Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
Trading
VWAP Reset at Asian Session (Midnight UTC)Vwap strategy based on mainly usd pairs for scalping it starts at the start of everyday and ends at the end of everyday and it is a line thats colour can be changed so u can design it acc to u it is best for scalping and taking small trades
Previous D/W/M HLOCHey traders,
Here's a simple Multi-Timeframe indicator that essentially turns time and price into a box. It'll take the previous high, low, opening price, or closing price from one of the three timeframes of your choice (day, week, or month). For whatever reason I can't get the opening price to function consistently so if you find improvements feel free to let me know, this will help traders who prefer to use opening price over closing price.
Naturally this form of charting is classical and nature and some key figures you could use to study its usage are
- Richard W. Schabacker (1930s)
- Edwards & Magee (1948)
- Peter Brandt
- Stacey Burke (more on the intraday side - typically our preference)
It's usage put plainly:
- Quantifying Accumulation or Distribution
- Revealing Energy Build-Up (Compression)
- Framing Breakouts and False Breakouts
- Structuring Time
- Identifying opportunities to trade a daily, weekly, or monthly range.
Volume Surprise [LuxAlgo]The Volume Surprise tool displays the trading volume alongside the expected volume at that time, allowing users to spot unexpected trading activity on the chart easily.
The tool includes an extrapolation of the estimated volume for future periods, allowing forecasting future trading activity.
🔶 USAGE
We define Volume Surprise as a situation where the actual trading volume deviates significantly from its expected value at a given time.
Being able to determine if trading activity is higher or lower than expected allows us to precisely gauge the interest of market participants in specific trends.
A histogram constructed from the difference between the volume and expected volume is provided to easily highlight the difference between the two and may be used as a standalone.
The tool can also help quantify the impact of specific market events, such as news about an instrument. For example, an important announcement leading to volume below expectations might be a sign of market participants underestimating the impact of the announcement.
Like in the example above, it is possible to observe cases where the volume significantly differs from the expected one, which might be interpreted as an anomaly leading to a correction.
🔹 Detecting Rare Trading Activity
Expected volume is defined as the mean (or median if we want to limit the impact of outliers) of the volume grouped at a specific point in time. This value depends on grouping volume based on periods, which can be user-defined.
However, it is possible to adjust the indicator to overestimate/underestimate expected volume, allowing for highlighting excessively high or low volume at specific times.
In order to do this, select "Percentiles" as the summary method, and change the percentiles value to a value that is close to 100 (overestimate expected volume) or to 0 (underestimate expected volume).
In the example above, we are only interested in detecting volume that is excessively high, we use the 95th percentile to do so, effectively highlighting when volume is higher than 95% of the volumes recorded at that time.
🔶 DETAILS
🔹 Choosing the Right Periods
Our expected volume value depends on grouping volume based on periods, which can be user-defined.
For example, if only the hourly period is selected, volumes are grouped by their respective hours. As such, to get the expected volume for the hour 7 PM, we collect and group the historical volumes that occurred at 7 PM and average them to get our expected value at that time.
Users are not limited to selecting a single period, and can group volume using a combination of all the available periods.
Do note that when on lower timeframes, only having higher periods will lead to less precise expected values. Enabling periods that are too low might prevent grouping. Finally, enabling a lot of periods will, on the other hand, lead to a lot of groups, preventing the ability to get effective expected values.
In order to avoid changing periods by navigating across multiple timeframes, an "Auto Selection" setting is provided.
🔹 Group Length
The length setting allows controlling the maximum size of a volume group. Using higher lengths will provide an expected value on more historical data, further highlighting recurring patterns.
🔹 Recommended Assets
Obtaining the expected volume for a specific period (time of the day, day of the week, quarter, etc) is most effective when on assets showing higher signs of periodicity in their trading activity.
This is visible on stocks, futures, and forex pairs, which tend to have a defined, recognizable interval with usually higher trading activity.
Assets such as cryptocurrencies will usually not have a clearly defined periodic trading activity, which lowers the validity of forecasts produced by the tool, as well as any conclusions originating from the volume to expected volume comparisons.
🔶 SETTINGS
Length: Maximum number of records in a volume group for a specific period. Older values are discarded.
Smooth: Period of a SMA used to smooth volume. The smoothing affects the expected value.
