Filtered DTR Table📊 Filtered Daily True Range (DTR) Indicator
This indicator calculates and displays a filtered version of the Daily True Range (DTR) over the last 14 trading days, using high and low prices of each day.
It filters out extreme values by excluding any daily range that is:
Less than 0.5× the average range
Greater than 2× the average range
The indicator shows a table in the bottom-right corner of the main chart, containing:
Filtered ATR – The average of valid (filtered) daily ranges over the past 14 days, based on the high-low difference.
Current Day's Range – The high-low range of the current trading day.
% of ATR – How much of the filtered ATR has been covered by today's range, expressed as a whole number percentage.
在腳本中搜尋"daily"
Levels & Flow📌 Overview
Levels & Flow is a visual trading tool that combines daily pivot levels with a dynamic EMA ribbon to help traders identify structure, momentum, and key decision zones in the market.
This script is designed for discretionary traders who rely on clean visual cues for intraday and swing trading strategies.
⚙️ Key Features
Daily Pivot, Support, and Resistance Lines
Automatically plots the daily pivot level based on the previous day’s OHLC data, along with calculated support and resistance levels.
Fibonacci Retracement Levels
Two dashed lines above and below the pivot represent the retracement of the pivot-resistance and pivot-support range, forming the boundaries of the “no-trade zone.”
No-Trade Zone (Shaded Box)
A gray shaded box between the two Fibonacci levels to visually mark a high-chop/low-conviction zone.
Trend-Based Candle Coloring (Current Day Only)
Candles are colored green if the close is above the pivot, red if below (only on the current trading day).
Bullish/Bearish Trend Label
A small table in the bottom-right corner displays “Bullish” or “Bearish” depending on whether price is above or below the pivot.
20-EMA Gradient Ribbon
A stack of 20 EMAs, each smoothed and color-coded from blue to green to reflect short- to long-term trend alignment.
Cumulative EMA with Adaptive Weighting
An intelligent moving average line that adjusts weight distribution among the 20 EMAs based on recent predictive accuracy using a learning rate and lookback period.
🧠 How It Works
📍 Levels
The script calculates daily pivot, resistance, and support levels using standard formulas:
Pivot = (High + Low + Close) / 3
Resistance = (2 × Pivot) – Low
Support = (2 × Pivot) – High
These levels update each day and extend 143 bars to the right.
📏 Fib Lines
Fib Up = Pivot + (Resistance – Pivot) × 0.382
Fib Down = Pivot – (Pivot – Support) × 0.382
These lines form the “no-trade zone” box.
📈 EMA Ribbon
20 EMAs starting from the user-defined Base Length, each incremented by 1
Each EMA is smoothed using the Smoothing Period
Color-coded from blue to green for intuitive visual flow
Filled between EMAs to visualize trend strength and alignment
🧠 Cumulative EMA Learning
Each EMA’s historical error is calculated over a Lookback Period
Lower-error EMAs receive higher weight; weights are normalized to sum to 1
The result is a cumulative EMA that adapts based on historical predictive power
🔧 User Inputs
Input
Base EMA Length: Sets the period for the shortest EMA (default: 20)
Smoothing Period: Smooths all EMAs and the cumulative EMA
Lookback for Learning: Number of bars to evaluate EMA prediction accuracy
Learning Rate: Adjusts how quickly weights shift in favor of more accurate EMAs
✅ How to Use It
Use the pivot level to define directional bias.
Watch for price breakouts above resistance or breakdowns below support to consider entry.
Avoid trading inside the shaded zone, where direction is less reliable.
Use the EMA ribbon gradient to confirm short/long alignment.
The cumulative EMA helps define trend with noise reduction.
🧪 Best For
Intraday traders who want to blend structure with flow
Swing traders needing clean daily levels with dynamic confirmation
Anyone looking to avoid choppy zones and improve visual clarity
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a trading recommendation. Always test scripts in simulation or on demo accounts before live use. Use at your own risk.
Filt ADR🟠 Script Name: Filtered Average Daily Range (Filt ADR)
This script calculates a filtered version of the Average Daily Range (ADR) based on the last 14 daily candles. It's designed to reduce the influence of unusually high or low daily ranges (outliers) by applying a filter before calculating the average.
🔧 How It Works — Step by Step
1. Calculate Daily Ranges (High - Low)
It retrieves the daily price ranges (difference between daily high and low) for the last 14 days using request.security() with the "D" (daily) timeframe.
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high - low // today's daily range
high - low // yesterday's daily range
...
These values are stored into individual variables dr0 to dr13.
2. Build an Array of Daily Ranges
An array named ranges is used to store the 14 daily ranges, but only if they are not na (missing data). This avoids errors during processing.
3. Calculate the Initial (Unfiltered) Average Range
The script sums all values in the ranges array and calculates their average:
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avg_all = total sum of ranges / number of valid entries
4. Filter Out Outliers
Now it filters the values in ranges:
Only keeps the ranges that are between 0.5×avg_all and 2×avg_all.
This is to remove abnormally small or large daily ranges that could distort the average.
The filtered values are added to a second array called filtered.
5. Calculate the Filtered ADR
Finally, it calculates the average of the filtered daily ranges:
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avg_filt = sum of filtered ranges / number of filtered values
This is the Filtered ADR.
6. Plot the Result
The result (avg_filt) is plotted as an orange line on the chart. It updates on each bar (depending on the current timeframe you're viewing) but the underlying data is based on the last 14 daily candles.
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plot(avg_filt, title="Filtered ADR", color=color.orange, linewidth=2)
✅ Use Case
This script is useful for traders who use the Average Daily Range (ADR) to:
Estimate expected price movement during a day
Set volatility-based stop-loss or take-profit levels
Identify days with unusually high or low volatility
By filtering out extreme values, it provides a more stable and reliable estimate of daily volatility.
P1 & P2 Helper by Brighter DataThis script draws the current high & low on the chart for multiple timeframes in P1/P2 format: P1 is either the highest or lowest point of the timeframe, whichever came first. P2 is whichever came second.
For example, on the daily timeframe if the daily low is marked out as P1 and the daily high is P2, it means that the daily low was put in before the daily high. This mapping of highs/lows is used as support for the BD dashboard and its statistics.
Seasonality DOW CombinedOverall Purpose
This script analyzes historical daily returns based on two specific criteria:
Month of the year (January through December)
Day of the week (Sunday through Saturday)
It summarizes and visually displays the average historical performance of the selected asset by these criteria over multiple years.
Step-by-Step Breakdown
1. Initial Settings:
Defines minimum year (i_year_start) from which data analysis will start.
Ensures the user is using a daily timeframe, otherwise prompts an error.
Sets basic display preferences like text size and color schemes.
2. Data Collection and Variables:
Initializes matrices to store and aggregate returns data:
month_data_ and month_agg_: store monthly performance.
dow_data_ and dow_agg_: store day-of-week performance.
COUNT tracks total number of occurrences, and COUNT_POSITIVE tracks positive-return occurrences.
3. Return Calculation:
Calculates daily percentage change (chg_pct_) in price:
chg_pct_ = close / close - 1
Ensures it captures this data only for the specified years (year >= i_year_start).
4. Monthly Performance Calculation:
Each daily return is grouped by month:
matrix.set updates total returns per month.
The script tracks:
Monthly cumulative returns
Number of occurrences (how many days recorded per month)
Positive occurrences (days with positive returns)
5. Day-of-Week Performance Calculation:
Similarly, daily returns are also grouped by day-of-the-week (Sunday to Saturday):
Daily return values are summed per weekday.
The script tracks:
Cumulative returns per weekday
Number of occurrences per weekday
Positive occurrences per weekday
6. Visual Display (Tables):
The script creates two visual tables:
Left Table: Monthly Performance.
Right Table: Day-of-the-Week Performance.
For each table, it shows:
Yearly data for each month/day.
Summaries at the bottom:
SUM row: Shows total accumulated returns over all selected years for each month/day.
+ive row: Shows percentage (%) of times the month/day had positive returns, along with a tooltip displaying positive occurrences vs total occurrences.
Cells are color-coded:
Green for positive returns.
Red for negative returns.
Gray for neutral/no change.
7. Interpreting the Tables:
Monthly Table (left side):
Helps identify seasonal patterns (e.g., historically bullish/bearish months).
Day-of-Week Table (right side):
Helps detect recurring weekday patterns (e.g., historically bullish Mondays or bearish Fridays).
Practical Use:
Traders use this to:
Identify patterns based on historical data.
Inform trading strategies, e.g., avoiding historically bearish days/months or leveraging historically bullish periods.
Example Interpretation:
If the table shows consistently green (positive) for March and April, historically the asset tends to perform well during spring. Similarly, if the "Friday" column is often red, historically Fridays are bearish for this asset.
Kinetic Price Momentum Oscillator📈 Kinetic Price Momentum Oscillator (Sri-PMO)
Author's Note:
This script is an educational and custom-adapted visualization based on the concept of the Price Momentum Oscillator (PMO). It is not a direct clone of any proprietary implementation, and it introduces enhancements such as timeframe sensitivity, customizable smoothings, multi-timeframe analysis, and visual trend meters.
🔍 Overview:
The Kinetic Price Momentum Oscillator (Kinetic-PMO) is a dynamic momentum indicator that analyzes price rate of change smoothed with dual exponential moving averages. It offers a clear view of momentum trends across multiple timeframes—the chart's current timeframe, the 1-hour timeframe, and the 1-day timeframe. It includes optional visual cues for zero-line crossovers, trend ribbon fills, and a daily trend meter.
🧮 Calculation Logic:
At its core, Kinetic-PMO calculates momentum by:
Measuring Rate of Change (ROC) over 1 bar.
Applying double EMA smoothing:
The first smoothing (len1) smooths the ROC.
The second smoothing (len2) smooths the result further.
This produces the main KPMO Line.
A third EMA (sigLen) is applied to the KPMO line to produce the Signal Line.
The formula includes a multiplier of 10 to scale values.
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roc = ta.roc(source, 1)
kmo = ta.ema(10 * ta.ema(roc, len1), len2)
signal = ta.ema(kmo, sigLen)
To allow responsiveness across timeframes, the script provides sensitivity inputs (sensA, sensB, sensC) which dynamically scale the smoothing lengths for different contexts:
Intraday (current chart timeframe)
Hourly (1H)
Daily (1D)
🧭 Features:
✅ Multi-Timeframe Calculation:
Intraday: Based on current chart resolution
1H: PMO for the hourly trend
1D: Daily trend meter using KPMO structure
✅ Trend Identification:
Green if PMO is above Signal Line (bullish)
Red if PMO is below Signal Line (bearish)
Daily Trend Meter includes nuanced color mapping:
Lime = Bullish above zero
Orange = Bullish below zero
Red = Bearish below zero
Yellow = Bearish above zero
✅ Custom Visual Enhancements:
Optional filled ribbons between KPMO and Signal
Optional zero-line crossover background highlight
Compact daily trend meter displayed as a color-coded shape
🛠 Customization Parameters:
Input Description
Primary Smoothing Controls ROC smoothing depth (1st EMA)
Secondary Smoothing Controls final smoothing (2nd EMA)
Signal Smoothing Controls EMA of the PMO line
Input Source Default is close, but any price type can be selected
Sensitivity Factors Separate multipliers for intraday, 1H, and 1D
Visual Settings Toggle zero-line highlight and ribbon fill
🧠 Intended Use:
The Kinetic-PMO is suitable for trend confirmation, momentum divergence detection, and entry/exit refinement. The multi-timeframe aspect helps align short-term and long-term momentum trends, supporting better trade decision-making.
⚖️ Legal & Attribution Statement:
This script was independently created and modified for educational and analytical purposes. While the concept of the PMO is inspired by technical analysis literature, this implementation does not copy or reverse-engineer any proprietary code. It introduces custom parameters, visualization enhancements, and multi-timeframe logic. Posting this script complies with TradingView’s policy on derivative work and educational indicators.
Enhanced Volume Trend Indicator with BB SqueezeEnhanced Volume Trend Indicator with BB Squeeze: Comprehensive Explanation
The visualization system allows traders to quickly scan multiple securities to identify high-probability setups without detailed analysis of each chart. The progression from squeeze to breakout, supported by volume trend confirmation, offers a systematic approach to identifying trading opportunities.
The script combines multiple technical analysis approaches into a comprehensive dashboard that helps traders make informed decisions by identifying high-probability setups while filtering out noise through its sophisticated confirmation requirements. It combines multiple technical analysis approaches into an integrated visual system that helps traders identify potential trading opportunities while filtering out false signals.
Core Features
1. Volume Analysis Dashboard
The indicator displays various volume-related metrics in customizable tables:
AVOL (After Hours + Pre-Market Volume): Shows extended hours volume as a percentage of the 21-day average volume with color coding for buying/selling pressure. Green indicates buying pressure and red indicates selling pressure.
