Kase Dev Stops Backtest The Kase Dev Stops system finds the optimal statistical balance between letting profits run,
while cutting losses. Kase DevStop seeks an ideal stop level by accounting for volatility (risk),
the variance in volatility (the change in volatility from bar to bar), and volatility skew
(the propensity for volatility to occasionally spike incorrectly).
Kase Dev Stops are set at points at which there is an increasing probability of reversal against
the trend being statistically significant based on the log normal shape of the range curve.
Setting stops will help you take as much risk as necessary to stay in a good position, but not more.
WARNING:
- For purpose educate only
- This script to change bars colors.
Поиск скриптов по запросу "curve"
Kase Dev Stops Strategy The Kase Dev Stops system finds the optimal statistical balance between letting profits run,
while cutting losses. Kase DevStop seeks an ideal stop level by accounting for volatility (risk),
the variance in volatility (the change in volatility from bar to bar), and volatility skew
(the propensity for volatility to occasionally spike incorrectly).
Kase Dev Stops are set at points at which there is an increasing probability of reversal against
the trend being statistically significant based on the log normal shape of the range curve.
Setting stops will help you take as much risk as necessary to stay in a good position, but not more.
WARNING:
- For purpose educate only
- This script to change bars colors.
Kase Dev Stops The Kase Dev Stops system finds the optimal statistical balance between letting profits run,
while cutting losses. Kase DevStop seeks an ideal stop level by accounting for volatility (risk),
the variance in volatility (the change in volatility from bar to bar), and volatility skew
(the propensity for volatility to occasionally spike incorrectly).
Kase Dev Stops are set at points at which there is an increasing probability of reversal against
the trend being statistically significant based on the log normal shape of the range curve.
Setting stops will help you take as much risk as necessary to stay in a good position, but not more.
Lucid SARI wrote this script after having listened to Hyperwave with Sawcruhteez and Tyler Jenks of Lucid Investments Strategies LLC on July 3, 2019. They felt that the existing built-in Parabolic SAR indicator was not doing its calculations properly, and they hoped that someone might help them correct this. So I tried my hand at it, learning Pine Script as I went. I worked on it through the early morning hours and finished it by 4 am on July 4, 2019. I've added a few bits of code since, adding the rule regarding the SAR not advancing beyond the high (low) of the prior two candles during an uptrend (downtrend), but the core script is as it was.
This code is open source under the MIT license. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com
For more details on the initial script, see
Sawcruhteez from Lucid Investment Strategies wrote the following description of the Parabolic SAR, where the quotes are from Section II of J. Welles Wilder, Jr.'s book New Concepts in Technical Trading Systems (1978)
--------------------------------------------------------------------------------------------------------------------------
Parabolic SAR
"The Parabolic Time / Price System derives its name from the fact that when charted, the
pattern formed by the stops resembles a parabola, or if you will, a French Curve. The system
allows room for the market to react for the first few days after a trade is initiated and then the
stop begins to move up more rapidly. The stop is not only a function of price but also a function
of time .
"The stop never backs up. It moves an incremental amount each day, only in the direction which
the trade has been initiated."
"The stop is also a function of price because the distance the stop moves up is relative to the
favorable distance the price has moved... specifically, the most favorable price reached since the
trade was initiated."
A. The calculation for a bullish Parabolic SAR is:
Tomorrow’s SAR = Today’s SAR + AF(EP - Today’s SAR)
"Acceleration Factor (AF) is one of a progression of numbers beginning at 0.02 and ending at
0.20. The AF is increased by 0.02 each period that a new high is made" (if long) or new low is
made (if short).
EP is the "Extreme Price Point for the trade made so far. If Long , EP is the extreme high price for
the trade; if Short , EP is the extreme low price for the trade.”
Most websites will provide the above calculation for the Parabolic SAR but almost all of them
leave out this crucial detail:
B. "Never move the SAR into the previous day’s range or today’s range
"1. If Long , never move the SAR for tomorrow above the previous day’s low or
today’s low . If the SAR is calculated to be above the previous day’s low or
today’s low, then use the lower low between today and the previous day as
the new SAR. Make the next days calculations based upon this SAR.
"2. If Short , never move the SAR for tomorrow below the previous day’s high or
today’s high . If the SAR is calculated to be below the previous days’ high or
today’s high, then use the higher high between today and the previous day
as the new SAR. Make the next days calculations based upon this SAR."
When a Bullish SAR is broken then it gets placed at the SIP (significant point) of the prior trend.
In otherwords it is placed above the current candle and at the price that was the SIP.
The inverse is true for the first Bullish SAR.
"This system is a true reversal system; that is, every stop point is also a reverse point." If breaking
through a bearish SAR (one above price) that simultaneously signals to close a short and go
long.
DSL Synthetic MomentumThis indicator combines 5 running moving averages of different periods, calculate their momentum and synthesize the result into 1 single curve.
Dynamic levels made of the discontinued signal lines function are added to create pseudo overbought and oversold levels.
Rolling Skew (Returns) - Beasley SavageSkewness is a term in statistics used to describe asymmetry from the normal distribution in a set of statistical data. Skewness can come in the form of negative skewness or positive skewness, depending on whether data points are skewed to the left and negative, or to the right and positive of the data average. A dataset that shows this characteristic differs from a normal bell curve.
MMI SignalTrend trading strategies filtered by the Market Meanness Index.
This is a port of the experiment described at
www.financial-hacker.com
www.financial-hacker.com
www.financial-hacker.com
www.financial-hacker.com
The Market Meanness Index tells whether the market is currently moving in or out of a "trending" regime. It can this way prevent losses by false signals of trend indicators. It is a purely statistical algorithm and not based on volatility, trends, or cycles of the price curve.
The indicator measures the meanness of the market - its tendency to revert to the mean after pretending to start a trend. If that happens too often, all trend following systems will bite the dust.
Inputs
Price Source: Either open, high, low, close, hl2, hlc3, or ohlc4. The default value is hlc3.
Trend MA Type: Either SMA, EMA, LowPass, Hull MA, Zero-Lag MA, ALMA, Laguerre, Smooth, Decycle. The default value is LowPass.