🔹 Periods
Auto Selection: Automatically choose a practical combination of periods based on the chart timeframe.
Custom periods can be used if disabling "Auto Selection". Available periods include:
- Minutes
- Hours
- Days (can be: Day of Week, Day of Month, Day of Year)
- Months
- Quarters
🔹 Summary
Method: Method used to obtain the expected value. Options include Mean (default) or Percentile.
Percentile: Percentile number used if "Method" is set to "Percentile". A value of 50 will effectively use a median for the expected value.
🔹 Forecast
Forecast Window: Number of bars ahead for which the expected volume is predicted.
Style: Style settings of the forecast.
VWAP Entry Assistant (v1.0)Description:
Anchored VWAP with a lightweight assistant for VWAP reversion trades.
It shows the distance to VWAP, an estimated hit probability for the current bar, the expected number of bars to reach VWAP, and a recommended entry price.
If the chance of touching VWAP is low, the script suggests an adjusted limit using a fraction of ATR.
The VWAP line is white by default, and a compact summary table appears at the bottom-left.
Educational tool. Not financial advice. Not affiliated with TradingView or any exchange. Always backtest before use.
Momentum-Based Fair Value Gaps [BackQuant]Momentum-Based Fair Value Gaps
A precision tool that detects Fair Value Gaps and color-codes each zone by momentum, so you can quickly tell which imbalances matter, which are likely to fill, and which may power continuation.
What is a Fair Value Gap
A Fair Value Gap is a 3-candle price imbalance that forms when the middle candle expands fast enough that it leaves a void between candle 1 and candle 3.
Bullish FVG : low > high . This marks a bullish imbalance left beneath price.
Bearish FVG : high < low . This marks a bearish imbalance left above price.
These zones often act as magnets for mean reversion or as fuel for trend continuation when price respects the gap boundary and runs.
Why add momentum
Not all gaps are equal. This script measures momentum with RSI on your chosen source and paints each FVG with a momentum heatmap. Strong-momentum gaps are more likely to hold or propel continuation. Weak-momentum gaps are more likely to fill.
Core Features
Auto FVG Detection with size filters in percent of price.
Momentum Heatmap per gap using RSI with smoothing. Multiple palettes: Gradient, Discrete, Simple, and scientific schemes like Viridis, Plasma, Inferno, Magma, Cividis, Turbo, Jet, plus Red-Green and Blue-White-Red.
Bull and Bear Modes with independent toggles.
Extend Until Filled : keep drawing live to the right until price fully fills the gap.
Auto Remove Filled for a clean chart.
Optional Labels showing the smoothed RSI value stored at the gap’s birth.
RSI-based Filters : only accept bullish gaps when RSI is oversold and bearish gaps when RSI is overbought.
Performance Controls : cap how many FVGs to keep on chart.
Alerts : new bullish or bearish FVG, filled FVG, and extreme RSI FVGs.
How it works
Source for Momentum : choose Returns, Close, or Volume.
Returns computes percent change over a short lookback to focus on impulse quality.
RSI and Smoothing : RSI length and a small SMA smooth the signal to stabilize the color coding.
Gap Scan : each bar checks for a 3-candle bullish or bearish imbalance that also clears your minimum size filter in percent of price.
Heatmap Color : the gap is painted at creation with a color from your palette based on the smoothed RSI value, preserving the momentum signature that formed it.
Lifecycle : if Extend Unfilled is on, the zone projects forward until price fully trades through the far edge. If Auto Remove is on, a filled gap is deleted immediately.
How to use it
Scan for structure : turn on both bullish and bearish FVGs. Start with a moderate Min FVG Size percent to reduce noise. You will see stacked clusters in trends and scattered singletons in chop.
Read the colors : brighter or stronger palette values imply stronger momentum at gap formation. Weakly colored gaps are lower conviction.
Decide bias : bullish FVGs below price suggest demand footprints. Bearish FVGs above price suggest supply footprints. Use the heatmap and RSI value to rank importance.
Choose your playbook :
Mean reversion : target partial or full fills of opposing FVGs that were created on weak momentum or that sit against higher timeframe context.
Trend continuation : look for price to respect the near edge of a strong-momentum FVG, then break away in the direction of the original impulse.
Manage risk : in continuation ideas, invalidation often sits beyond the opposite edge of the active FVG. In reversion ideas, invalidation sits beyond the gap that should attract price.