Volume Metrics: Includes regular volume (VOL), dollar volume ($VOL), relative volume compared to 21-day average (RVOL), and relative volume compared to 90-day average (RVOL90D).
Pre-Market Data: Optional display of pre-market volume (PVOL), pre-market dollar volume (P$VOL), pre-market relative volume (PRVOL), and pre-market price change percentage (PCHG%).
2. Enhanced Volume Trend (VTR) Analysis
The Volume Trend indicator uses adaptive analysis to evaluate buying and selling pressure, combining multiple factors:
MACD (Moving Average Convergence Divergence) components
Volume-to-SMA (Simple Moving Average) ratio
Price direction and market conditions
Volume change rates and momentum
EMA (Exponential Moving Average) alignment and crossovers
Volatility filtering
VTR Visual Indicators
The VTR score ranges from 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions. This is visually represented by colored circles:
"●" (Filled Circle):
Green: Strong bullish trend (VTR ≥ 80)
Red: Strong bearish trend (VTR ≤ 20)
"◯" (Hollow Circle):
Green: Moderate bullish trend (VTR 65-79)
Red: Moderate bearish trend (VTR 21-35)
"·" (Small Dot):
Green: Weak bullish trend (VTR 55-64)
Red: Weak bearish trend (VTR 36-45)
"○" (Medium Hollow Circle): Neutral conditions (VTR 46-54), shown in gray
In "Both" display mode, the VTR shows both the numerical score (0-100) alongside the appropriate circle symbol.
Enhanced VTR Settings
The Enhanced Volume Trend component offers several advanced customization options:
Adaptive Volume Analysis (volTrendAdaptive):
When enabled, dynamically adjusts volume thresholds based on recent market volatility
Higher volatility periods require proportionally higher volume to generate significant signals
Helps prevent false signals during highly volatile markets
Keep enabled for most trading conditions, especially in volatile markets
Speed of Change Weight (volTrendSpeedWeight, range 0-1):
Controls emphasis on volume acceleration/deceleration rather than absolute levels
Higher values (0.7-1.0): More responsive to new volume trends, better for momentum trading
Lower values (0.2-0.5): Less responsive, better for trend following
Helps identify early volume trends before they fully develop
Momentum Period (volTrendMomentumPeriod, range 2-10):
Defines lookback period for volume change rate calculations
Lower values (2-3): More responsive to recent changes, better for short timeframes
Higher values (7-10): Smoother, better for daily/weekly charts
Directly affects how quickly the indicator responds to new volume patterns
Volatility Filter (volTrendVolatilityFilter):
Adjusts significance of volume by factoring in current price volatility
High volume during high volatility receives less weight
High volume during low volatility receives more weight
Helps distinguish between genuine volume-driven moves and volatility-driven moves
EMA Alignment Weight (volTrendEmaWeight, range 0-1):
Controls importance of EMA alignments in final VTR calculation
Analyzes multiple EMA relationships (5, 10, 21 period)
Higher values (0.7-1.0): Greater emphasis on trend structure
Lower values (0.2-0.5): More focus on pure volume patterns
Display Mode (volTrendDisplayMode):
"Value": Shows only numerical score (0-100)
"Strength": Shows only symbolic representation
"Both": Shows numerical score and symbol together
3. Bollinger Band Squeeze Detection (SQZ)
The BB Squeeze indicator identifies periods of low volatility when Bollinger Bands contract inside Keltner Channels, often preceding significant price movements.
SQZ Visual Indicators
"●" (Filled Circle): Strong squeeze - high probability setup for an impending breakout
Green: Strong squeeze with bullish bias (likely upward breakout)
Red: Strong squeeze with bearish bias (likely downward breakout)
Orange: Strong squeeze with unclear direction
"◯" (Hollow Circle): Moderate squeeze - medium probability setup
Green: With bullish EMA alignment
Red: With bearish EMA alignment
Orange: Without clear directional bias
"-" (Dash): Gray dash indicates no squeeze condition (normal volatility)
The script identifies squeeze conditions through multiple methods:
Bollinger Bands contracting inside Keltner Channels
BB width falling to bottom 20% of recent range (BB width percentile)
Very narrow Keltner Channel (less than 5% of basis price)
Tracking squeeze duration in consecutive bars
Different squeeze strengths are detected:
Strong Squeeze: BB inside KC with tight BB width and narrow KC
Moderate Squeeze: BB inside KC with either tight BB width or narrow KC
No Squeeze: Normal market conditions
4. Breakout Detection System
The script includes two breakout indicators working in sequence:
4.1 Pre-Breakout (PBK) Indicator
Detects potential upcoming breakouts by analyzing multiple factors:
Squeeze conditions lasting 2-3 bars or more
Significant price ranges
Strong volume confirmation
EMA/MACD crossovers
Consistent price direction
PBK Visual Indicators
"●" (Filled Circle): Detected pre-breakout condition
Green: Likely upward breakout (bullish)
Red: Likely downward breakout (bearish)
Orange: Direction not yet clear, but breakout likely
"-" (Dash): Gray dash indicates no pre-breakout condition
The PBK uses sophisticated conditions to reduce false signals including minimum squeeze length, significant price movement, and technical confirmations.
4.2 Breakout (BK) Indicator
Confirms actual breakouts in progress by identifying:
End of squeeze or strong expansion of Bollinger Bands
Volume expansion
Price moving outside Bollinger Bands
EMA crossovers with volume confirmation
MACD crossovers with significant price range
BK Visual Indicators
"●" (Filled Circle): Confirmed breakout in progress
Green: Upward breakout (bullish)
Red: Downward breakout (bearish)
Orange: Unusual breakout pattern without clear direction
"◆" (Diamond): Special breakout conditions (meets some but not all criteria)
"-" (Dash): Gray dash indicates no breakout detected
The BK indicator uses advanced filters for confirmation:
Requires consecutive breakout signals to reduce false positives
Strong volume confirmation requirements (40% above average)
Significant price movement thresholds
Consistency checks between price action and indicators
5. Market Metrics and Analysis
Price Change Percentage (CHG%)
Displays the current percentage change relative to the previous day's close, color-coded green for positive changes and red for negative changes.
Average Daily Range (ADR%)
Calculates the average daily percentage range over a specified period (default 20 days), helping traders gauge volatility and set appropriate price targets.
Average True Range (ATR)
Shows the Average True Range value, a volatility indicator developed by J. Welles Wilder that measures market volatility by decomposing the entire range of an asset price for that period.
Relative Strength Index (RSI)
Displays the standard 14-period RSI, a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100.
6. External Market Indicators
QQQ Change
Shows the percentage change in the Invesco QQQ Trust (tracking the Nasdaq-100 Index), useful for understanding broader tech market trends.
UVIX Change
Displays the percentage change in UVIX, a volatility index, providing insight into market fear and potential hedging activity.
BTC-USD
Shows the current Bitcoin price from Coinbase, useful for traders monitoring crypto correlation with equities.
Market Breadth (BRD)
Calculates the percentage difference between ATHI.US and ATLO.US (high vs. low securities), indicating overall market direction and strength.
7. Session Analysis and Volume Direction
Session Detection
The script accurately identifies different market sessions:
Pre-market: 4:00 AM to 9:30 AM
Regular market: 9:30 AM to 4:00 PM
After-hours: 4:00 PM to 8:00 PM
Closed: Outside trading hours
This detection works on any timeframe through careful calculation of current time in seconds.
Buy/Sell Volume Direction
The script analyzes buying and selling pressure by:
Counting up volume when close > open
Counting down volume when close < open
Tracking accumulated volume within the day
Calculating intraday pressure (up volume minus down volume)
Enhanced AVOL Calculation
The improved AVOL calculation works in all timeframes by:
Estimating typical pre-market and after-hours volume percentages
Combining yesterday's after-hours with today's pre-market volume
Calculating this as a percentage of the 21-day average volume
Determining buying/selling pressure by analyzing after-hours and pre-market price changes
Color-coding results: green for buying pressure, red for selling pressure
This calculation is particularly valuable because it works consistently across any timeframe.
Customization Options
Display Settings
The dashboard has two customizable tables: Volume Table and Metrics Table, with positions selectable as bottom_left or bottom_right.
All metrics can be individually toggled on/off:
Pre-market data (PVOL, P$VOL, PRVOL, PCHG%)
Volume data (AVOL, RVOL Day, RVOL 90D, Volume, SEED_YASHALGO_NSE_BREADTH:VOLUME )
Price metrics (ADR%, ATR, RSI, Price Change%)
Market indicators (QQQ, UVIX, Breadth, BTC-USD)
Analysis indicators (Volume Trend, BB Squeeze, Pre-Breakout, Breakout)
These toggle options allow traders to customize the dashboard to show only the metrics they find most valuable for their trading style.
Table and Text Customization
The dashboard's appearance can be customized:
Table background color via tableBgColor
Text color (White or Black) via textColorOption
The indicator uses smart formatting for volume and price values, automatically adding appropriate suffixes (K, M, B) for readability.
MACD Configuration for VTR
The Volume Trend calculation incorporates MACD with customizable parameters:
Fast Length: Controls the period for the fast EMA (default 3)
Slow Length: Controls the period for the slow EMA (default 9)
Signal Length: Controls the period for the signal line EMA (default 5)
MACD Weight: Controls how much influence MACD has on the volume trend score (default 0.3)
These settings allow traders to fine-tune how momentum is factored into the volume trend analysis.
Bollinger Bands and Keltner Channel Settings
The Bollinger Bands and Keltner Channels used for squeeze detection have preset (hidden) parameters:
BB Length: 20 periods
BB Multiplier: 2.0 standard deviations
Keltner Length: 20 periods
Keltner Multiplier: 1.5 ATR
These settings follow standard practice for squeeze detection while maintaining simplicity in the user interface.
Practical Trading Applications
Complete Trading Strategies
1. Squeeze Breakout Strategy
This strategy combines multiple components of the indicator:
Wait for a strong squeeze (SQZ showing ●)
Look for pre-breakout confirmation (PBK showing ● in green or red)
Enter when breakout is confirmed (BK showing ● in same direction)
Use VTR to confirm volume supports the move (VTR ≥ 65 for bullish or ≤ 35 for bearish)
Set profit targets based on ADR (Average Daily Range)
Exit when VTR begins to weaken or changes direction
2. Volume Divergence Strategy
This strategy focuses on the volume trend relative to price:
Identify when price makes a new high but VTR fails to confirm (divergence)
Look for VTR to show weakening trend (● changing to ◯ or ·)
Prepare for potential reversal when SQZ begins to form
Enter counter-trend position when PBK confirms reversal direction
Use external indicators (QQQ, BTC, Breadth) to confirm broader market support
3. Pre-Market Edge Strategy
This strategy leverages pre-market data:
Monitor AVOL for unusual pre-market activity (significantly above 100%)
Check pre-market price change direction (PCHG%)
Enter position at market open if VTR confirms direction
Use SQZ to determine if volatility is likely to expand
Exit based on RVOL declining or price reaching +/- ADR for the day
Market Context Integration
The indicator provides valuable context for trading decisions:
QQQ change shows tech market direction
BTC price shows crypto market correlation
UVIX change indicates volatility expectations
Breadth measurement shows market internals
This context helps traders avoid fighting the broader market and align trades with overall market direction.
Timeframe Optimization
The indicator is designed to work across different timeframes:
For day trading: Focus on AVOL, VTR, PBK/BK, and use shorter momentum periods
For swing trading: Focus on SQZ duration, VTR strength, and broader market indicators
For position trading: Focus on larger VTR trends and use EMA alignment weight
Advanced Analytical Components
Enhanced Volume Trend Score Calculation
The VTR score calculation is sophisticated, with the base score starting at 50 and adjusting for:
Price direction (up/down)
Volume relative to average (high/normal/low)
Volume acceleration/deceleration
Market conditions (bull/bear)
Additional factors are then applied, including:
MACD influence weighted by strength and direction
Volume change rate influence (speed)
Price/volume divergence effects
EMA alignment scores
Volatility adjustments
Breakout strength factors
Price action confirmations
The final score is clamped between 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions.
Anti-False Signal Filters
The indicator employs multiple techniques to reduce false signals:
Requiring significant price range (minimum percentage movement)
Demanding strong volume confirmation (significantly above average)
Checking for consistent direction across multiple indicators
Requiring prior bar consistency (consecutive bars moving in same direction)
Counting consecutive signals to filter out noise
These filters help eliminate noise and focus on high-probability setups.