Trend MA Period: Sets the lookback period of trend MA. The default value is 200.
MMI Period: Sets the lookback period of the Market Meanness Index. The default value is 300.
NG [Gaussian Filter Multi-Pole]When smoothing data there is always a trade-off between lag and removal of noise.
Gaussian filter has a consistently low lag and a very smooth curve.
This filter works for poles higher than the 4 (usual usage).
Mathematically maximum poles is 15 after which coefficients are too high to see any difference.
By tuning Lag and number of Poles you can achieve a very smooth MA with least lag possible.
It's just as good as 3rd gen moving averages and can be used as input feed for other indicators.
Standard Error of the Estimate -Composite Bands-Standard Error of the Estimate - Code and adaptation by @glaz & @XeL_arjona
Ver. 2.00.a
Original implementation idea of bands by:
Traders issue: Stocks & Commodities V. 14:9 (375-379):
Standard Error Bands by Jon Andersen
This code is a former update to previous "Standard Error Bands" that was wrongly applied given that previous version in reality use the Standard Error OF THE MEAN, not THE ESTIMATE as it should be used by Jon Andersen original idea and corrected in this version.
As always I am very Thankfully with the support at the Pine Script Editor chat room, with special mention to user @glaz in order to help me adequate the alpha-beta (y-y') algorithm, as well to give him full credit to implement the "wide" version of the former bands.
For a quick and publicly open explanation of this truly statistical (regression analysis) indicator, you can refer at Here!
Extract from the former URL:
Standard Error Bands are quite different than Bollinger's. First, they are bands constructed around a linear regression curve. Second, the bands are based on two standard errors above and below this regression line. The error bands measure the standard error of the estimate around the linear regression line. Therefore, as a price series follows the course of the regression line the bands will narrow, showing little error in the estimate. As the market gets noisy and random, the error will be greater resulting in wider bands.
Standard Error Bands by @XeL_arjonaStandard Error Bands - Code by @XeL_arjona
Original implementation by:
Traders issue: Stocks & Commodities V. 14:9 (375-379):
Standard Error Bands by Jon Andersen
Version 1
For a quick and publicly open explanation of this Statistical indicator, you can refer at Here!
Extract from the former URL:
Standard Error bands are quite different than Bollinger's. First, they are bands constructed around a linear regression curve. Second, the bands are based on two standard errors above and below this regression line. The error bands measure the standard error of the estimate around the linear regression line. Therefore, as a price series follows the course of the regression line the bands will narrow, showing little error in the estimate. As the market gets noisy and random, the error will be greater resulting in wider bands.
MA Ribbon (Horizontal Levels)📊 MA Ribbon (Horizontal Levels)
MA Ribbon (Horizontal Levels) is a minimalist moving average tool that displays moving averages as horizontal price levels instead of traditional sloping lines.
Rather than showing the historical path of each moving average, this indicator focuses exclusively on where each selected MA is currently located in price, allowing traders to treat moving averages as dynamic support and resistance levels.
The result is a clean, uncluttered chart that preserves moving average structure without visual noise.
🔍 What Makes It Different
No traditional moving average curves
No shading, bands, or fills
Each moving average is represented as a horizontal line at its current value
Lines automatically update as price and the MA value change
Designed to complement price action rather than dominate the chart
This approach makes it easier to see key MA levels at a glance, especially when multiple averages are in use.
⚙️ Key Features
✅ Fully Customizable Moving Averages
Select the moving average type:
SMA
EMA
SMMA (RMA)
WMA
VWMA
Choose the price source (e.g., close)
Configure up to 10 independent moving averages
✅ Per-MA Controls
Each moving average can be customized individually:
Enable or disable any MA (use anywhere from 1 to 10)
Set the MA period (length)
Choose line color
Adjust line thickness
Select line style (solid, dashed, dotted)
✅ Horizontal Level Visualization
Each MA is plotted as a horizontal line extending across the chart, representing the current value of that moving average.
As the MA updates, the level shifts vertically, maintaining a clear and consistent reference point.
🧠 How to Use It
This indicator is designed as a context and structure tool, not a signal generator.
Common use cases include:
Identifying dynamic support and resistance zones
Visualizing where short-term and long-term MA levels are stacked
Using MA levels as confluence with price action, VWAP, or volume-based tools
Maintaining a clean chart while still respecting moving average structure
Because the lines are horizontal, the indicator is especially useful for:
Breakout traders
Mean-reversion traders
Market participants who focus on structure and levels rather than indicator signals
🎯 Who It’s For
This indicator is ideal for traders who:
Prefer minimal, uncluttered charts
Think of moving averages as levels, not signals
Want full control over MA appearance and behavior
Use price action and structure first, indicators second
Use this tool in conjunction with standard moving average indicators, treating these horizontal MA levels as complementary reference points rather than replacements
MA Ribbon (Horizontal Levels) is built for traders who want clarity, flexibility, and structural insight — without sacrificing chart readability.
Apex Wallet - Ultimate Trading Suite: All-In-One Overlay & SignaOverview The Apex Wallet All-In-One is a comprehensive professional trading toolkit designed to centralize every essential technical analysis tool directly onto your main price chart. Instead of cluttering your workspace with dozens of separate indicators, this script integrates trend analysis, volatility bands, automated chart patterns, and a multi-indicator signal engine into a single, cohesive interface.
Key Modular Features:
Trend Core: Features dynamic trend curves, cloud fills for momentum visualization, and a multi-timeframe dashboard (1m to 4h) to ensure you are always trading with the higher-timeframe bias.
Automated Chart Structures: Automatically detects and plots Support/Resistance levels, Standard Pivot Points, Market Gaps, and Fair Value Gaps (Imbalances).
Volatility & Volume: Includes professional-grade VWAP with standard deviation bands, Bollinger Bands, and a built-in Volume Delta (Raw/Net) tracker.
Signal Engine: A powerful cross-logic system that generates entry signals based on RSI (QQE), MACD (Zero-cross & Relance), Stochastic, TDI, and the Andean Oscillator.
Predictive Projections: A unique feature that projects current indicator slopes into future candles to help anticipate potential trend continuations or reversals.