Two trade playbooks
Continuation - Buy the hold of a bullish FVG
Context uptrend.
A bullish FVG prints with strong RSI color.
Price revisits the top of the gap, holds, and rotates up. Enter on hold or first higher low inside or just above the gap.
Invalidation: below the gap bottom. Targets: prior swing, measured move, or next LV area.
Reversion - Fade a weak bearish FVG toward fill
Context range or fading trend.
A bearish FVG prints with weak RSI color near a completed move.
Price fails to accelerate lower and rotates back into the gap.
Enter toward mid-gap with confirmation.
Invalidation: above gap top. Target: opposite edge for a full fill, or the gap midline for partials.
Key settings
Max FVG Display : memory cap to keep charts fast. Try 30 to 60 on intraday.
Min FVG Size % : sets a quality floor. Start near 0.20 to 0.50 on liquid markets.
RSI Length and Smooth : 14 and 3 are balanced. Increase length for higher timeframe stability.
RSI Source :
Returns : most sensitive to true momentum bursts
Close : traditional.
Volume : uses raw volume impulses to judge footprint strength.
Filter by RSI Extremes : tighten rules so only the most stretched gaps print as signals.
Heatmap Style and Palette : pick a palette with good contrast for your background. Gradient for continuous feel, Discrete for quick zoning, Simple for binary, Palette for scientific schemes.
Extend Unfilled - Auto Remove : choose live projection and cleanup behavior to match your workflow.
Reading the chart
Bullish zones sit beneath price. Respect and hold of the upper boundary suggests demand. Strong green or warm palette tones indicate impulse quality.
Bearish zones sit above price. Respect and hold of the lower boundary suggests supply. Strong red or cool palette tones indicate impulse quality.
Stacking : multiple same-direction gaps stacked in a trend create ladders. Ladders often act as stepping stones for continuation.
Overlapping : opposing gaps overlapping in a small region usually mark a battle zone. Expect chop until one side is absorbed.
Workflow tips
Map higher timeframe trend first. Use lower timeframe FVGs for entries aligned with the higher timeframe bias.
Increase Min FVG Size percent and RSI length for noisy symbols.
Use labels when learning to correlate the RSI numbers with your palette colors.
Combine with VWAP or moving averages for confluence at FVG edges.
If you see repeated fills and refills of the same zone, treat that area as fair value and avoid chasing.
Alerts included
New Bullish FVG
New Bearish FVG
Bullish FVG Filled
Bearish FVG Filled
Extreme Oversold FVG - bullish
Extreme Overbought FVG - bearish
Practical defaults
RSI Length 14, Smooth 3, Source Returns.
Min FVG Size 0.25 percent on liquid majors.
Heatmap Style Gradient, Palette Viridis or Turbo for contrast.
Extend Unfilled on, Auto Remove on for a clean live map.
Notes
This tool does not predict the future. It maps imbalances and momentum so you can frame trades with clearer context, cleaner invalidation, and better ranking of which gaps matter. Use it with risk control and in combination with your broader process.
Institutional Orderflow Pro — VWAP, Delta, and Liquidity
Institutional Orderflow Pro is a next-generation order flow analysis indicator designed to help traders identify institutional participation, directional bias, and exhaustion zones in real time.
Unlike traditional volume-based indicators, it merges VWAP dynamics, cumulative delta, relative volume, and liquidity proximity into a single unified dashboard that updates tick-by-tick — without repainting.
The indicator is open-source, transparent, and educational. It aims to provide traders with a clearer read on who controls the market — buyers or sellers — and where liquidity lies.
The indicator combines multiple institutional-grade analytics into one framework:
RVOL (Relative Volume) = Compares current volume against the average of recent bars to identify strong institutional participation.
zΔ (Delta Z-Score) = Normalizes the buying/selling delta to reveal unusually aggressive market behavior.
CVDΔ (Cumulative Volume Delta Change) = Shows which side (buyers/sellers) is dominating this bar’s order flow.
VWAP Direction & Slope = Determines whether price is trading above/below VWAP and whether VWAP is trending or flat.
PD Distance (Prev Day Confluence) = Measures the current price’s distance from previous day’s high, low, close, and VWAP in ATR units — highlighting liquidity zones.