MACD Enhancement and Integration
The indicator enhances standard MACD analysis:
Calculating MACD relative strength compared to recent history
Normalizing MACD slope relative to volatility
Detecting MACD acceleration for stronger signals
Integrating MACD crossovers with other confirmation factors
EMA Analysis System
The indicator uses a comprehensive EMA analysis system:
Calculating multiple EMAs (5, 10, 21 periods)
Detecting golden cross (10 EMA crosses above 21 EMA)
Detecting death cross (10 EMA crosses below 21 EMA)
Assessing price position relative to EMAs
Measuring EMA separation percentage
Recent Enhancements and Evolution
Version 5.2 includes several improvements:
Enhanced AVOL to show buying/selling direction through color coding
Improved VTR with adaptive analysis based on market conditions
AVOL display now works in all timeframes through sophisticated estimation
Removed animal symbols and streamlined code with bright colors for better visibility
Improved anti-false signal filters throughout the system
Optimizing Indicator Settings
For Different Market Types
Range-Bound Markets:
Lower EMA Alignment Weight (0.2-0.4)
Higher Speed of Change Weight (0.8-1.0)
Focus on SQZ and PBK signals for breakout potential
Trending Markets:
Higher EMA Alignment Weight (0.7-1.0)
Moderate Speed of Change Weight (0.4-0.6)
Focus on VTR strength and BK confirmations
Volatile Markets:
Enable Volatility Filter
Enable Adaptive Volume Analysis
Lower Momentum Period (2-3)
Focus on strong volume confirmation (VTR ≥ 80 or ≤ 20)
For Different Asset Classes
Equities:
Standard settings work well
Pay attention to AVOL for gap potential
Monitor QQQ correlation
Futures:
Consider higher Volume/RVOL weight
Reduce MACD weight slightly
Pay close attention to SQZ duration
Crypto:
Higher volatility thresholds may be needed
Monitor BTC price for correlation
Focus on stronger confirmation signals
Integrated Visual System for Trading Decisions
The colored circle indicators create an intuitive visual system for quick market assessment:
Progression Sequence: SQZ (Squeeze) → PBK (Pre-Breakout) → BK (Breakout)
This sequence often occurs in order, with the squeeze leading to pre-breakout conditions, followed by an actual breakout.
VTR (Volume Trend): Provides context about the volume supporting these movements.
Color Coding: Green for bullish conditions, red for bearish conditions, and orange/gray for neutral or undefined conditions.
Yearly History Calendar-Aligned Price up to 10 Years)Overview
This indicator helps traders compare historical price patterns from the past 10 calendar years with the current price action. It overlays translucent lines (polylines) for each year’s price data on the same calendar dates, providing a visual reference for recurring trends. A dynamic table at the top of the chart summarizes the active years, their price sources, and history retention settings.
Key Features
Historical Projections
Displays price data from the last 10 years (e.g., January 5, 2023 vs. January 5, 2024).
Price Source Selection
Choose from Open, Low, High, Close, or HL2 ((High + Low)/2) for historical alignment.
The selected source is shown in the legend table.
Bulk Control Toggles
Show All Years : Display all 10 years simultaneously.
Keep History for All : Preserve historical lines on year transitions.
Hide History for All : Automatically delete old lines to update with current data.
Individual Year Settings
Toggle visibility for each year (-1 to -10) independently.
Customize color and line width for each year.
Control whether to keep or delete historical lines for specific years.
Visual Alignment Aids
Vertical lines mark yearly transitions for reference.
Polylines are semi-transparent for clarity.
Dynamic Legend Table
Shows active years, their price sources, and history status (On/Off).
Updates automatically when settings change.
How to Use
Configure Settings
Projection Years : Select how many years to display (1–10).
Price Source : Choose Open, Low, High, Close, or HL2 for historical alignment.
History Precision : Set granularity (Daily, 60m, or 15m).
Daily (D) is recommended for long-term analysis (covers 10 years).
60m/15m provides finer precision but may only cover 1–3 years due to data limits.
Adjust Visibility & History
Show Year -X : Enable/disable specific years for comparison.
Keep History for Year -X : Choose whether to retain historical lines or delete them on new year transitions.
Bulk Controls
Show All Years : Display all 10 years at once (overrides individual toggles).
Keep History for All / Hide History for All : Globally enable/disable history retention for all years.
Customize Appearance
Line Width : Adjust polyline thickness for better visibility.
Colors : Assign unique colors to each year for easy identification.
Interpret the Legend Table
The table shows:
Year : Label (e.g., "Year -1").
Source : The selected price type (e.g., "Close", "HL2").
Keep History : Indicates whether lines are preserved (On) or deleted (Off).
Tips for Optimal Use
Use Daily Timeframes for Long-Term Analysis :
Daily (1D) allows 10+ years of data. Smaller timeframes (60m/15m) may have limited historical coverage.
Compare Recurring Patterns :
Look for overlaps between historical polylines and current price to identify potential support/resistance levels.
Customize Colors & Widths :
Use contrasting colors for years you want to highlight. Adjust line widths to avoid clutter.
Leverage Global Toggles :
Enable Show All Years for a quick overview. Use Keep History for All to maintain continuity across transitions.
Example Workflow
Set Up :
Select Projection Years = 5.
Choose Price Source = Close.
Set History Precision = 1D for long-term data.
Customize :
Enable Show Year -1 to Show Year -5.
Assign distinct colors to each year.
Disable Keep History for All to ensure lines update on year transitions.
Analyze :
Observe how the 2023 close prices align with 2024’s price action.
Use vertical lines to identify yearly boundaries.
Common Questions
Why are some years missing?
Ensure the chart has sufficient historical data (e.g., daily charts cover 10 years, 60m/15m may only cover 1–3 years).
How do I update the data?
Adjust the Price Source or toggle years/history settings. The legend table updates automatically.
Stochastic RSI with MTF TableShort Description of the Script
The provided Pine Script indicator, titled "Stochastic RSI with MTF Table," calculates and displays the Stochastic RSI for the current timeframe and multiple other timeframes (5m, 15m, 30m, 60m, 240m, and daily). The Stochastic RSI is a momentum indicator that blends the Relative Strength Index (RSI) and Stochastic Oscillator to identify overbought and oversold conditions, as well as potential trend reversals via K and D line crossovers.
Key features of the script include:
Inputs: Customizable parameters such as K smoothing (default 3), D smoothing (default 3), RSI length (default 14), Stochastic length (default 14), source price (default close), and overbought/oversold levels (default 80/20).
MTF Table: A table displays the Stochastic RSI status for each timeframe:
"OB" (overbought) if K > 80, "OS" (oversold) if K < 20, or "N" (neutral) otherwise.
Crossovers: "K↑D" for bullish (K crosses above D) and "K↓D" for bearish (K crosses below D).
Visualization: Plots the K and D lines for the current timeframe, with horizontal lines at 80 (overbought), 50 (middle), and 20 (oversold), plus a background fill for clarity.
Table Position: Configurable to appear in one of four chart corners (default: top-right).
This indicator helps traders assess momentum across multiple timeframes simultaneously, aiding in the identification of trend strength and potential entry/exit points.
Trading Strategy with 50EMA and 200EMA for Highest Winning Rate
To create a strategy with the best probability of a high winning rate using the Stochastic RSI MTF indicator alongside the 50-period Exponential Moving Average (50EMA) and 200-period Exponential Moving Average (200EMA), we can combine trend identification with momentum-based entry timing. The 50EMA and 200EMA are widely used to determine medium- and long-term trends, while the Stochastic RSI MTF table provides multi-timeframe momentum signals. Here’s the strategy:
1. Determine the Overall Trend
Bullish Trend: The 50EMA is above the 200EMA on the current timeframe (e.g., daily or 60m chart). This suggests an uptrend, often associated with a "Golden Cross."
Bearish Trend: The 50EMA is below the 200EMA on the current timeframe. This indicates a downtrend, often linked to a "Death Cross."
Implementation: Plot the 50EMA and 200EMA on your chart and visually confirm their relative positions.
2. Identify Entry Signals Using the Stochastic RSI MTF Table
In a Bullish Trend (50EMA > 200EMA):
Look for timeframes in the MTF table showing:
Oversold (OS): K < 20, indicating a potential pullback in the uptrend where price may rebound.
Bullish Crossover (K↑D): K crosses above D, signaling rising momentum and a potential entry point.
Example: If the 60m and 240m timeframes show "OS" or "K↑D," this could be a buy signal.
In a Bearish Trend (50EMA < 200EMA):
Look for timeframes in the MTF table showing:
Overbought (OB): K > 80, suggesting a rally in the downtrend where price may reverse downward.
Bearish Crossover (K↓D): K crosses below D, indicating declining momentum and a potential short entry.
Example: If the 30m and daily timeframes show "OB" or "K↓D," this could be a sell/short signal.
Current Timeframe Check: Use the plotted K and D lines on your trading timeframe for precise entry timing (e.g., confirm a K↑D crossover on a 60m chart for a long trade).
3. Confirm Signals Across Multiple Timeframes
Strengthen the Signal: A higher winning rate is more likely when multiple timeframes align with the trend and signal. For instance:
Bullish trend + "OS" or "K↑D" on 60m, 240m, and daily = strong buy signal.
Bearish trend + "OB" or "K↓D" on 15m, 60m, and 240m = strong sell signal.
Prioritize Higher Timeframes: Signals from the 240m or daily timeframe carry more weight due to their indication of broader trends, increasing reliability.
4. Set Stop-Loss and Take-Profit Levels
Long Trades (Bullish):
Stop-Loss: Place below the most recent swing low or below the 50EMA, whichever is closer, to protect against trend reversals.
Take-Profit: Target a key resistance level or use a risk-reward ratio (e.g., 2:1 or 3:1) based on the stop-loss distance.
Short Trades (Bearish):
Stop-Loss: Place above the most recent swing high or above the 50EMA, whichever is closer.
Take-Profit: Target a key support level or apply a similar risk-reward ratio.
Trailing Stop Option: As the trend progresses, trail the stop below the 50EMA (for longs) or above it (for shorts) to lock in profits.
5. Risk Management
Position Sizing: Risk no more than 1-2% of your trading capital per trade to minimize losses from false signals.
Volatility Consideration: Adjust stop-loss distances and position sizes based on the asset’s volatility (e.g., wider stops for volatile stocks or crypto).
Avoid Overtrading: Wait for clear alignment between the EMA trend and MTF signals to avoid low-probability setups.
Example Scenario
Chart: 60-minute timeframe.
Trend: 50EMA > 200EMA (bullish).
MTF Table: 60m shows "OS," 240m shows "K↑D," and daily is "N."
Action: Enter a long position when the 60m K line crosses above D, confirming the table signal.
Stop-Loss: Below the recent 60m swing low (e.g., 2% below entry).
Take-Profit: At the next resistance level or a 3:1 reward-to-risk ratio.
Outcome: High probability of success due to trend alignment and multi-timeframe confirmation.
Why This Strategy Works
Trend Following: Trading in the direction of the 50EMA/200EMA trend reduces the risk of fighting the market’s momentum.
Momentum Timing: The Stochastic RSI MTF table pinpoints pullbacks or reversals within the trend, improving entry timing.
Multi-Timeframe Confirmation: Alignment across timeframes filters out noise, increasing the win rate.
Risk Control: Defined stop-loss and position sizing protect against inevitable losses.
Caveats
No strategy guarantees a 100% win rate; false signals can occur, especially in choppy markets.
Test this strategy on historical data or a demo account to verify its effectiveness for your asset and timeframe.
This approach leverages the strengths of both trend-following (EMA) and momentum (Stochastic RSI) tools, aiming for a high-probability, disciplined trading system.
IBD Style Candles [tradeviZion]IBD Style Candles - Visualize Price Bars Like the Pros
Transform your chart with institutional-grade IBD-style bars and customizable moving averages for both daily and weekly timeframes. This indicator helps you visualize price action the way professionals at Investors Business Daily do.
What This Indicator Offers:
IBD-style bar visualization (clean, professional appearance)
Customizable coloring based on price movement or previous close
Automatic timeframe detection for appropriate moving averages
Four customizable moving averages for daily timeframes (10, 21, 50, 200)
Four customizable moving averages for weekly timeframes (10, 20, 30, 40)
Options to use SMAs or EMAs with adjustable colors and line widths
"The IBD-style bars provide a cleaner view of price action, allowing you to focus on market structure without the visual noise of traditional candles."
How to Apply the IBD-Style Bars:
On your TradingView chart, select "Bars" as the chart type from the main chart type selection menu (next to the time interval options).
Right-click on the chart and select "Settings".
Go to the "Symbol" tab.
Uncheck the "Thin Bars" option to display thicker bars.
Set the "Up Color" and "Down Color" opacity to 0 for a clean IBD-style appearance.
Enable "IBD-style Candles" from the script's settings.
To revert to the original chart style, repeat the above steps and restore the default settings.