Adaptability The script includes three core presets—Scalping, Day-Trading, and Swing-Trading—which automatically adjust all internal periods (Moving Averages, Bollinger, RSI, etc.) to match your specific market speed.
Visual Cleanliness Every feature is toggleable. You can display a "clean" chart with just the Trend Cloud or a "complete" workstation with signals, patterns (Doji, Engulfing), and pivot levels
Fed Balance Sheet (Candles)Fed Balance Sheet (Candles) - TradingView Description
📊 OVERVIEW
Fed Balance Sheet (Candles) transforms the Federal Reserve's total assets into an intuitive candlestick visualization, allowing you to track monetary policy changes with the same visual language you use for price action.
This indicator pulls real-time data directly from FRED (Federal Reserve Economic Data) and displays the Total Assets of All Federal Reserve Banks as dynamic candles on your chart, making it effortless to correlate central bank liquidity with market movements.
🎯 WHY THIS MATTERS
The Federal Reserve's balance sheet is one of the most powerful leading indicators in global markets. When the Fed expands its balance sheet (Quantitative Easing), it injects liquidity into the financial system, historically correlating with:
Rising asset prices (stocks, crypto, commodities)
Lower volatility
Risk-on sentiment
Currency devaluation
When the Fed contracts its balance sheet (Quantitative Tightening), liquidity drains from markets, often leading to:
Asset price pressure
Increased volatility
Risk-off sentiment
Dollar strength
By visualizing this as candles, you can instantly see:
The pace of change (candle size)
The direction (green = expansion, red = contraction)
Acceleration or deceleration (consecutive candles in same direction)
Pivots in monetary policy (color changes from green to red or vice versa)
🔧 HOW IT WORKS
Data Source
Source: Federal Reserve Economic Data (FRED)
Metric: Total Assets of All Federal Reserve Banks
Unit: Displayed in Trillions of USD for easy reading
Frequency: Weekly updates (every Wednesday)
Candlestick Construction
Since balance sheet data is reported as a single number each week (not traditional open-high-low-close), this indicator creates candles by comparing each period to the previous one:
Open = Last week's balance sheet value
Close = This week's balance sheet value
High = The higher of the two values
Low = The lower of the two values
This captures directional movement and magnitude of change, making it intuitive for traders accustomed to candlestick analysis.
Color Scheme
🟢 GREEN CANDLES (Expanding Balance Sheet)
When this week's value is higher than last week's
Interpretation: Fed is adding liquidity (Quantitative Easing)
Historically bullish for risk assets
🔴 RED CANDLES (Contracting Balance Sheet)
When this week's value is lower than last week's
Interpretation: Fed is removing liquidity (Quantitative Tightening)
Historically bearish or neutral for risk assets
Value Label
A floating label displays the current balance sheet value in trillions (e.g., "$8.75T") so you always know the exact figure at a glance.
📈 PRACTICAL APPLICATIONS
1. Market Regime Identification
Strings of green candles = Liquidity-driven bull markets
Strings of red candles = Tightening-induced bear markets or corrections
Color transitions = Potential market inflection points
2. Correlation Analysis
Overlay on stock indices (SPY, QQQ, IWM)
Overlay on crypto (BTC, ETH)
Overlay on commodities (Gold, Silver)
Observe how asset prices react to Fed liquidity changes in real-time
3. Macro Timing
Large green candles = Aggressive easing (crisis response)
Large red candles = Aggressive tightening (inflation fighting)
Small candles = Neutral policy (Fed on hold)
4. Risk Management
Shift portfolio allocation based on liquidity environment
Reduce leverage during red candle trends
Increase exposure during green candle trends
Use as confirmation for other technical signals
5. Multi-Timeframe Context
Daily charts: See how daily price action relates to weekly Fed data
Weekly charts: Perfect alignment with data release frequency
Monthly charts: Visualize long-term monetary cycles spanning years
⚙️ SETTINGS
Zero configuration needed. Simply add the indicator to any chart and it works immediately.
The indicator automatically:
Overlays on your main chart
Uses the left price scale (won't interfere with asset prices)
Updates with the latest Fed data
Displays values in trillions for clean readability
🎨 VISUAL DESIGN PHILOSOPHY
The indicator uses semi-transparent candle bodies with vibrant borders to maintain visibility without obscuring your price action. The color scheme follows universal chart conventions where green represents growth/expansion and red represents decline/contraction.
It's designed to blend seamlessly into any chart theme while providing immediate visual clarity about the Fed's monetary stance.
📚 WHAT YOU NEED TO KNOW
Data Availability
Historical data available from December 2002 (over 20 years of Fed policy)
Updates every Wednesday (Federal Reserve's reporting schedule)
Typically published with a 1-week lag
How the Data Appears
On weekdays: Shows the most recent Wednesday's data
On weekends: Shows Friday's data (which is the prior Wednesday's figure)
Updates automatically when new data is released
Scale Considerations
The Fed's balance sheet is measured in trillions, while most assets are priced much lower. The indicator uses the left price scale by default to avoid conflicts with your main asset's price scale. You can easily move it to a separate pane if you prefer.
🧠 INTERPRETATION GUIDE
Historical QE Phases (Green Candles)
2008-2014: Financial Crisis Response
The Fed's balance sheet expanded from under $1T to ~$4.5T to stabilize markets after the mortgage crisis.
2020: COVID-19 Response
Rapid expansion to ~$7T as the Fed stepped in during pandemic lockdowns.
2020-2022: Extended Support
Balance sheet reached historic peak of ~$9T.
Historical QT Phases (Red Candles)
2017-2019: First Modern QT Attempt
The Fed tried to normalize its balance sheet, reducing it from ~$4.5T to ~$3.8T before pivoting.
2022-Present: Inflation-Fighting QT
The Fed began shrinking its balance sheet to combat inflation, letting bonds mature without replacement.
Key Insights
Size matters, but rate of change matters MORE.
A $9T balance sheet growing slowly has different implications than a $5T balance sheet growing rapidly.
Watch for acceleration.
Increasingly large candles (up or down) signal a policy shift that markets will notice.
Plateaus mean "wait and see."
Tiny candles indicate the Fed is holding steady and watching economic data.
Reversals are major events.
