣ It Finds a Match: It looks at the most recent price action and searches through hundreds of historical bars to find moments that were almost identical.
3️⃣ It Analyzes the Outcome: It checks what happened next in those similar historical scenarios.
4️⃣ It Predicts: Based on that historical data, it calculates the probability of each potential outcome and presents it to you.
🚀 How to Use This Indicator in Your Trading
Confirmation Tool: Use a high probability score (e.g., >60% for a HH) to confirm your own bullish analysis before entering a trade.
Finding High-Probability Zones: Use the Prediction Zones as potential areas to take profit, or as reversal zones to watch for entries in the opposite direction.
Gauging Market Sentiment: Check the "Market Phase" on the dashboard. Avoid forcing trades when the indicator shows "😴 Low Volatility."
Confluence is Key: This indicator is incredibly powerful when combined with your existing strategy. Use it alongside supply/demand zones, moving averages, or RSI for ultimate confirmation.
We hope this tool gives you a powerful new perspective on the market. Dive into the settings to customize it to your liking!
If you find this indicator helpful, please give it a Boost 👍 and leave a comment with your feedback below! Happy trading!
Disclaimer: All predictions are probabilistic and based on historical data. Past performance is not indicative of future results. Always use proper risk management.
Sweep2Trade Pro [CHE]Sweep2Trade Pro \ — Liquidity Sweep → Trend → Confirmation
Sweep2Trade Pro \ helps you catch high-probability reversals or continuations that start with a liquidity sweep, align with the T3 trend, and finalize with a structure confirmation (BOS). It’s designed to reduce noise, time your entries, and keep you out of weak, chop-driven signals.
What’s a “sweep”?
A liquidity sweep happens when price briefly breaks a prior swing high/low (where many stops sit), triggers those stops, and then snaps back. This “stop-hunt” creates liquidity for bigger players and often precedes a sharp move in the opposite direction if the break fails, or fuels continuation if structure actually shifts.
What’s a BOS (Break of Structure)?
A BOS is a price action event where the market takes out a recent swing level in the trend’s direction, signaling continuation and confirming that structure has shifted (bullish BOS through a recent swing high, bearish BOS through a recent swing low).
How the indicator works (at a glance)
1. Regime Filter (T3 + R²)
T3 Moving Average: A smoother, faster-responding moving average that aims to reduce lag while filtering noise, so trend direction changes are clearer.
R² (Coefficient of Determination): Measures how “linear” the recent price path is (0→1). Higher values = stronger, cleaner trend; lower values = more chop. Used here to allow trades only when trend quality exceeds a user-set threshold.
2. Sweep Detection
Bullish sweep: price pokes below a prior swing low and closes back above it.
Bearish sweep: price pokes above a prior swing high and closes back below it.
Lookback length is configurable.
3. Sequence Lock (built-in FSM)
The script manages state in phases so you don’t jump the gun:
Phase 1: Sweep detected → wait for T3 to turn in the corresponding direction.
Phase 2: T3 direction confirmed → show “SWEEP OK” and wait for final confirmation.
Trade Signal: Only fires if confirmation arrives before a timeout.
4. Confirmation Layer
BOS via wick or close (you choose),
Strong close toward the signal (top/bottom quartile of the candle),
Optional “close above/below T3” condition.
These checks help avoid weak sweeps that immediately fade.
5. Alerts & Visuals
“SWEEP OK” markers show when the sweep + T3 direction align.
Final BUY/SELL arrows appear only when the confirmation layer passes.
Ready-made alert conditions for automation.
What you can do with it
Time reversals after sweeps: Enter when a stop-hunt fades and structure confirms.
Ride continuations: Use BOS with the T3 trend to pyramid or re-enter with structure on your side.
Filter chop: Let R² gate entries to periods with cleaner directional drift.
Automate: Use the included alerts with your platform or webhook setup.
Inputs (key settings)
Regime Filter
T3 Length / Volume Factor: Controls smoothness and responsiveness. Smaller length → faster, more sensitive; higher volume factor → smoother curve.
R² Lookback & Threshold: Length of the linear fit window and the minimum “trend quality” required. Higher thresholds mean fewer, cleaner signals.
Sweep / Sequence
Swing Lookback: How far back to define the “reference” high/low for sweeps.
Timeout: Maximum bars allowed between phases to keep signals fresh.
Restart timeout on Phase 2: Optional safety so entries don’t go stale.
Confirmation
BOS Lookback: Micro-pivot window for structure breaks.
Wick vs Close BOS: Conservative traders may prefer close.
Require close above/below T3: Tightens confirmation with trend alignment.
Practical guide (quick start)
1. Timeframe & markets: Works across majors, indices, and crypto. Start with 5m–1h intraday or 1h–4h swing; adjust R² threshold upward on noisier pairs.
2. Entry recipe (Long):
Bullish sweep of a prior low → T3 turns up → BOS/strong close.
Optional: enable “close above T3” for extra confirmation.
3. Entry recipe (Short): Mirror the above.
4. Stops: Common choices are just beyond the sweep wick (tighter) or past the BOS invalidation (safer).
5. Targets: Previous structural levels, measured move, or a T3 trail (exit when price closes back through T3).
6. Avoid low-quality contexts: If R² is very low, market is likely ranging erratically—skip or widen filters.
Tips & best practices
Context first: The same sweep means different things in a strong trend vs. flat regime; that’s why the T3+R² filter exists.
BOS choice: Wick-based BOS is earlier but noisier; close-based BOS is slower but cleaner. Tune per market.
Backtest -> Forward test: Validate settings per symbol/timeframe; then paper trade before going live.
Risk: Fixed fractional risk with asymmetric R\:R (e.g., 1:1.5–1:3) generally performs better than “all-in” discretionary sizing.
Behind the scenes (for the curious)
T3 is a multi-stage EMA construction that produces a smooth curve with reduced lag versus simple/standard EMAs.
R² is the square of correlation (0–1). Here it’s used as a moving gauge of how well price aligns to a linear path—our “trend quality” dial.
Stop-hunts / sweeps are a recognized microstructure phenomenon where clustered stops provide the liquidity that fuels the next move.
Disclaimer
No indicator guarantees profits. Sweep2Trade Pro \ is a decision aid; always combine with solid risk management and your own judgment. Backtest, forward test, and size responsibly.
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence 🚀
Happy trading
Chervolino