Moving Average Configuration:
The indicator automatically detects your timeframe and displays the appropriate moving averages:
Daily Timeframe Moving Averages:
10-day moving average (SMA/EMA)
21-day moving average (SMA/EMA)
50-day moving average (SMA/EMA)
200-day moving average (SMA/EMA)
Weekly Timeframe Moving Averages:
10-week moving average (SMA/EMA)
20-week moving average (SMA/EMA)
30-week moving average (SMA/EMA)
40-week moving average (SMA/EMA)
Usage Tips:
Enable "Color bars based on previous close" to identify momentum shifts based on prior candle closes
Customize colors to match your chart theme or preference
Enable only the moving averages relevant to your trading strategy
For cleaner charts, reduce the number of visible moving averages
For stock trading, the 10/21/50/200 daily and 10/40 weekly MAs are most commonly used by institutions
// Example configuration for different timeframes
if timeframe.isweekly
// Weekly configuration
showSMA1_Weekly = true // 10-week MA
showSMA4_Weekly = true // 40-week MA
else
// Daily configuration
showMA2_Daily = true // 21-day MA
showMA3_Daily = true // 50-day MA
showMA4_Daily = true // 200-day MA
While the IBD style provides clarity, remember that no visualization method guarantees trading success. Always combine with proper analysis and risk management.
If you found this indicator helpful, please consider leaving a comment or suggestion for future improvements. Happy trading!
Camarilla Pivot Plays█ OVERVIEW
This indicator implements the Camarilla Pivot Points levels and a system for suggesting particular plays. It only calculates and shows the 3rd, 4th, and 6th levels, as these are the only ones used by the system. In total, there are 12 possible plays, grouped into two groups of six. The algorithm constantly evaluates conditions for entering and exiting the plays and indicates them in real time, also triggering user-configurable alerts.
█ CREDITS
The Camarilla pivot plays are defined in a strategy developed by Thor Young, and the whole system is explained in his book "A Complete Day Trading System" . The indicator is published with his permission, and he is a user of it. The book is not necessary in order to understand and use the indicator; this description contains sufficient information to use it effectively.
█ FEATURES
Automatically draws plays, suggesting an entry, stop-loss, and maximum target
User can set alerts on chosen ticker to call these plays, even when not currently viewing them
Highly configurable via many options
Works for US/European stocks and US futures (at least)
Works correctly on both RTH and ETH charts
Automatically switches between RTH and ETH data
Optionally also shows the "other" set of pivots (RTH vs ETH data)
Configurable behaviour in the pre-market, not active in the post-market
Configurable sensitivity of the play detection algorithm
Can also show weekly and monthly Camarilla pivots
Well-documented options tooltips
Sensible defaults which are suitable for immediate use
Well-documented and high-quality open-source code for those who are interested
█ HOW TO USE
The defaults work well; at a minimum, just add the indicator and watch the plays being called. To avoid having to watch securities, by selecting the three dots next to the indicator name, you can set an alert on the indicator and choose to be alerted on play entry or exit events—or both. The following diagram shows several plays activated in the past (with the "Show past plays" option selected).
By default, the indicator draws plays 5 days back; this can be changed up to 20 days. The labels can be shifted left/right using the "label offset" option to avoid overlapping with other labels in this indicator or those of another indicator.
An information box at the top-right of the chart shows:
The data currently in use for the main pivots. This can switch in the pre-market if the H/L range exceeds the previous day's H/L, and if it does, you will see that switch at the time that it happens
Whether the current day's pivots are in a higher or lower range compared to the previous day's. This is based on the RTH close, so large moves in the post-market won't be reflected (there is an advanced option to change this)
The width of the value relationship in the current day compared to the previous day
The currently active play. If multiple plays are active in parallel, only the last activated one is shown
The resistance pivots are all drawn in the same colour (red by default), as are the support pivots (green by default). You can change the resistance and support colours, but it is not possible to have different colours for different levels of the same kind. Plays will always use the correct colour, drawing over the pivots. For example, R4 is red by default, but if a play treats R4 as a support, then the play will draw a green line (by default) over the red R4 line, thereby hiding it while the play is active.
There are a few advanced parameters; leave these as default unless you really know what they do. Please note the script is complicated—it does a lot. You might need to wait a few seconds while it (re)calculates on new tickers or when changing options. Give it time when first loading or changing options!
█ CONCEPTS
The indicator is focused around daily Camarilla pivots and implements 12 possible plays: 6 when in a higher range, 6 when in a lower range. The plays are labelled by two letters—the first indicates the range, the second indicates the play—as shown in this diagram:
The pivots can be calculated using only RTH (Regular Trading Hours) data, or ETH (Extended Trading Hours) data, which includes the pre-market and post-market. The indicator implements logic to automatically choose the correct data, based on the rules defined by the strategy. This is user-overridable. With the default options, ETH will be used when the H/L range in the previous day's post-market or current day's pre-market exceeds that of the previous day's regular market. In auto mode, the chosen pivots are considered the main pivots for that day and are the ones used for play evaluation. The "other" pivots can also be shown—"other" here meaning using ETH data when the main pivots use RTH data, and vice versa.
When displaying plays in the pre-market, since the RTH open is not yet known (and that value is needed to evaluate play pre-conditions), the pre-market open is used as a proxy for the RTH open. After the regular market opens, the correct RTH open is used to evaluate play conditions.
█ NOTE FOR FUTURES
Futures always use full ETH data in auto mode. Users may, however, wish to use the option "Always use RTH close," which uses the 3 p.m. Central Time (CME/Chicago) as a basis for the close in the pivot calculations (instead of the 4 p.m. actual close).
Futures don't officially have a pre-market or post-market like equities. Let's take ES on CME as an example (CME is in Chicago, so all times are Central Time, i.e., 1 hour behind Eastern Time). It trades from 17:00 Sunday to 16:00 Friday, with a daily pause between 16:00 and 17:00. However, most of the trading activity is done between 08:30 and 15:00 (Central), which you can tell from the volume spikes at those times, and this coincides with NYSE/NASDAQ regular hours (09:30–16:00 Eastern). So we define a pseudo-pre-market from 17:00 the previous day to 08:30 on the current day, then a pseudo-regular market from 08:30 to 15:00, then a pseudo-post-market from 15:00 to 16:00.
The indicator then works exactly the same as with equities—all the options behave the same, just with different session times defined for the pre-, regular, and post-market, with "RTH" meaning just the regular market and "ETH" meaning all three. The only difference from equities is that the auto calculation mode always uses ETH instead of switching based on ETH range compared to RTH range. This is so users who just leave all the defaults are not confused by auto-switching of the calculation mode; normally you'll want the pivots based on all the (ETH) data. However, both "Force RTH" and "Use RTH close with ETH data" work the same as with equities—so if, in the calculations, you really want to only use RTH data, or use all ETH H/L data but use the RTH close (at 15:00), you can.
█ LIMITATIONS
The pivots are very close to those shown in DAS Trader Pro. They are not to-the-cent exact, but within a few cents. The reasons are:
TradingView uses real-time data from CBOE One, so doesn't have access to full exchange data (unless you pay for it in TradingView), and
the close/high/low are taken from the intraday timeframe you are currently viewing, not daily data—which are very close, but often not exactly the same. For example, the high on the daily timeframe may differ slightly from the daily high you'll see on an intraday timeframe.
I have occasionally seen larger than a few cents differences in the pivots between these and DAS Trader Pro—this is always due to differences in data, for example a big spike in the data in TradingView but not in DAS Trader Pro, or vice versa. The more traded the stock is, the less the difference tends to be. Highly traded stocks are usually within a few cents. Less traded stocks may be more (for example, 30¢ difference in R4 is the highest I've seen). If it bothers you, official NYSE/NASDAQ data in TradingView is quite inexpensive (but even that doesn't make the 8am candle identical).
The 6th Camarilla level does not have a standard definition and may not match the level shown on other platforms. It does match the definition used by DAS Trader Pro.
The indicator is an intraday indicator (despite also being able to show weekly and monthly pivots on an intraday chart). It deactivates on a daily timeframe and higher. It is untested on sub-minute timeframes; you may encounter runtime errors on these due to various historical data referencing issues. Also, the play detection algorithm would likely be unpredictable on sub-minute timeframes. Therefore, sub-minute timeframes are formally unsupported.
The indicator was developed and tested for US/European stocks and US futures. It may or may not work as intended for stocks and futures in different locations. It does not work for other security types (e.g., crypto), where I have no evidence that the strategy has any relevance.
Adaptive ATR Limits█ OVERVIEW
This indicator plots adaptive ATR limits for intraday trading. A key feature of this indicator, which makes it different from other ATR limit indicators, is that the top and bottom ATR limit lines are always exactly one ATR apart from each other (in "auto" mode; there is also a "basic" mode, which plots the limits in the more traditional way—i.e., one ATR above the low and one ATR below the high at all times—and this can be used for comparison).
█ FEATURES
Provides an algorithm to plot the most reasonable intraday ATR top/bottom limits based on currently available information
Dynamically adapts limits as the price evolves during the day
Works correctly and consistently on both RTH and ETH charts
Has a user-selected ADR mode to base the limits on ADR instead of ATR
Option to include the current pre-market and previous day's post-market range in the calculation
Configurable ATR/ADR averaging length
Provides a visual smoothing option
Provides an information box showing the current numerical ATR/ADR values
Reasonable defaults that work well if the user changes nothing
Well-documented, high-quality, open-source code for those interested
█ HOW TO USE
At a minimum, there is nothing that needs to be set. The defaults work well. The ATR top line (red, configurable) gives you the most reasonable move given the currently available information. The line will move away from the price as the price approaches it; that is normal—it is reacting to new information. This happens until the ATR bottom limit hits the lower of the daily low and the previous day's close (in ATR mode). The ATR bottom line (green, configurable) works the same way, with reversed logic.
There is an option to use ADR instead of ATR. The ATR includes the previous day's RTH close in the range, whereas ADR does not. Another option allows the user to add the current day's pre-market range or the previous day's post-market into the current day's range, which has an effect if either of those went outside of today's RTH range, plus yesterday's RTH close (in the default ATR mode). Pre-market and post-market range is not typically included in the daily true range, so only change it if you really know you want it.
█ CONCEPTS
Most traditional ATR limit indicators plot the top ATR limit one ATR above the current daily low, and the bottom ATR limit one ATR below the current daily high. This indicator can also do that (in "basic" mode), but its value lies in its default "auto" mode, which uses an algorithm to dynamically adapt the ATR limits throughout the day, keeping them one ATR apart at all times. It tries to plot the most sensible ATR limits based on the current daily ATR, in order to provide a reasonable visual intraday target, given the available information at that point in time.
"Auto" mode is actually a weighted average of two methods: midpoint and relative (both of which can also be explicitly selected). The midpoint method places the midpoint of the ATR limit equal to the midpoint of the currently established daily range. The relative method measures the currently established daily range and calculates the position of the current price within it (as a ratio between 0 and 1). It then uses that value as a weight in a weighted average of extreme locations for the ATR limits, which are: the ATR top anchored to one ATR above the daily low, and the ATR bottom anchored to one ATR below the daily high.
The relative method is more advanced and better for most of the day; however, it can cause wild swings in the early market or pre-market before a reasonable range (as a percentage of ATR) has been established. "Auto" mode therefore takes another weighted average between the two methods, with the weight determined by the percentage of the ATR currently established within the day, more strongly weighting the calmer midpoint method before a good range is established. Once the full ATR has been achieved, the algorithm in "auto" mode will have fully switched to the relative method and will remain with that method for the rest of the day.
To explain the effect further, as an example, imagine that the price is approaching the full ATR range on the high side. At this point, the indicator will have almost fully transitioned to the second (relative) method. The lower ATR limit will now be anchored to the daily low as the price hits the upper ATR limit. If the price goes beyond the upper ATR, the lower ATR limit will stay anchored to the daily low, and the upper limit will stay anchored to one ATR above the lower limit. This allows you to see how far the price is going beyond the upper ATR limit. If the price then returns and backs off the upper ATR limit, the lower ATR limit will un-anchor from the daily low (it will actually rise, since the daily ATR range has been exceeded, so the lower ATR limit needs to come up because the actual daily range can’t fit into the ATR range anymore). The overall effect is to give you the best visual indication of where the price is in relation to a possible upper ATR-based target. Reverse this example for when the price low approaches the ATR range on the low side.
Care was taken so that the code uses no hard-coded time zones, exchanges, or session times. For this reason, it can in principle work globally. However, it very much depends on the information provided by the exchange, which is reflected in built-in Pine Script variables (see Limitations below).
█ LIMITATIONS
The indicator was developed for US/European equities and is tested on them only. It is also known to work on US futures; in this case, the whole 23-hour session is used, and the "Sessions to include in range" setting has no effect. It may or may not work as intended on security types and equities/futures for other countries.
Dskyz (DAFE) Adaptive Regime - Quant Machine ProDskyz (DAFE) Adaptive Regime - Quant Machine Pro:
Buckle up for the Dskyz (DAFE) Adaptive Regime - Quant Machine Pro, is a strategy that’s your ultimate edge for conquering futures markets like ES, MES, NQ, and MNQ. This isn’t just another script—it’s a quant-grade powerhouse, crafted with precision to adapt to market regimes, deliver multi-factor signals, and protect your capital with futures-tuned risk management. With its shimmering DAFE visuals, dual dashboards, and glowing watermark, it turns your charts into a cyberpunk command center, making trading as thrilling as it is profitable.