When candles switch from green to red (or vice versa), the Fed has changed course—these are critical market turning points.
🎓 EDUCATIONAL VALUE
This indicator helps you understand:
The mechanics of monetary policy through visual learning
The lag between Fed actions and market reactions by observing temporal correlation
The scale of modern central banking (trillions put into perspective)
The relationship between liquidity and asset prices (cause and effect in action)
Many traders talk about "don't fight the Fed" but never actually track what the Fed is doing. Now you can see it as clearly as you see price action.
🔗 RELATED CONCEPTS
For comprehensive macro analysis, consider also tracking:
Fed Funds Rate (short-term interest rates)
M2 Money Supply (broader measure of money in circulation)
Treasury Yield Curves (bond market expectations)
Dollar Index (DXY) (currency strength)
VIX (market fear/volatility)
The Fed's balance sheet is just one piece of the puzzle, but it's arguably the most important one for understanding liquidity conditions.
⚠️ DISCLAIMER
This indicator displays publicly available economic data from the Federal Reserve. It is for informational and educational purposes only and does not constitute financial advice.
Important considerations:
Past monetary policy does not guarantee future market outcomes
Correlation does not equal causation
Asset prices are influenced by many factors beyond Fed liquidity
Always use proper risk management
Consult with qualified financial professionals before making investment decisions
Trading involves substantial risk of loss and is not suitable for everyone.
📜 VERSION HISTORY
Version 1.0 - Initial Release
Fed balance sheet visualized as candlesticks
Real-time FRED data integration
Automatic display in trillions
Dynamic color coding (green/red)
Current value label with exact figure
💡 WHY CANDLES?
You might wonder: "Why show the Fed's balance sheet as candles instead of a line?"
Because candles tell stories that lines can't.
A line shows you where we are
Candles show you how we got here, how fast we're moving, and what momentum looks like
Candles make the Fed's actions feel immediate and tangible
Candles connect macro data to the chart language you already speak
When you see three big green candles in a row on the Fed balance sheet while your crypto or stock portfolio is rallying, you feel the connection. When you see the candles turn red and shrink, you understand the headwinds forming.
It transforms dry economic data into actionable market intelligence.
📞 SUPPORT & FEEDBACK
If you find this indicator valuable:
⭐ Like and favorite to help others discover it
📝 Comment with your use cases and insights
🔔 Follow for updates and new macro indicators
Your feedback drives improvements and helps build better tools for the trading community.
🚀 THE BOTTOM LINE
The Fed's balance sheet is the tide that lifts or lowers all boats.
Whether you're trading stocks, crypto, forex, or commodities—whether you're a day trader or long-term investor—understanding the Fed's liquidity operations gives you an edge.
This indicator makes that understanding visual, immediate, and actionable.
Stop guessing about macro conditions. Start seeing them.
"Don't fight the Fed" - Wall Street Wisdom
Now you can see exactly what they're doing—in the same language you use to read price action.
May your trades ride the tide of liquidity. 🌊📈
Area per IntervalDescription
This indicator shades the area between 2 curves, an SMA and the nearest open/close to the SMA, and their intersections. The black labels with leader lines describe the calculated area of each shaded section, and the total area accumulated per total number of time intervals for that area. The additional value visible in the status line that is not displayed on the chart is, at any bar index (time interval), the current total area of the incomplete shaded area.
Usage
- The default color of the shaded areas denote the type of momentum being built before the cross. Green for bullish, red for bearish.
- The area value of the shaded areas can be used as a capacity indicator, denoting imbalances between the previous and next crosses.
- The area per interval value of the shaded areas can be used as a momentum indicator, denoting which area is carrying more price movement before the price crosses.
- Similar to indicators that use dynamic price differences between OHLC data, moving averages, etc, confluence with other momentum indicators that use different elements creates additional confirmation.
Conclusion
Simple momentum indicator. Comment for possible updates that can be made.
Multi-Distribution Volume Profile (Zeiierman)█ Overview
Multi-Distribution Volume Profile (Zeiierman) is a flexible, structure-first volume profile tool that lets you reshape how volume is distributed across price, from classic uniform profiles to advanced statistical curves like Gaussian, Lognormal, Student-t, and more.
Instead of forcing every market into a single "one-size-fits-all" profile, this tool lets you model how volume is likely concentrated inside each bar (body vs wicks, midpoint, tails, center bias, right-skew, heavy tails, etc.) and then stacks that behavior across a whole lookback window to build a rich, multi-distribution map of traded activity.
On top of that, it overlays a dynamic Center Band (value area) and a fade/gradient model that can color each price row by volume, hits, recency, volatility, reversals, or even liquidity voids, turning a plain profile into a multi-dimensional context map.
Highlights
Choose from multiple Profile Build Modes , including uniform, body-only, wick-only, midpoint/close/open, center-weighted, and a suite of probability-style distributions (Gaussian, Lognormal, Weibull, Student-t, etc.)
Flexible anchor layout: draw the profile on Right/Left (horizontal) or Bottom/Top (vertical) to fit any chart layout
Value Area / Center Band computed from volume quantiles around the POC.
Gradient-based Fade Metrics: volume, price hits, freshness (time decay), volatility impact, dwell time, reversal density, compression, and liquidity voids
Separate bullish vs bearish volume at each price row for directional structure insights
█ How It Works
⚪ Profile Construction
The script scans a user-defined Bars Included window and finds the full high–low span of that zone. It then divides this range into a user-controlled number of Price Levels (rows).
For each historical bar within the window:
It measures the candle’s price range, body, and wicks.
It assigns volume to rows according to the selected Profile Build Mode, for example:
* Range Uniform – volume spread evenly across the full high–low range.
* Range Body Only / Range Wick Only – concentrate volume inside the body or wicks only.
* Midpoint / Close / Open Only – allocate volume entirely into one price row (pinpoint modeling).
HL2 / Body Center Weighted – center weights around the middle of the range/body.
Recent-Weighted Volume – amplify newer bars using exponential time decay.
Volume Squared (Hard) – aggressively boost bars with large volume.
Up Bars Only / Down Bars Only – filter volume to only bullish or bearish bars.
For more advanced shapes, the script uses continuous distributions across the bar’s span:
Linear, Triangular, Exponential to High
Cosine Centered, PERT
Gaussian, Lognormal, Cauchy, Laplace
Pareto, Weibull, Logistic, Gumbel
Gamma, Beta, Chi-Square, Student-t, F-Shape
Each distribution produces a weight for each row within the bar’s range, normalized so the total volume remains consistent, but the shape of where that volume lands changes.
⚪ POC & Center Band (Value Area)
Once all rows are accumulated:
The row with the highest total volume becomes the Point of Control (POC)
The script computes cumulative volume and finds the band that wraps a user-defined Center of Profile % (e.g., 68%) around the center of distribution.
This range is displayed as a central band, often treated like a value area where price has spent the most “effort” trading.
⚪ Gradient Fade Engine
Each row also gets a fade metric, chosen in Fade Metric:
Volume – opacity based on relative volume.
Price Hits – how frequently that row was touched.
Blended (Vol+Hits) – average of volume & hits.
Freshness – emphasizes recent activity, controlled by Decay.
Volatility Impact – rows that saw larger ranges contribute more.
Dwell Time – where price “camped” the longest.
Reversal Density – where direction changes cluster.
Compression – tight-range compression zones.
Liquidity Void – inverse of volume (thin liquidity zones).
When Apply Gradient is enabled, the row’s bullish/bearish colors are tinted from faint to strong based on this chosen metric, effectively turning the profile into a heatmap of your chosen structural property.
█ How to Use
⚪ Explore Different Distribution Assumptions
Switch between multiple Profile Build Modes to see how your assumptions about intrabar volume affect structure:
Use Range Uniform for classical profile reading.
Deploy Gaussian, Logistic, or Cosine shapes to emphasize central clustering.
Try Pareto, Lognormal, or F-Shape to focus on tail / extremal activity.
Use Recent-Weighted Volume to prioritize the most recent structural behavior.
This is especially useful for traders who want to test how different modeling assumptions change perceived value areas and levels of interest.
⚪ Identify Value, Acceptance & Rejection Zones
Use the POC and Center of Profile (%) band to distinguish:
High-acceptance zones – wide central band, thick rows, strong gradient → fair value areas
Rejection zones & tails – thin extremes, low dwell time, high volatility or reversal density
These regions can be used as:
Targets and origin zones for mean reversion
Context for breakout validation (leaving value)
Bias reference for intraday rotations or swing rotations
⚪ Read Directional Structure Within the Profile
Because each row is split into bullish vs bearish contributions, you can visually read:
Where buyers dominated a price region (large bullish slice)
Where sellers absorbed or defended (large bearish slice)
Combining this with Fade Metrics like Reversal Density, Dwell Time, or Freshness turns the profile into a structural order-flow map, without needing raw tick-by-tick volume data.
⚪ Use Fade Metrics for Contextual Heatmaps
Each Fade Metric can be used for a different analytical lens:
Volume / Blended – emphasize where volume and activity are concentrated.
Freshness – highlight the most recently active zones that still matter.
Volatility Impact & Compression – spot areas of explosive moves vs coiled ranges.
Reversal Density – locate micro turning points and battle zones.
Liquidity Void – visually pop out thin regions that may act as speedways or magnets.
█ Settings
Profile Build Mode – Selects how each bar’s volume is distributed across its price range (uniform, body/wick, midpoint/close/open, center-weighted, or statistical distribution families).
Bars Included – Number of bars used to build the profile from the current bar backward.
Price Levels – Vertical resolution of the profile: more levels = smoother but heavier.
Anchor Side – Where the profile is drawn on the chart: Right, Left, Bottom, or Top.
Offset (bars) – Horizontal offset from the last bar to the profile when using Right/Left modes.
Apply Gradient – Toggles the fade/heatmap coloring based on the selected metric.
Fade Metric – Chooses the property driving row opacity (Volume, Hits, Freshness, Volatility Impact, Dwell Time, Reversal Density, Compression, Liquidity Void).
Decay – Time-decay factor for Freshness (values close to 1 keep older activity relevant for longer).
Profile Thickness – Relative thickness of the profile along the time axis, as a % of the lookback window.
Center of Profile (%) – Volume percentage used to define the central band (value area) around the POC.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Robrechtian Long-Medium Breakout Trend SystemRobrechtian Long–Medium-Term Breakout Trend System
A professional, rule-based trend-following strategy designed to capture large, sustained price movements using pure price action and breakouts.
This system follows long-established trend-following philosophy: no prediction, no volatility targeting, and no profit targets. Only disciplined entries, position additions, and exits driven entirely by trend structure.
Core Principles
Breakout-driven entries: Initial positions are taken only when price breaks above/below the 80-day Donchian channel, confirming a long–medium-term trend shift.
Short-term confirmation: Breakouts must also exceed the 20-day channel, reducing false positives.
Trend-direction filter: A 50-day moving average slope filter ensures alignment with the broader trend.
Explosive bar filter: Entries avoid excessively large, single-candle expansions (>2.5× ATR(20)) to prevent chasing exhaustion spikes.
Pyramiding into strength: Additional units are added only when price makes fresh 20-day breakouts in the direction of the trend. No scaling out. No adding on dips.
Exit only on trend violation: Positions are closed exclusively when price breaks the opposite 80-day channel. This preserves unlimited upside while enforcing disciplined exits.
Pure trend philosophy: No volatility targeting, no smoothing, no discretionary overrides, no optimization for short-term performance.
Intended Use
This system is designed primarily for diversified futures portfolios, where diversification across dozens of globally liquid markets creates robustness and stability. However, it may also be used on individual assets for educational and analytical purposes.
The system embraces the core trend-following logic:
Small losses, big winners, and unlimited upside when trends persist.
⚠️ WARNINGS / DISCLAIMERS
⚠️ Warning 1 — This strategy is not optimized for single stocks
The Robrechtian Trend System is designed for multi-asset futures portfolios, not single equities.
Performance on individual tickers may vary greatly due to lack of diversification.
⚠️ Warning 2 — Trend following includes substantial drawdowns
Deep drawdowns are a normal and expected feature of all long-term trend-following systems.
The strategy does not attempt to smooth returns or manage volatility.