Unlike generic scripts clogging up the space, the Adaptive Regime is a DAFE original, built from the ground up to tackle the chaos of futures trading. It identifies market regimes (Trending, Range, Volatile, Quiet) using ADX, Bollinger Bands, and HTF indicators, then fires trades based on a weighted scoring system that blends candlestick patterns, RSI, MACD, and more. Add in dynamic stops, trailing exits, and a 5% drawdown circuit breaker, and you’ve got a system that’s as safe as it is aggressive. Whether you’re a newbie or a prop desk pro, this strat’s your ticket to outsmarting the markets. Let’s break down every detail and see why it’s a must-have.
Why Traders Need This Strategy
Futures markets are a gauntlet—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional traps that punish the unprepared. Meanwhile, platforms are flooded with low-effort scripts that recycle old ideas with zero innovation. The Adaptive Regime stands tall, offering:
Adaptive Intelligence: Detects market regimes (Trending, Range, Volatile, Quiet) to optimize signals, unlike one-size-fits-all scripts.
Multi-Factor Precision: Combines candlestick patterns, MA trends, RSI, MACD, volume, and HTF confirmation for high-probability trades.
Futures-Optimized Risk: Calculates position sizes based on $ risk (default: $300), with ATR or fixed stops/TPs tailored for ES/MES.
Bulletproof Safety: 5% daily drawdown circuit breaker and trailing stops keep your account intact, even in chaos.
DAFE Visual Mastery: Pulsing Bollinger Band fills, dynamic SL/TP lines, and dual dashboards (metrics + position) make signals crystal-clear and charts a work of art.
Original Craftsmanship: A DAFE creation, built with community passion, not a rehashed clone of generic code.
Traders need this because it’s a complete, adaptive system that blends quant smarts, user-friendly design, and DAFE flair. It’s your edge to trade with confidence, cut through market noise, and leave the copycats in the dust.
Strategy Components
1. Market Regime Detection
The strategy’s brain is its ability to classify market conditions into five regimes, ensuring signals match the environment.
How It Works:
Trending (Regime 1): ADX > 20, fast/slow EMA spread > 0.3x ATR, HTF RSI > 50 or MACD bullish (htf_trend_bull/bear).
Range (Regime 2): ADX < 25, price range < 3% of close, no HTF trend.
Volatile (Regime 3): BB width > 1.5x avg, ATR > 1.2x avg, HTF RSI overbought/oversold.
Quiet (Regime 4): BB width < 0.8x avg, ATR < 0.9x avg.
Other (Regime 5): Default for unclear conditions.
Indicators: ADX (14), BB width (20), ATR (14, 50-bar SMA), HTF RSI (14, daily default), HTF MACD (12,26,9).
Why It’s Brilliant:
Regime detection adapts signals to market context, boosting win rates in trending or volatile conditions.
HTF RSI/MACD add a big-picture filter, rare in basic scripts.
Visualized via gradient background (green for Trending, orange for Range, red for Volatile, gray for Quiet, navy for Other).
2. Multi-Factor Signal Scoring
Entries are driven by a weighted scoring system that combines candlestick patterns, trend, momentum, and volume for robust signals.
Candlestick Patterns:
Bullish: Engulfing (0.5), hammer (0.4 in Range, 0.2 else), morning star (0.2), piercing (0.2), double bottom (0.3 in Volatile, 0.15 else). Must be near support (low ≤ 1.01x 20-bar low) with volume spike (>1.5x 20-bar avg).
Bearish: Engulfing (0.5), shooting star (0.4 in Range, 0.2 else), evening star (0.2), dark cloud (0.2), double top (0.3 in Volatile, 0.15 else). Must be near resistance (high ≥ 0.99x 20-bar high) with volume spike.
Logic: Patterns are weighted higher in specific regimes (e.g., hammer in Range, double bottom in Volatile).
Additional Factors:
Trend: Fast EMA (20) > slow EMA (50) + 0.5x ATR (trend_bull, +0.2); opposite for trend_bear.
RSI: RSI (14) < 30 (rsi_bull, +0.15); > 70 (rsi_bear, +0.15).
MACD: MACD line > signal (12,26,9, macd_bull, +0.15); opposite for macd_bear.
Volume: ATR > 1.2x 50-bar avg (vol_expansion, +0.1).
HTF Confirmation: HTF RSI < 70 and MACD bullish (htf_bull_confirm, +0.2); RSI > 30 and MACD bearish (htf_bear_confirm, +0.2).
Scoring:
bull_score = sum of bullish factors; bear_score = sum of bearish. Entry requires score ≥ 1.0.
Example: Bullish engulfing (0.5) + trend_bull (0.2) + rsi_bull (0.15) + htf_bull_confirm (0.2) = 1.05, triggers long.
Why It’s Brilliant:
Multi-factor scoring ensures signals are confirmed by multiple market dynamics, reducing false positives.
Regime-specific weights make patterns more relevant (e.g., hammers shine in Range markets).
HTF confirmation aligns with the big picture, a quant edge over simplistic scripts.
3. Futures-Tuned Risk Management
The risk system is built for futures, calculating position sizes based on $ risk and offering flexible stops/TPs.
Position Sizing:
Logic: Risk per trade (default: $300) ÷ (stop distance in points * point value) = contracts, capped at max_contracts (default: 5). Point value = tick value (e.g., $12.5 for ES) * ticks per point (4) * contract multiplier (1 for ES, 0.1 for MES).
Example: $300 risk, 8-point stop, ES ($50/point) → 0.75 contracts, rounded to 1.
Impact: Precise sizing prevents over-leverage, critical for micro contracts like MES.
Stops and Take-Profits:
Fixed: Default stop = 8 points, TP = 16 points (2:1 reward/risk).
ATR-Based: Stop = 1.5x ATR (default), TP = 3x ATR, enabled via use_atr_for_stops.
Logic: Stops set at swing low/high ± stop distance; TPs at 2x stop distance from entry.
Impact: ATR stops adapt to volatility, while fixed stops suit stable markets.
Trailing Stops:
Logic: Activates at 50% of TP distance. Trails at close ± 1.5x ATR (atr_multiplier). Longs: max(trail_stop_long, close - ATR * 1.5); shorts: min(trail_stop_short, close + ATR * 1.5).
Impact: Locks in profits during trends, a game-changer in volatile sessions.
Circuit Breaker:
Logic: Pauses trading if daily drawdown > 5% (daily_drawdown = (max_equity - equity) / max_equity).
Impact: Protects capital during black swan events (e.g., April 27, 2025 ES slippage).
Why It’s Brilliant:
Futures-specific inputs (tick value, multiplier) make it plug-and-play for ES/MES.
Trailing stops and circuit breaker add pro-level safety, rare in off-the-shelf scripts.
Flexible stops (ATR or fixed) suit different trading styles.
4. Trade Entry and Exit Logic
Entries and exits are precise, driven by bull_score/bear_score and protected by drawdown checks.
Entry Conditions:
Long: bull_score ≥ 1.0, no position (position_size <= 0), drawdown < 5% (not pause_trading). Calculates contracts, sets stop at swing low - stop points, TP at 2x stop distance.
Short: bear_score ≥ 1.0, position_size >= 0, drawdown < 5%. Stop at swing high + stop points, TP at 2x stop distance.
Logic: Tracks entry_regime for PNL arrays. Closes opposite positions before entering.
Exit Conditions:
Stop-Loss/Take-Profit: Hits stop or TP (strategy.exit).
Trailing Stop: Activates at 50% TP, trails by ATR * 1.5.
Emergency Exit: Closes if price breaches stop (close < long_stop_price or close > short_stop_price).
Reset: Clears stop/TP prices when flat (position_size = 0).
Why It’s Brilliant:
Score-based entries ensure multi-factor confirmation, filtering out weak signals.
Trailing stops maximize profits in trends, unlike static exits in basic scripts.
Emergency exits add an extra safety layer, critical for futures volatility.
5. DAFE Visuals
The visuals are pure DAFE magic, blending function with cyberpunk flair to make signals intuitive and charts stunning.
Shimmering Bollinger Band Fill:
Display: BB basis (20, white), upper/lower (green/red, 45% transparent). Fill pulses (30–50 alpha) by regime, with glow (60–95 alpha) near bands (close ≥ 0.995x upper or ≤ 1.005x lower).
Purpose: Highlights volatility and key levels with a futuristic glow.
Visuals make complex regimes and signals instantly clear, even for newbies.
Pulsing effects and regime-specific colors add a DAFE signature, setting it apart from generic scripts.
BB glow emphasizes tradeable levels, enhancing decision-making.
Chart Background (Regime Heatmap):
Green — Trending Market: Strong, sustained price movement in one direction. The market is in a trend phase—momentum follows through.
Orange — Range-Bound: Market is consolidating or moving sideways, with no clear up/down trend. Great for mean reversion setups.
Red — Volatile Regime: High volatility, heightened risk, and larger/faster price swings—trade with caution.
Gray — Quiet/Low Volatility: Market is calm and inactive, with small moves—often poor conditions for most strategies.
Navy — Other/Neutral: Regime is uncertain or mixed; signals may be less reliable.
Bollinger Bands Glow (Dynamic Fill):
Neon Red Glow — Warning!: Price is near or breaking above the upper band; momentum is overstretched, watch for overbought conditions or reversals.
Bright Green Glow — Opportunity!: Price is near or breaking below the lower band; market could be oversold, prime for bounce or reversal.
Trend Green Fill — Trending Regime: Fills between bands with green when the market is trending, showing clear momentum.
Gold/Yellow Fill — Range Regime: Fills with gold/aqua in range conditions, showing the market is sideways/oscillating.
Magenta/Red Fill — Volatility Spike: Fills with vivid magenta/red during highly volatile regimes.
Blue Fill — Neutral/Quiet: A soft blue glow for other or uncertain market states.
Moving Averages:
Display: Blue fast EMA (20), red slow EMA (50), 2px.
Purpose: Shows trend direction, with trend_dir requiring ATR-scaled spread.
Dynamic SL/TP Lines:
Display: Pulsing colors (red SL, green TP for Trending; yellow/orange for Range, etc.), 3px, with pulse_alpha for shimmer.
Purpose: Tracks stops/TPs in real-time, color-coded by regime.
6. Dual Dashboards
Two dashboards deliver real-time insights, making the strat a quant command center.
Bottom-Left Metrics Dashboard (2x13):
Metrics: Mode (Active/Paused), trend (Bullish/Bearish/Neutral), ATR, ATR avg, volume spike (YES/NO), RSI (value + Oversold/Overbought/Neutral), HTF RSI, HTF trend, last signal (Buy/Sell/None), regime, bull score.
Display: Black (29% transparent), purple title, color-coded (green for bullish, red for bearish).
Purpose: Consolidates market context and signal strength.
Top-Right Position Dashboard (2x7):
Metrics: Regime, position side (Long/Short/None), position PNL ($), SL, TP, daily PNL ($).
Display: Black (29% transparent), purple title, color-coded (lime for Long, red for Short).
Purpose: Tracks live trades and profitability.
Why It’s Brilliant:
Dual dashboards cover market context and trade status, a rare feature.
Color-coding and concise metrics guide beginners (e.g., green “Buy” = go).
Real-time PNL and SL/TP visibility empower disciplined trading.
7. Performance Tracking
Logic: Arrays (regime_pnl_long/short, regime_win/loss_long/short) track PNL and win/loss by regime (1–5). Updated on trade close (barstate.isconfirmed).
Purpose: Prepares for future adaptive thresholds (e.g., adjust bull_score min based on regime performance).
Why It’s Brilliant: Lays the groundwork for self-optimizing logic, a quant edge over static scripts.
Key Features
Regime-Adaptive: Optimizes signals for Trending, Range, Volatile, Quiet markets.
Futures-Optimized: Precise sizing for ES/MES with tick-based risk inputs.
Multi-Factor Signals: Candlestick patterns, RSI, MACD, and HTF confirmation for robust entries.
Dynamic Exits: ATR/fixed stops, 2:1 TPs, and trailing stops maximize profits.
Safe and Smart: 5% drawdown breaker and emergency exits protect capital.
DAFE Visuals: Shimmering BB fill, pulsing SL/TP, and dual dashboards.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
How to Use
Add to Chart: Load on a 5min ES/MES chart in TradingView.
Configure Inputs: Set instrument (ES/MES), tick value ($12.5/$1.25), multiplier (1/0.1), risk ($300 default). Enable ATR stops for volatility.
Monitor Dashboards: Bottom-left for regime/signals, top-right for position/PNL.
Backtest: Run in strategy tester to compare regimes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see regime shifts and stops.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Backtest results may differ from live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Slippage: 3
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Adaptive Regime - Quant Machine Pro is more than a strategy—it’s a revolution. Crafted with DAFE’s signature precision, it rises above generic scripts with adaptive regimes, quant-grade signals, and visuals that make trading a thrill. Whether you’re scalping MES or swinging ES, this system empowers you to navigate markets with confidence and style. Join the DAFE crew, light up your charts, and let’s dominate the futures game!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
Dskyz (DAFE) Aurora Divergence – Quant Master Dskyz (DAFE) Aurora Divergence – Quant Master
Introducing the Dskyz (DAFE) Aurora Divergence – Quant Master , a strategy that’s your secret weapon for mastering futures markets like MNQ, NQ, MES, and ES. Born from the legendary Aurora Divergence indicator, this fully automated system transforms raw divergence signals into a quant-grade trading machine, blending precision, risk management, and cyberpunk DAFE visuals that make your charts glow like a neon skyline. Crafted with care and driven by community passion, this strategy stands out in a sea of generic scripts, offering traders a unique edge to outsmart institutional traps and navigate volatile markets.
The Aurora Divergence indicator was a cult favorite for spotting price-OBV divergences with its aqua and fuchsia orbs, but traders craved a system to act on those signals with discipline and automation. This strategy delivers, layering advanced filters (z-score, ATR, multi-timeframe, session), dynamic risk controls (kill switches, adaptive stops/TPs), and a real-time dashboard to turn insights into profits. Whether you’re a newbie dipping into futures or a pro hunting reversals, this strat’s got your back with a beginner guide, alerts, and visuals that make trading feel like a sci-fi mission. Let’s dive into every detail and see why this original DAFE creation is a must-have.
Why Traders Need This Strategy
Futures markets are a battlefield—fast-paced, volatile, and riddled with institutional games that can wipe out undisciplined traders. From the April 28, 2025 NQ 1k-point drop to sneaky ES slippage, the stakes are high. Meanwhile, platforms are flooded with unoriginal, low-effort scripts that promise the moon but deliver noise. The Aurora Divergence – Quant Master rises above, offering:
Unmatched Originality: A bespoke system built from the ground up, with custom divergence logic, DAFE visuals, and quant filters that set it apart from copycat clutter.
Automation with Precision: Executes trades on divergence signals, eliminating emotional slip-ups and ensuring consistency, even in chaotic sessions.
Quant-Grade Filters: Z-score, ATR, multi-timeframe, and session checks filter out noise, targeting high-probability reversals.
Robust Risk Management: Daily loss and rolling drawdown kill switches, plus ATR-based stops/TPs, protect your capital like a fortress.
Stunning DAFE Visuals: Aqua/fuchsia orbs, aurora bands, and a glowing dashboard make signals intuitive and charts a work of art.
Community-Driven: Evolved from trader feedback, this strat’s a labor of love, not a recycled knockoff.
Traders need this because it’s a complete, original system that blends accessibility, sophistication, and style. It’s your edge to trade smarter, not harder, in a market full of traps and imitators.
1. Divergence Detection (Core Signal Logic)
The strategy’s core is its ability to detect bullish and bearish divergences between price and On-Balance Volume (OBV), pinpointing reversals with surgical accuracy.
How It Works:
Price Slope: Uses linear regression over a lookback (default: 9 bars) to measure price momentum (priceSlope).
OBV Slope: OBV tracks volume flow (+volume if price rises, -volume if falls), with its slope calculated similarly (obvSlope).
Bullish Divergence: Price slope negative (falling), OBV slope positive (rising), and price above 50-bar SMA (trend_ma).
Bearish Divergence: Price slope positive (rising), OBV slope negative (falling), and price below 50-bar SMA.
Smoothing: Requires two consecutive divergence bars (bullDiv2, bearDiv2) to confirm signals, reducing false positives.
Strength: Divergence intensity (divStrength = |priceSlope * obvSlope| * sensitivity) is normalized (0–1, divStrengthNorm) for visuals.
Why It’s Brilliant:
- Divergences catch hidden momentum shifts, often exploited by institutions, giving you an edge on reversals.
- The 50-bar SMA filter aligns signals with the broader trend, avoiding choppy markets.
- Adjustable lookback (min: 3) and sensitivity (default: 1.0) let you tune for different instruments or timeframes.
2. Filters for Precision
Four advanced filters ensure signals are high-probability and market-aligned, cutting through the noise of volatile futures.
Z-Score Filter:
Logic: Calculates z-score ((close - SMA) / stdev) over a lookback (default: 50 bars). Blocks entries if |z-score| > threshold (default: 1.5) unless disabled (useZFilter = false).
Impact: Avoids trades during extreme price moves (e.g., blow-off tops), keeping you in statistically safe zones.
ATR Percentile Volatility Filter:
Logic: Tracks 14-bar ATR in a 100-bar window (default). Requires current ATR > 80th percentile (percATR) to trade (tradeOk).
Impact: Ensures sufficient volatility for meaningful moves, filtering out low-volume chop.
Multi-Timeframe (HTF) Trend Filter:
Logic: Uses a 50-bar SMA on a higher timeframe (default: 60min). Longs require price > HTF MA (bullTrendOK), shorts < HTF MA (bearTrendOK).
Impact: Aligns trades with the bigger trend, reducing counter-trend losses.
US Session Filter:
Logic: Restricts trading to 9:30am–4:00pm ET (default: enabled, useSession = true) using America/New_York timezone.
Impact: Focuses on high-liquidity hours, avoiding overnight spreads and erratic moves.
Evolution:
- These filters create a robust signal pipeline, ensuring trades are timed for optimal conditions.
- Customizable inputs (e.g., zThreshold, atrPercentile) let traders adapt to their style without compromising quality.
3. Risk Management
The strategy’s risk controls are a masterclass in balancing aggression and safety, protecting capital in volatile markets.
Daily Loss Kill Switch:
Logic: Tracks daily loss (dayStartEquity - strategy.equity). Halts trading if loss ≥ $300 (default) and enabled (killSwitch = true, killSwitchActive).
Impact: Caps daily downside, crucial during events like April 27, 2025 ES slippage.
Rolling Drawdown Kill Switch:
Logic: Monitors drawdown (rollingPeak - strategy.equity) over 100 bars (default). Stops trading if > $1000 (rollingKill).
Impact: Prevents prolonged losing streaks, preserving capital for better setups.
Dynamic Stop-Loss and Take-Profit:
Logic: Stops = entry ± ATR * multiplier (default: 1.0x, stopDist). TPs = entry ± ATR * 1.5x (profitDist). Longs: stop below, TP above; shorts: vice versa.
Impact: Adapts to volatility, keeping stops tight but realistic, with TPs targeting 1.5:1 reward/risk.
Max Bars in Trade:
Logic: Closes trades after 8 bars (default) if not already exited.
Impact: Frees capital from stagnant trades, maintaining efficiency.
Kill Switch Buffer Dashboard:
Logic: Shows smallest buffer ($300 - daily loss or $1000 - rolling DD). Displays 0 (red) if kill switch active, else buffer (green).
Impact: Real-time risk visibility, letting traders adjust dynamically.
Why It’s Brilliant:
- Kill switches and ATR-based exits create a safety net, rare in generic scripts.
- Customizable risk inputs (maxDailyLoss, dynamicStopMult) suit different account sizes.
- Buffer metric empowers disciplined trading, a DAFE signature.
4. Trade Entry and Exit Logic
The entry/exit rules are precise, filtered, and adaptive, ensuring trades are deliberate and profitable.
Entry Conditions:
Long Entry: bullDiv2, cooldown passed (canSignal), ATR filter passed (tradeOk), in US session (inSession), no kill switches (not killSwitchActive, not rollingKill), z-score OK (zOk), HTF trend bullish (bullTrendOK), no existing long (lastDirection != 1, position_size <= 0). Closes shorts first.
Short Entry: Same, but for bearDiv2, bearTrendOK, no long (lastDirection != -1, position_size >= 0). Closes longs first.
Adaptive Cooldown: Default 2 bars (cooldownBars). Doubles (up to 10) after a losing trade, resets after wins (dynamicCooldown).
Exit Conditions:
Stop-Loss/Take-Profit: Set per trade (ATR-based). Exits on stop/TP hits.
Other Exits: Closes if maxBarsInTrade reached, ATR filter fails, or kill switch activates.
Position Management: Ensures no conflicting positions, closing opposites before new entries.
Built To Be Reliable and Consistent:
- Multi-filtered entries minimize false signals, a stark contrast to basic scripts.
- Adaptive cooldown prevents overtrading, especially after losses.
- Clean position handling ensures smooth execution, even in fast markets.
5. DAFE Visuals
The visuals are a DAFE hallmark, blending function with clean flair to make signals intuitive and charts stunning.
Aurora Bands:
Display: Bands around price during divergences (bullish: below low, bearish: above high), sized by ATR * bandwidth (default: 0.5).
Colors: Aqua (bullish), fuchsia (bearish), with transparency tied to divStrengthNorm.
Purpose: Highlights divergence zones with a glowing, futuristic vibe.
Divergence Orbs:
Display: Large/small circles (aqua below for bullish, fuchsia above for bearish) when bullDiv2/bearDiv2 and canSignal. Labels show strength (0–1).
Purpose: Pinpoints entries with eye-catching clarity.
Gradient Background:
Display: Green (bullish), red (bearish), or gray (neutral), 90–95% transparent.
Purpose: Sets the market mood without clutter.
Strategy Plots:
- Stop/TP Lines: Red (stops), green (TPs) for active trades.
- HTF MA: Yellow line for trend context.
- Z-Score: Blue step-line (if enabled).
- Kill Switch Warning: Red background flash when active.
What Makes This Next-Level?:
- Visuals make complex signals (divergences, filters) instantly clear, even for beginners.
- DAFE’s unique aesthetic (orbs, bands) sets it apart from generic scripts, reinforcing originality.
- Functional plots (stops, TPs) enhance trade management.
6. Metrics Dashboard
The top-right dashboard (2x8 table) is your command center, delivering real-time insights.
Metrics:
Daily Loss ($): Current loss vs. day’s start, red if > $300.
Rolling DD ($): Drawdown vs. 100-bar peak, red if > $1000.
ATR Threshold: Current percATR, green if ATR exceeds, red if not.
Z-Score: Current value, green if within threshold, red if not.
Signal: “Bullish Div” (aqua), “Bearish Div” (fuchsia), or “None” (gray).
Action: “Consider Buying”/“Consider Selling” (signal color) or “Wait” (gray).
Kill Switch Buffer ($): Smallest buffer to kill switch, green if > 0, red if 0.
Why This Is Important?:
- Consolidates critical data, making decisions effortless.
- Color-coded metrics guide beginners (e.g., green action = go).
- Buffer metric adds transparency, rare in off-the-shelf scripts.
7. Beginner Guide
Beginner Guide: Middle-right table (shown once on chart load), explains aqua orbs (bullish, buy) and fuchsia orbs (bearish, sell).
Key Features:
Futures-Optimized: Tailored for MNQ, NQ, MES, ES with point-value adjustments.
Highly Customizable: Inputs for lookback, sensitivity, filters, and risk settings.
Real-Time Insights: Dashboard and visuals update every bar.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
User-Friendly: Guide, visuals, and dashboard make it accessible yet powerful.
Original Design: DAFE’s unique logic and visuals stand out from generic scripts.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Configure Inputs: Adjust instrument, filters, or risk (defaults optimized for MNQ).
Monitor Dashboard: Watch signals, actions, and risk metrics (top-right).
Backtest: Run in strategy tester to evaluate performance.
Live Trade: Connect to a broker (e.g., Tradovate) for automation. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Use bar replay (e.g., April 28, 2025 NQ drop) to test volatility handling.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Backtest results may not reflect live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Aurora Divergence – Quant Master isn’t just a strategy—it’s a movement. Crafted with originality and driven by community passion, it rises above the flood of generic scripts to deliver a system that’s as powerful as it is beautiful. With its quant-grade logic, DAFE visuals, and robust risk controls, it empowers traders to tackle futures with confidence and style. Join the DAFE crew, light up your charts, and let’s outsmart the markets together!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Smart Breakout with ATR Stop-LossThe Smart Breakout indicator combines a classic 20-day Donchian channel breakout with a tight trailing stop, drawing green lines and “ENTRY” labels at the bar after a valid breakout, and red lines and “EXIT” label at the bar after a stop-loss breach.
By default it uses the chart’s timeframe to compute ATR and stops, but you can flip on Daily lock to freeze both ATR and price reads at the daily resolution—so your stops stay the same whether you view at 1s, 15 m, 4h or lower frequency bars.