If you seek steady, low-volatility equity curves, this system is not suitable.
⚠️ Warning 3 — No volatility targeting or risk smoothing
This system intentionally avoids volatility-based position sizing.
Trades may experience larger fluctuations than systems using risk parity or vol targeting.
⚠️ Warning 4 — Not financial advice
This script is for educational and research purposes only.
Past performance does not guarantee future results.
Use at your own risk.
⚠️ Warning 5 — TradingView backtests have known limitations
TradingView does not simulate:
futures contract roll logic
slippage
real bid/ask spreads
liquidity conditions
limit-up/limit-down behavior
Results may vary from live market execution.
Kalman Ema Crosses - [JTCAPITAL]Kalman EMA Crosses - is a modified way to use Kalman Filters applied on Exponential Moving Averages (EMA Crosses) for Trend-Following.
Credits for the kalman function itself goes to @BackQuant
The Kalman filter is a recursive smoothing algorithm that reduces noise from raw price or indicator data, and in this script it is applied both directly to price and on top of EMA calculations. The goal is to create cleaner, more reliable crossover signals between two EMAs that are less prone to false triggers caused by volatility or market noise.
The indicator works by calculating in the following steps:
Source Selection
The script starts by selecting the price input (default is Close, but can be adjusted). This chosen source is the foundation for all further smoothing and EMA calculations.
Kalman Filtering on Price
Depending on user settings, the selected source is passed through one of two independent Kalman filters. The filter takes into account process noise (representing expected market randomness) and measurement noise (representing uncertainty in the price data). The Kalman filter outputs a smoothed version of price that minimizes noise and preserves underlying trend structure.
EMA Calculation
Two exponential moving averages (EMA 1 and EMA 2) are then computed on the Kalman-smoothed price. The lengths of these EMAs are fully customizable (default 15 and 25).
Kalman Filtering on EMA Values
Instead of directly using raw EMA curves, the script applies a second layer of Kalman filtering to the EMA values themselves. This step significantly reduces whipsaw behavior, creating smoother crossovers that emphasize real momentum shifts rather than temporary volatility spikes.
Trend Detection via EMA Crossovers
-A bullish trend is detected when EMA 1 (fast) crosses above EMA 2 (slow).
-A bearish trend is detected when EMA 1 crosses below EMA 2.
The detected trend state is stored and used to dynamically color the plots.
Visual Representation
Both EMAs are plotted on the chart. Their colors shift to blue during bullish phases and purple during bearish phases. The area between the two EMAs is filled with a shaded region to clearly highlight trending conditions.
Buy and Sell Conditions:
-Buy Condition: When the Kalman-smoothed EMA 1 crosses above the Kalman-smoothed EMA 2, a bullish crossover is confirmed.
-Sell Condition: When EMA 1 crosses below EMA 2, a bearish crossover is confirmed.
Users may enhance the robustness of these signals by adjusting process noise, measurement noise, or EMA lengths. Lower measurement noise values make the filter react faster (but potentially noisier), while higher values make it smoother (but slower).
Features and Parameters:
-Source: Selectable price input (Close, Open, High, Low, etc.).
-EMA 1 Length: Defines the fast EMA period.
-EMA 2 Length: Defines the slow EMA period.
-Process Noise: Controls how much randomness the Kalman filter assumes in price dynamics.
-Measurement Noise: Controls how much uncertainty is assumed in raw input data.
-Kalman Usage: Option to apply Kalman filtering either before EMA calculation (on price) or after (on EMA values).
Specifications:
Kalman Filter
The Kalman filter is an optimal recursive algorithm that estimates the state of a system from noisy measurements. In trading, it is used to smooth prices or indicator values. By balancing process noise (expected volatility) with measurement noise (data uncertainty), it generates a smoothed signal that reacts adaptively to market conditions.
Exponential Moving Average (EMA)
An EMA is a weighted moving average that emphasizes recent data more heavily than older data. This makes it more responsive than a simple moving average (SMA). EMAs are widely used to identify trends and momentum shifts.
EMA Crossovers
The crossing of a fast EMA above a slow EMA suggests bullish momentum, while the opposite suggests bearish momentum. This is a cornerstone technique in trend-following systems.
Dual Kalman Filtering
Applying Kalman both to raw price and to the EMAs themselves reduces whipsaws further. It creates crossover signals that are not only smoothed but also validated across two levels of noise reduction. This significantly enhances signal reliability compared to traditional EMA crossovers.
Process Noise
Represents the filter’s assumption about how much the underlying market can randomly change between steps. Higher values make the filter adapt faster to sudden changes, while lower values make it more stable.
Measurement Noise
Represents uncertainty in price data. A higher measurement noise value means the filter trusts the model more than the observed data, leading to smoother results. A lower value makes the filter more reactive to observed price fluctuations.
Trend Coloring & Fill
The use of dynamic colors and filled regions provides immediate visual recognition of trend states, helping traders act faster and with greater clarity.
Enjoy!
Super-AO with Risk Management Alerts Template - 11-29-25Super-AO with Risk Management: ALERTS & AUTOMATION Edition
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
This is the Indicator / Alerts companion to the Super-AO Strategy.
While the Strategy version is built for backtesting (verifying profitability and checking historical performance), this Indicator version is built for Live Execution.
We understand the frustration of finding a great strategy, only to realize you can't easily hook it up to your trading bot. This script solves that. It contains the exact same "Super-AO" logic and "Risk Management Engine" as the strategy version, but it is optimized to send signals to automation platforms like Signal Lynx, 3Commas, or any Webhook listener.
2. Quick Action Guide (TL;DR)
Purpose: Live Signal Generation & Automation.
Workflow:
Use the Strategy Version to find profitable settings.
Copy those settings into this Indicator Version.
Set a TradingView Alert using the "Any Alert() function call" condition.
Best Timeframe: 4 Hours (H4) and above.
Compatibility: Works with any webhook-based automation service.
3. Why Two Scripts?
Pine Script operates in two distinct modes:
Strategy Mode: Calculates equity, drawdowns, and simulates orders. Great for research, but sometimes complex to automate.
Indicator Mode: Plots visual data on the chart. This is the preferred method for setting up robust alerts because it is lighter weight and plots specific values that automation services can read easily.