Key features:
20-day Donchian breakout: entry when price closes above the highest high of the previous 20 bars
2 × ATR(14) trailing stop: initialized at entry and raised only when the new (close – 2 × ATR) exceeds the prior stop
Daily lock option: Ensures all ATR and close values are calculated on the daily timeframe, keeping stop levels consistent across resolutions
Sharpe & Sortino Ratio PROSharpe & Sortino Ratio PRO offers an advanced and more precise way to calculate and visualize the Sharpe and Sortino Ratios for financial assets on TradingView. Its main goal is to provide a scientifically accurate method for assessing the risk-adjusted performance of assets, both in the short and long term. Unlike TradingView’s built-in metrics, this script correctly handles periodic returns, uses optional logarithmic returns, properly annualizes both returns and volatility, and adjusts for the risk-free rate — all critical factors for truly meaningful Sharpe and Sortino calculations.
Users can customize the rolling analysis window (e.g., 252 periods for one year on daily data) and the long-term smoothing period (e.g., 1260 periods for five years). There’s also an option to select between linear and logarithmic returns and to manually input a risk-free rate if real-time data from FRED (the 3-Month T-Bill Rate via FRED:DGS3MO) is unavailable. Based on the chart’s timeframe (daily, weekly, or monthly), the script automatically adjusts the risk-free rate to a per-period basis.
The Sharpe Ratio is calculated by first determining the asset’s excess returns (returns after subtracting the risk-free return per period), then computing the average and standard deviation of those excess returns over the specified window, and finally annualizing these figures separately — in line with best scientific practices (Sharpe, 1994). The Sortino Ratio follows a similar approach but only considers negative returns, focusing specifically on downside risk (Sortino & Van der Meer, 1991).
To enhance readability, the script visualizes the ratios using a color gradient: strong negative values are shown in red, neutral values in yellow, and strong positive values in green. Additionally, the long-term averages for both Sharpe and Sortino are plotted with steady colors (teal and orange, respectively), making it easier to spot enduring performance trends.
Why calculating Sharpe and Sortino Ratios manually on TradingView is necessary?
While TradingView provides basic Sharpe and Sortino Ratios, they come with significant methodological flaws that can lead to misleading conclusions about an asset’s true risk-adjusted performance.
First, TradingView often computes volatility based on the standard deviation of price levels rather than returns (TradingView, 2023). This method is problematic because it causes the volatility measure to be directly dependent on the asset’s absolute price. For instance, a stock priced at $1,000 will naturally show larger absolute daily price moves than a $10 stock, even if their percentage changes are similar. This artificially inflates the measured standard deviation and, as a result, depresses the calculated Sharpe Ratio.
Second, TradingView frequently neglects to adjust for the risk-free rate. By treating all returns as risky returns, the computed Sharpe Ratio may significantly underestimate risk-adjusted performance, especially when interest rates are high (Sharpe, 1994).
Third, and perhaps most critically, TradingView doesn’t properly annualize the mean excess return and the standard deviation separately. In correct financial math, the mean excess return should be multiplied by the number of periods per year, while the standard deviation should be multiplied by the square root of the number of periods per year (Cont, 2001; Fabozzi et al., 2007). Incorrect annualization skews the Sharpe and Sortino Ratios and can lead to under- or overestimating investment risk.
These flaws lead to three major issues:
• Overstated volatility for high-priced assets.
• Incorrect scaling between returns and risk.
• Sharpe Ratios that are systematically biased downward, especially in high-price or high-interest environments.
How to properly calculate Sharpe and Sortino Ratios in Pine Script?
To get accurate results, the Sharpe and Sortino Ratios must be calculated using the correct methodology:
1. Use returns, not price levels, to calculate volatility. Ideally, use logarithmic returns for better mathematical properties like time additivity (Cont, 2001).
2. Adjust returns by subtracting the risk-free rate on a per-period basis to obtain true excess returns.
3. Annualize separately:
• Multiply the mean excess return by the number of periods per year (e.g., 252 for daily data).
• Multiply the standard deviation by the square root of the number of periods per year.
4. Finally, divide the annualized mean excess return by the annualized standard deviation to calculate the Sharpe Ratio.
The Sortino Ratio follows the same structure but uses downside deviations instead of standard deviations.
By following this scientifically sound method, you ensure that your Sharpe and Sortino Ratios truly reflect the asset’s real-world risk and return characteristics.
References
• Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance, 1(2), pp. 223–236.
• Fabozzi, F.J., Gupta, F. and Markowitz, H.M. (2007). The Legacy of Modern Portfolio Theory. Journal of Investing, 16(3), pp. 7–22.
• Sharpe, W.F. (1994). The Sharpe Ratio. Journal of Portfolio Management, 21(1), pp. 49–58.
• Sortino, F.A. and Van der Meer, R. (1991). Downside Risk: Capturing What’s at Stake in Investment Situations. Journal of Portfolio Management, 17(4), pp. 27–31.
• TradingView (2023). Help Center - Understanding Sharpe and Sortino Ratios. Available at: www.tradingview.com (Accessed: 25 April 2025).
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
[Stop!Loss] ADR Signal ADR Signal - a technical indicator located in a separate window, which displays by default the 80%-level , as well as the 100%-level of the average daily range (ADR) for the last 10 days and compares it with the current intraday range. The indicator helps not only with the use of a mathematical-statistical method to identify a potential reversal at the moment during intraday trading, but can also serves as an effective assistant in risk management.
👉 Basic mechanics of the indicator
Firstly, this indicator tracks the performance of the standard ATR indicator on the daily chart, in other words, ADR (Average Daily Range).
Important ❗️The ATR (Average True Range) indicator was created by J. Welles Wilder Jr. He first introduced ATR in his book "New Concepts in Technical Trading Systems", published in 1978. Wilder developed this indicator to measure market volatility to help traders estimate the range of price movements. This indicator is built into TradingView, more details can be found by link: www.tradingview.com
Like ATR , ADR calculates the average true range for a specified period. In this case, the distance in points from the maximum of each day to its minimum is calculated, after which the arithmetic mean is calculated - this is ADR .
👉 Visualization
ADR Signal is located in a separate window on the chart and has 3 levels:
1) "ADR level" (green line) - the same parameter, the calculations of which are briefly described above. There is 100%-level of ATR on the daily chart (ADR).
2) "Current level" (red line) - this is the current price passage within the day, calculated in points. At the start of a new day, this parameter is reset. Therefore, in the indicator window, this line has sharp drops at the start of a new trading day: "A new trading day - the instrument's power reserve is renewed again".
3) "Signal level" (blue line) - this is an individually customized value that demonstrates a certain part of the ADR parameter.
👉 Inputs
1) - is responsible for the ATR indicator period, the value of which will always be calculated on the daily chart. The default value is "10", that is, ATR is calculated for the last 10 days (not including the current one).
2) - signal level (in %). The default value is "0.8", that is, 80%-level of the ADR parameter (set earlier) is calculated.
👉 Style
1) - by default, this level is colored "blue".
2) - by default, this level is colored "red".
3) - by default, this level is colored "green".
👉 How to use this indicator
Important❗️ The two methods of the use of the ADR Signal indicator described below will be most effective when trading intraday (which is highlighted quite well below), so it is more logical to use the indicator information on time periods H1 and below.
1) Identifying potential reversals during intraday trading:
The ADR Signal indicator can be used as a potential individual reversal strategy.
Important ❗️It should be noted that using it in it without additional confirming analysis tools will be a rather aggressive trading approach. Therefore, it is best to support the entry point in particular with other methods.
In this case, the crossing of the red line (the number of points passed within the current day, that is, from the minimum of the current day to its maximum) and the blue line (color of the Signal level based on the default settings), indicates that the trading instrument has passed 80% (based on the default settings for the "Signal level") of its average distance from the maximum to the minimum over the past 10 days (based on the default settings for the "ADR Length"). Such a situation in the context of the mathematical-statistical approach indicates a probable reversal, since the "power reserve" of this instrument is mostly exhausted, so one can expect with a higher probability, at least, a price stop and possibly a reversal. In case of crossing of the red line and the green one (ADR level), it says again that based on the mathematical-statistical approach, this trading instrument has completely exhausted its intraday "power reserve". In this situation, a stop or reversal of the price will be even more likely.
Of course, using the "Signal level" parameter, one can filter out even more reliable situations for potential price reversals within a day, namely, by specifying, for example, 1.5 in the field of this parameter. Under such conditions, in the case of crossing the red and blue lines (based on the default style settings), to say that the trading instrument has passed 150% of its average distance over the last 10 days (based on the default style settings "ADR length"). In this case, the probability of a stop or reversal of the price increases even more.
2) Use in risk management:
In terms of risk management, this indicator is more applicable to open trades. For example, if one had an open Buy-position (especially if it is an intraday trade) and the price has raised significantly during the day, then the crossing of the red line with the blue line , and especially the red line with the green line , may indicate that the price will most likely stop growing, since the "power reserve" is almost or completely exhausted for this instrument within the current day. In this case, one can, at a minimum, move the trade to breakeven or even partially fix the profit.
We will continue to discuss the methods of using this indicator and strategies based on it here. And we are always waiting for your reactions and feedback on this topic 💬.
Thank you for your support 🚀
Horizontal Price TableOverview:
This script displays a dynamic price table on your chart, showing real-time prices and daily percentage changes for up to 7 user-defined tickers. You can customize both which tickers are shown and how many are visible, all through the settings panel.
How it works (Step-by-Step):
User-Defined Tickers:
The script provides input fields for up to 7 tickers using input.symbol(). You can track stocks, indexes, ETFs, crypto, or futures — anything supported by TradingView.
Choose How Many to Display:
An additional dropdown lets you choose how many of the 7 tickers to actually display (between 1 and 7). This gives you control over screen space and focus.
Market Data Fetching:
For each displayed ticker, the script fetches:
The current day’s closing price (close)
The previous day’s closing price (close )
This data is pulled using request.security() on the daily timeframe (1D).
% Change Calculation:
The script calculates the daily percentage change using:
(Current Price−Previous Close)/Previous Close×100(Current Price−Previous Close)/Previous Close×100
Cleaned Ticker Names:
Ticker symbols often include an exchange prefix like NASDAQ:AAPL. The script automatically removes anything before the colon (:), so only the clean symbol (e.g., AAPL) is shown in the table.
Table Display:
A visual table appears at the top-center of your chart, showing:
Row 1: Ticker symbol (cleaned)
Row 2: Current price (rounded to 2 decimals)
Row 3: Daily % change (green for gains, red for losses)
Customization:
You can choose the background color of the table.
Ticker names appear in white text with a gray background.
% change is color-coded: green for positive, red for negative.
Why Use This Script?
Track multiple tickers at once without leaving your chart.
Clean, customizable layout.
Useful for monitoring watchlists, portfolios, or related markets.
Tips:
Combine this with your favorite indicators for a personalized dashboard.
Works great on any chart or timeframe.
Ensure the tickers entered are valid on TradingView (e.g., SPY, BTCUSD, NQ1!, etc.).
Prop Firm Business SimulatorThe prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms.
Now what is a modern day CFD Prop Firm?
These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out.
I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change.
Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations.
Now why is this tool helpful?
Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal.
While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in.
I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using.
How to use this tool
It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that.
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
//--$$$$$--Strategy-- --$$$$$$--// ******************************************************************************************************************************
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
length = input.int(20, minval=1, group="Keltner Channel Breakout")
mult = input(2.0, "Multiplier", group="Keltner Channel Breakout")
src = input(close, title="Source", group="Keltner Channel Breakout")
exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout")
BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout")
atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout")
esma(source, length)=>
s = ta.sma(source, length)
e = ta.ema(source, length)
exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
//--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
u = plot(upper, color=#2962FF, title="Upper", force_overlay=true)
plot(ma, color=#2962FF, title="Basis", force_overlay=true)
l = plot(lower, color=#2962FF, title="Lower", force_overlay=true)
fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background")
//--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout")
le = high>upper ? false : true
se = lowlower
strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots)
if se and upper>lower
strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots)
The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge.
If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains.
If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains.
These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income.
The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate.
The daily drawdown limit get's reset every time there is a new dayofweek on chart.
If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K.
The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade.
Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication:
That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.
Aurora Flow Oscillator [QuantAlgo]The Aurora Flow Oscillator is an advanced momentum-based technical indicator designed to identify market direction, momentum shifts, and potential reversal zones using adaptive filtering techniques. It visualizes price momentum through a dynamic oscillator that quantifies trend strength and direction, helping traders and investors recognize momentum shifts and trading opportunities across various timeframes and asset class.
🟢 Technical Foundation
The Aurora Flow Oscillator employs a sophisticated mathematical approach with adaptive momentum filtering to analyze market conditions, including:
Price-Based Momentum Calculation: Calculates logarithmic price changes to measure the rate and magnitude of market movement
Adaptive Momentum Filtering: Applies an advanced filtering algorithm to smooth momentum calculations while preserving important signals
Acceleration Analysis: Incorporates momentum acceleration to identify shifts in market direction before they become obvious
Signal Normalization: Automatically scales the oscillator output to a range between -100 and 100 for consistent interpretation across different market conditions
The indicator processes price data through multiple filtering stages, applying mathematical principles including exponential smoothing with adaptive coefficients. This creates an oscillator that dynamically adjusts to market volatility while maintaining responsiveness to genuine trend changes.
🟢 Key Features & Signals
1. Momentum Flow and Extreme Zone Identification
The oscillator presents market momentum through an intuitive visual display that clearly indicates both direction and strength:
Above Zero: Indicates positive momentum and potential bullish conditions
Below Zero: Indicates negative momentum and potential bearish conditions
Slope Direction: The angle and direction of the oscillator provide immediate insight into momentum strength
Zero Line Crossings: Signal potential trend changes and new directional momentum
The indicator also identifies potential overbought and oversold market conditions through extreme zone markings:
Upper Zone (>50): Indicates strong bullish momentum that may be approaching exhaustion
Lower Zone (<-50): Indicates strong bearish momentum that may be approaching exhaustion
Extreme Boundaries (±95): Mark potentially unsustainable momentum levels where reversals become increasingly likely
These zones are displayed with gradient intensity that increases as the oscillator moves toward extremes, helping traders and investors:
→ Identify potential reversal zones
→ Determine appropriate entry and exit points
→ Gauge overall market sentiment strength
2. Customizable Trading Style Presets
The Aurora Flow Oscillator offers pre-configured settings for different trading approaches:
Default (80,150): Balanced configuration suitable for most trading and investing situations.
Scalping (5,80): Highly responsive settings for ultra-short-term trades. Generates frequent signals and catches quick price movements. Best for 1-15min charts when making many trades per day.
Day Trading (8,120): Optimized for intraday movements with faster response than default settings while maintaining reasonable signal quality. Ideal for 5-60min or 4h-12h timeframes.
Swing Trading (10,200): Designed for multi-day positions with stronger noise filtering. Focuses on capturing larger price swings while avoiding minor fluctuations. Works best on 1-4h and daily charts.
Position Trading (14,250): For longer-term position traders/investors seeking significant market trends. Reduces false signals by heavily filtering market noise. Ideal for daily or even weekly charts.
Trend Following (16,300): Maximum smoothing that prioritizes established directional movements over short-term fluctuations. Best used on daily and weekly charts, but can also be used for lower timeframe trading.
Countertrend (7,100): Tuned to detect potential reversals and exhaustion points in trends. More sensitive to momentum shifts than other presets. Effective on 15min-4h charts, as well as daily and weekly charts.
Each preset automatically adjusts internal parameters for optimal performance in the selected trading context, providing flexibility across different market approaches without requiring complex manual configuration.
🟢 Practical Usage Tips
1/ Trend Analysis and Interpretation
→ Direction Assessment: Evaluate the oscillator's position relative to zero to determine underlying momentum bias
→ Momentum Strength: Measure the oscillator's distance from zero within the -100 to +100 range to quantify momentum magnitude
→ Trend Consistency: Monitor the oscillator's path for sustained directional movement without frequent zero-line crossings
→ Reversal Detection: Watch for oscillator divergence from price and deceleration of movement when approaching extreme zones
2/ Signal Generation Strategies
Depending on your trading approach, multiple signal strategies can be employed:
Trend Following Signals:
Enter long positions when the oscillator crosses above zero
Enter short positions when the oscillator crosses below zero
Add to positions on pullbacks while maintaining the overall trend direction
Countertrend Signals:
Look for potential reversals when the oscillator reaches extreme zones (±95)
Enter contrary positions when momentum shows signs of exhaustion
Use oscillator divergence with price as additional confirmation
Momentum Shift Signals:
Enter positions when oscillator changes direction after establishing a trend
Exit positions when oscillator direction reverses against your position
Scale position size based on oscillator strength percentage
3/ Timeframe Optimization
The indicator can be effectively applied across different timeframes with these considerations:
Lower Timeframes (1-15min):
Use Scalping or Day Trading presets
Focus on quick momentum shifts and zero-line crossings
Be cautious of noise in extreme market conditions
Medium Timeframes (30min-4h):
Use Default or Swing Trading presets
Look for established trends and potential reversal zones
Combine with support/resistance analysis for entry/exit precision
Higher Timeframes (Daily+):
Use Position Trading or Trend Following presets
Focus on major trend identification and long-term positioning
Use extreme zones for position management rather than immediate reversals
🟢 Pro Tips
Price Momentum Period:
→ Lower values (5-7) increase sensitivity to minor price fluctuations but capture more market noise
→ Higher values (10-16) emphasize sustained momentum shifts at the cost of delayed response
→ Adjust based on your timeframe (lower for shorter timeframes, higher for longer timeframes)
Oscillator Filter Period:
→ Lower values (80-120) produce more frequent directional changes and earlier response to momentum shifts
→ Higher values (200-300) filter out shorter-term fluctuations to highlight dominant market cycles
→ Match to your typical holding period (shorter holding time = lower filter values)
Multi-Timeframe Analysis:
→ Compare oscillator readings across different timeframes for confluence
→ Look for alignment between higher and lower timeframe signals
→ Use higher timeframe for trend direction, lower for earlier entries
Volatility-Adaptive Trading:
→ Use oscillator strength to adjust position sizing (stronger = larger)
→ Consider reducing exposure when oscillator reaches extreme zones
→ Implement tighter stops during periods of oscillator acceleration
Combination Strategies:
→ Pair with volume indicators for confirmation of momentum shifts
→ Use with support/resistance levels for strategic entry and exit points
→ Combine with volatility indicators for comprehensive market context
VolumePrice Intensity AnalyzerVolumePrice Intensity Analyzer
The VolumePrice Intensity Analyzer is a Pine Script v6 indicator designed to measure market activity intensity through the trading value (Price * Volume, scaled to millions). It helps traders identify significant volume-price interactions, track trends, and gauge momentum by combining volume analysis with trend-following tools.
Features:
Volume-Based Analysis: Calculates Price * Volume in millions to highlight market activity levels.
Trend Identification: Plots 20-day and 50-day SMAs of the trading value to smooth fluctuations and reveal sustained trends.
Relative Strength: Displays the ratio of daily Price * Volume to the long-term SMA in a separate pane, helping traders assess activity intensity relative to historical averages.
Real-Time Metrics: A table shows the current Price * Volume and its ratio to the long SMA, updated continuously with bold text formatting (v6 feature).
Alerts: Triggers notifications for high trading values (when Price * Volume exceeds 1.5x the long SMA) and SMA crossovers (short SMA crossing above long SMA).
Visual Cues: Uses dynamic bar colors (teal for bullish, gray for bearish) and background highlights to mark significant market activity.
Customizable Inputs: Adjust SMA periods, scaling factor, and alert threshold via the settings panel, with tooltips for clarity (v6 feature).
Originality:
Unlike basic volume indicators, this tool combines Price * Volume with trend analysis (SMAs), relative strength (ratio plot), and actionable alerts. The real-time table and visual highlights provide a unique, at-a-glance view of market intensity, making it a valuable addition for volume and trend-focused traders.
Calculations:
Trading Value (P*V): (Close * Volume) * Scale Factor (default scale factor of 1e-6 converts to millions).
SMAs: 20-day and 50-day Simple Moving Averages of the trading value to identify short- and long-term trends.
Ratio: Daily Price * Volume divided by the 50-day SMA, plotted in a separate pane to show relative activity strength.
Bar Colors: Teal (RGB: 0, 132, 141) for bullish bars (close > open or close > previous close), gray for bearish or neutral bars.
Background Highlight: Light yellow (hex: #ffcb3b, 81% transparency) when Price * Volume exceeds the long SMA by the alert threshold.
Plotted Elements:
Short SMA P*V (M): Red line, 20-day SMA of Price*Volume in millions.
Long SMA P*V (M): Blue line, 50-day SMA of Price*Volume in millions.
Today P*V (M): Columns, daily Price*Volume in millions (teal/gray based on price action).
Daily V*P/Longer Term Average: Purple line in a separate pane, ratio of daily Price * Volume to the 50-day SMA.
Usage:
Spot High Activity: Look for Price * Volume columns exceeding the SMAs or spikes in the ratio plot to identify significant market moves.
Confirm Trends: Use SMA crossovers (e.g., short SMA crossing above long SMA) as bullish trend signals, or vice versa for bearish trends.
Monitor Intensity: The table provides real-time Price * Volume and ratio values, while background highlights signal high activity periods.
Versatility: Suitable for stocks, forex, crypto, or any market with volume data, across various timeframes.
How to Use:
Add the indicator to your chart.
Adjust inputs (SMA periods, scale factor, alert threshold) via the settings panel to match your trading style.
Watch for alerts, check the table for real-time metrics, and observe the ratio plot for relative strength signals.
Use the background highlights and bar colors to quickly spot significant market activity and price action.
This indicator leverages Pine Script v6 features like lazy evaluation for performance and advanced text formatting for better visuals, making it a powerful tool for traders focusing on volume, trends, and momentum.
GranDoc - Week, Day, Month, and Session Separator5Indicator Name: GranDoc's - Week, Day, Month, and Session Separator
Version: Pine Script v5
Author: Jonpaul Nnamdi Opara (GranDoc )
Description
The "GranDoc - Week, Day, Month, and Session Separator" is a highly customizable TradingView indicator designed to enhance chart analysis by visually marking critical time-based transitions. Developed by Jonpaul Nnamdi Opara, this tool plots vertical lines with labels or background highlights to denote the start and end of weeks, days, months, and major trading sessions (Frankfurt, London, NY Morning, NY Afternoon, Sydney, and Tokyo). Traders can tailor colors, line styles, widths, transparency, and session times to align with their strategies and timezones.
Ideal for forex, stocks, futures, and crypto traders, this indicator simplifies the identification of key market periods—such as session openings/closings or new weeks—that often signal increased volatility or trend shifts. It’s optimized for intraday timeframes for session separators but supports all timeframes for week, day, and month markers, making it a versatile addition to any trader’s toolkit.
Features
Week Separators: Marks Monday starts with customizable lines and "Week Start" labels.
Day Separators: Highlights daily openings with lines and "Day Start" labels.
Month Separators: Indicates new months with lines and "Month Start" labels.
Session Separators: Plots lines and labels for major trading sessions’ start and end:
Frankfurt (default: 07:00–15:00 UTC)
London (default: 08:00–16:00 UTC)
NY Morning (default: 13:00–16:00 UTC)
NY Afternoon (default: 16:00–21:00 UTC)
Sydney (default: 22:00–06:00 UTC)
Tokyo (default: 00:00–08:00 UTC)
Timezone Support: Adjusts session times with a UTC offset (±12 hours).
Display Flexibility : Toggle between labeled vertical lines or background highlights.
Customization: Fine-tune colors, line styles (solid, dashed, dotted), widths, and transparency.
Background Mode: Highlights periods with translucent backgrounds for cleaner charts.
[ i]Labeled Lines: Each line includes descriptive labels (e.g., "London Open", "Tokyo Closed") when not in background mode.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor.
Click "Add to Chart" to apply the indicator.
Customize Settings:
Open settings via double-click or the "Settings" gear icon.
Timezone Offset: Set your UTC offset (e.g., -5 for EST) to align sessions.
Toggles: Enable/disable week, day, month, or session separators.
Appearance: Adjust colors, line styles, widths, and transparency for each separator.
Session Times: Modify start/end hours and minutes if defaults don’t suit your market.
Background Mode: Enable "Show as Background" for colored backgrounds instead of lines, and tweak "Session Background Transparency."
Labels: Labeled lines (e.g., "Sydney Open") appear automatically unless background mode is active.
Chart Compatibility:
Session separators require intraday timeframes (e.g., 1-minute to 4-hour).
Week, day, and month separators work across all timeframes.
Confirm your chart’s timezone aligns with your analysis.
Analyze:
Use separators to pinpoint session transitions, daily openings, or weekly shifts for trade planning.
Labels make it easy to spot key periods on busy charts.
Pair with indicators like RSI, volume, or support/resistance for deeper insights.
Example Use Cases
Forex Trading: Highlight London and NY session opens/closes for high-liquidity entries.
Day Trading: Reset strategies at daily separators and monitor intraday volatility.
Swing Trading: Use week/month separators to track longer-term trends.
Session Focus: Isolate sessions like Tokyo for regional market analysis.
Chart Clarity: Background mode declutters charts while marking key times.
Notes
Session separators are disabled on daily+ timeframes to prevent clutter.
Verify timezone offset for accurate session alignment.
Background mode suits lower timeframes for readability.
Labels are visible only when background mode is disabled.
Feedback
Share your thoughts or suggestions to make this indicator even better! Reach out via TradingView or connect with the author for insights. Happy trading!
About the Author
Dr. Jonpaul Nnamdi Opara, a PhD graduate from Ehime University, Japan, is a researcher and developer specializing in AI and machine learning. His work on automated landslide mapping and defect detection, published in journals like GEOMATE, showcases his precision-driven approach. With the "GranDoc" indicator, Jonpaul brings intuitive, data-driven clarity to financial markets, reflecting his expertise in creating impactful tools.