The Golden Rule: Always backtest on the Strategy, but trade on the Indicator. This ensures that what you see in your history matches what you execute in real-time.
4. How to Automate This Script
This script uses a "Visual Spike" method to trigger alerts. Instead of drawing equity curves, it plots numerical values at the bottom of your chart when a trade event occurs.
The Signal Map:
Blue Spike (2 / -2): Entry Signal (Long / Short).
Yellow Spike (1 / -1): Risk Management Close (Stop Loss / Trend Reversal).
Green Spikes (1, 2, 3): Take Profit Levels 1, 2, and 3.
Setup Instructions:
Add this indicator to your chart.
Open your TradingView "Alerts" tab.
Create a new Alert.
Condition: Select SAO - RM Alerts Template.
Trigger: Select Any Alert() function call.
Message: Paste your JSON webhook message (provided by your bot service).
5. The Logic Under the Hood
Just like the Strategy version, this indicator utilizes:
SuperTrend + Awesome Oscillator: High-probability swing trading logic.
Non-Repainting Engine: Calculates signals based on confirmed candle closes to ensure the alert you get matches the chart reality.
Advanced Adaptive Trailing Stop (AATS): Internally calculates volatility to determine when to send a "Close" signal.
6. About Signal Lynx
Automation for the Night-Shift Nation 🌙
We are providing this code open source to help traders bridge the gap between manual backtesting and live automation. This code has been in action since 2022.
If you are looking to automate your strategies, please take a look at Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
Trend BG v2Trend BG v2 colors the chart background based on Directional Movement (DM) and DI strength. It provides an easy visual way to identify trending and non-trending conditions on any timeframe.
How It Works
The script calculates:
Upward Directional Movement (DM+)
Downward Directional Movement (DM–)
True Range smoothed with RMA (14-period)
Positive DI and Negative DI values from classic ADX logic
The trend state is determined by comparing +DI vs –DI:
+DI > –DI → Uptrend
–DI > +DI → Downtrend
Otherwise → Neutral / Sideways
The script then applies a background color based on the detected trend.
Color transparency and theme can be adjusted using the input options.
Why This Script Is Useful
Instead of plotting DI lines or ADX curves, this version presents the trend directly on the background, making it ideal for:
Quick trend recognition
Visual filtering of choppy vs trending markets
Enhancing manual or automated setups
Intraday scalping, positional trend following, and multi-timeframe analysis
The background display is subtle, customizable, and does not interfere with other indicators on the chart.
Key Features
Trend-colored chart background (Up / Down / Neutral)
Adjustable color palette and transparency
Built using classic Directional Movement logic
Works on all markets and all timeframes
Lightweight and efficient (no repainting)
How to Use It
Apply the indicator on your chart and use the background colors to:
Align trades with the market trend
Avoid trading during neutral or low-momentum periods
Confirm trend direction before entries
Improve clarity when using your existing indicators
This indicator does not generate buy/sell signals by itself; instead, it helps visualize the underlying trend environment so traders can make more informed decisions.
Atlas 8 Currency Session Momentum (6H, London)This indicator calculates real-time currency strength for the 8 major currencies (USD, EUR, GBP, JPY, AUD, NZD, CAD, CHF) using a balanced multi-pair engine and a 6-hour momentum reset.
🔍 How it works
The indicator computes the relative strength of each currency by averaging the percentage change of 7 major cross-pairs for each currency.
A currency's value increases when pairs where it is the base appreciate, and decreases when pairs where it is the quote depreciate.
This creates a symmetric and stable strength calculation similar to institutional relative-value models.
🕒 Session-based Momentum Reset
The global trading day is split into 4 × 6-hour blocks:
• 00:00–06:00 Tokyo
• 06:00–12:00 London
• 12:00–18:00 New York
• 18:00–24:00 Late US/Asia pre-open
At each new 6-hour session, all strength lines reset to 0.
This highlights fresh intraday momentum generated by liquidity transitions between sessions.
🎯 What the indicator shows
• Relative strength of all 8 currencies
• Smooth momentum curves using EMA smoothing
• Vertical dividers at each new session
• Background color for each session
• Real intraday build-up of strength/weakness (not cumulative from previous day)
This tool is designed for intraday traders who follow cross-currency momentum during session transitions (Tokyo → London → NY).
🧭 How to use it
• Look for the strongest vs weakest currency after each session reset
• Identify fresh trends during London and NY opens
• Confirm currency-pair bias using strength divergence
• Track momentum exhaustion when lines flatten or converge
Liquidity LayoutLiquidity Layout
The Liquidity Layout is a comprehensive macroeconomic indicator that tracks global liquidity conditions by aggregating multiple financial data streams from major economies (US, EU, China, Japan, UK, Canada, Switzerland). It provides traders with a macro view of market liquidity to help identify favorable conditions for risk assets
⚠️ Important: Timeframe Settings
This indicator is designed for the 1W (weekly) timeframe. If you use other timeframes, you must adjust the offset parameter in the settings to properly align the data with price action. The default offset of 12 is calibrated for weekly charts.
What It Measures
This indicator combines seven key components of global liquidity:
1. Global M2 Money Supply - Tracks broad money supply (M2) plus 10% of narrow money supply (M1) across major economies, weighted by currency strength. This represents the total amount of money circulating in the private sector.
2. Central Bank Balance Sheets (CBBS) - Monitors the combined balance sheets of major central banks (Fed, ECB, BoJ, PBoC, etc.), reflecting quantitative easing and monetary expansion policies.
3. Foreign Exchange Reserves (FER) - Aggregates forex reserves held by central banks, indicating international liquidity buffers and capital flows.
4. Current Account + Capital Flows (CA) - Combines current account balances with capital flows to measure cross-border money movement and trade liquidity.
5. Government Spending (GSP) - Tracks government expenditure minus a portion of federal expenses, representing fiscal stimulus and public sector liquidity injection.
6. World Currency Unit (WCU) - A custom forex composite that weights major and emerging market currencies to capture global currency strength dynamics.
7. Bond Market Conditions - Analyzes yield curves, spreads, and bond indices to assess credit conditions and risk appetite in fixed income markets.
The Formula
The indicator uses two main calculation modes:
ADJ Global Liquidity (Default):
×
This multiplies liquidity components by currency and bond market factors to capture the interactive effects between monetary conditions and market sentiment.
TPI (Trend Power Index) Mode:
A normalized version that combines all components with optimized weights:
Global Liquidity Index: 10%
Bonds: 17.5%
Bond Yields: 25%
Currency Strength: 25%
Government Spending: 5%
Current Account: 5%
M2: 2.5%
Central Bank Balance Sheets: 2.5%
Forex Reserves: 5%
Oil (macro risk indicator): 2.5%
How to Use It
Visualization Modes:
Background Mode (default): Orange background appears when TPI is positive (favorable liquidity conditions)
Line Mode: Displays the indicator as an orange line with customizable offset
Interpreting the Signal:
Positive/Rising = Expanding liquidity, generally bullish for risk assets
Negative/Falling = Contracting liquidity, risk-off environment
TPI > 1 = Extremely favorable conditions (upper threshold)
TPI < -1 = Severe liquidity stress (lower threshold)
Best Practices:
Use on higher timeframes (daily, weekly) for macro trend analysis
Combine with price action - liquidity often leads market moves by weeks or months
Watch for divergences between liquidity and asset prices
Particularly relevant for Bitcoin, equities, and risk assets
Data Sources
The indicator pulls real-time economic data from TradingView's ECONOMICS database and major market indices, including central bank statistics, government reports, and forex rates across G7 and major emerging markets.
Settings
Data Plot: Choose which liquidity component to display
Plot Type: Switch between raw Index values or normalized TPI
Offset: Shift the plot forward/backward for alignment (default: 12 for weekly charts)
Style: Background shading or line plot
Notes
This is a macro-level indicator best suited for understanding the broader liquidity environment rather than short-term trading signals. It helps answer the question: "Is the global financial system expanding or contracting liquidity?"
Filte Ichimoku1. Indicator Name
Filte Ichimoku
2. One-line Introduction
A smoothed and visually enhanced version of the Ichimoku Cloud that highlights trend direction and strength using adaptive color transparency.
3. General Overview
Filte Ichimoku is a modernized take on the classic Ichimoku Kinko Hyo indicator, designed for traders who value clarity and minimalism while retaining core Ichimoku functionality.
It calculates traditional components like Tenkan-sen, Kijun-sen, and the Senkou Span A/B, but focuses primarily on visualizing the Kumo (cloud) with enhanced styling.
Instead of raw plots, Filte Ichimoku applies triple-step smoothing to both Senkou spans, creating a soft, wave-like appearance that reflects trend fluidity.
The color of the cloud dynamically adapts based on whether Span A is above or below Span B (bullish/bearish), and its opacity changes according to the intensity of the trend, which is calculated relative to ATR-based volatility.
By forward-shifting the plots and visually blending the cloud, the indicator helps traders quickly identify dominant trends, potential reversals, and consolidation zones.
Its clean design makes it highly compatible with both traditional Ichimoku strategies and modern price action systems.
4. Key Advantages
🌥 Adaptive Ichimoku Cloud
Cloud color and transparency dynamically change based on real trend strength and direction.
📊 Smoother, Cleaner Display
Triple-smoothing on Senkou A and B creates a less noisy, more readable visual output.
📈 Forward Shift Preserved
Maintains the traditional Ichimoku forward-shift logic, helping project future price zones.
🎨 Customizable Trend Colors
Define your own bullish and bearish cloud colors for easy visual alignment with your strategy.
🚫 Noise Reduction via ATR Normalization
Trend intensity is calculated relative to ATR, reducing false positives in low-volatility zones.
🔒 Lightweight & Secure Design
Optimized script avoids exposure of sensitive logic while remaining fast and reliable in live charts.
📘 Indicator User Guide
📌 Basic Concept
Filte Ichimoku emphasizes cloud dynamics (Kumo) to interpret market structure.
Trend direction is derived from the relationship between Senkou Span A and B, while trend strength is measured by their distance relative to ATR.
The smoother curves make it easier to read while preserving all Ichimoku logic.
⚙️ Settings Explained
Tenkan Sen Length: Fast-moving average calculation period (default: 18)
Kijun Sen Length: Medium trend baseline (default: 52)
Senkou Span Length: Long-term cloud boundary (default: 104)
Bull/Bear Color: Set custom colors for bullish or bearish cloud states
📈 Bullish Timing Example
Senkou Span A > Span B, and the cloud appears green with high opacity
Indicates strong uptrend support, especially when price is above both Tenkan and Kijun
📉 Bearish Timing Example
Span B > Span A, cloud turns red and darkens
Suggests bearish dominance; avoid long entries or prepare for short-side setups
🧪 Recommended Use Cases
Use as a trend background layer for existing Ichimoku or price action systems
Combine with breakouts, support/resistance, and momentum indicators
Great for trend filtering in mid- to long-term strategies
🔒 Precautions
Designed for clarity and filtering—not a standalone entry system
In sideways markets, cloud may compress and color changes may become less meaningful
Adjust smoothing lengths cautiously to avoid lagging during volatile swings
Best results come from combining with price structure analysis
Swing Point PnL PressureThis indicator visualizes the cumulative profit potential of bulls and bears based on recent swing highs and lows — offering a unique lens into trend maturity, sentiment imbalance, and exhaustion risk.
🟢 Bull PnL rises as price moves above prior swing lows — reflecting unrealized gains for long positions
🔴 Bear PnL rises as price drops below prior swing highs — capturing short-side profitability
Over time, these curves diverge during strong trends, revealing which side is in control. But when they converge, it often signals that the dominant side is losing steam — a potential turning point where profit-taking, traps, or reversals may emerge.
This tool doesn’t predict tops or bottoms — it tracks the emotional and financial pressure building on each side of the market. Use it to:
Spot trend exhaustion before price confirms it
Identify profit parity zones where sentiment may flip
Time accumulation or distribution phases with greater confidence
Whether you’re swing trading or analyzing macro structure, this indicator helps you see what price alone can’t: who’s winning, who’s trapped, and who’s about to give up.