ABS/EXH Detection = Identifies institutional absorption and exhaustion patterns where momentum may reverse.
Bias Computation = Combines VWAP direction + slope to give a simplified regime signal: UP, DOWN, or FLAT.
All metrics are displayed through a color-coded, non-repainting HUD:
🟢 = bullish / favorable conditions
🔴 = bearish / weak conditions
⚫ = neutral / flat
🟡 = absorption (potential trap zone)
🟠 = exhaustion (momentum fading)
| Metric | Signal | Meaning |
| ---------------------- | ------- | ---------------------------------------------- |
| **RVOL ≥ 1.3** | 🟢 | High institutional activity — valid setup zone |
| **zΔ ≥ 1.2 / ≤ -1.2** | 🟢 / 🔴 | Unusual buy/sell aggression |
| **CVDΔ > 0** | 🟢 | Buyers dominate this bar |
| **VWAP dir ↑ / ↓** | 🟢 / 🔴 | Institutional bias long/short |
| **Slope ok = YES** | 🟢 | Trending market |
| **PD dist ≤ 0.35 ATR** | 🟢 | Near key liquidity zones |
| **Bias = UP/DOWN** | 🟢 / 🔴 | Trend-aligned environment |
| **ABS/EXH active** | 🟡 / 🟠 | Caution — possible reversal zone |
How to Use
Confirm Volume Context → RVOL > 1.2
Align with Bias → Take longs only when Bias = UP, shorts only when Bias = DOWN.
Check Slope and VWAP Dir → Ensure trending context (Slope = YES).
Confirm CVD and zΔ → Flow should agree with price direction.
Avoid ABS/EXH Triggers → These signal exhaustion or absorption by large players.
Enter Near PD Zones → Ideal trade zones are within 0.35 ATR of prior-day levels.
This multi-factor confirmation reduces noise and focuses only on high-probability institutional setups.
Originality
This script was written from scratch in Pine v6.
It does not reuse existing public indicators except for standard built-ins (ta.vwap, ta.atr, etc.).
The unique combination of delta z-scoring, VWAP slope filtering, and real-time confluence zones distinguishes it from typical orderflow tools or cumulative delta overlays.
The core innovation is its merged real-time HUD that integrates institutional metrics and natural-language feedback directly on the chart, allowing traders to read market context intuitively rather than decode multiple subplots.
Notes & Disclaimers
This indicator does not repaint.
It’s intended for educational and analytical purposes only — not as financial advice or a guaranteed signal system.
Works best on liquid instruments (Futures, Indices, FX majors).
Avoid non-standard chart types (Heikin Ashi, Renko, etc.) for accurate readings.
Open-source, modifiable, and compatible with Pine v6.
Recommended Use
Apply it with clean charts and standard candles for the best clarity.
Use alongside a basic structure or volume profile to contextualize institutional bias zones.
Author: Dhawal Ranka
Category - Orderflow / VWAP / Institutional Analysis
Version: Pine Script™ v6
License: Open Source (Educational Use)
Kalman Exponentialy Weighted Moving Average | MisinkoMasterThe Kalman Exponentialy Weighted Moving Average is a technical analysis tool providing users with more responsive and smoother signals, providing crystal-clear signals and giving investors valuable insights on market trends, however it could be used in many cases.
A deeper dive into the indicator:
When going through my creation of strategies, I had stumbled on an indicator called "EWMA", which worked decently, but it was far too simple in my opinion so I decided to combine the EMA & WMA, but with a little more complexity, and it has worked .
I began by learning how both MAs work, I already knew how WMA works, but EMA I did not.
After learning both I found out they were quite simple in principle and that there was a way to combine them in such way that you would get really good signals, however it was way too noisy.
While it could avoid major dumps that were not avoided by most indicators, it would lose that edge because of being too noisy.
After testing out many conditions, combinations & more, the best working one was this one:
WMA > KEWMA = long
WMA < KEWMA = short
I will explain this later, but this gave fast signals, and while it still was noisy it was better then before.
To smooth it out, I started testing price filters => Gaussian Filter and many more were tested out, but they either slowed it down to the point it was no longer of much use, or did not smooth it at all.
After testing the Kalman filter on this thing, I was shocked.
It was just right and made the indicator a lot better, smoothed it and kept most of the responsivness it had.
Now to the big question: "How is it calculated?"
Now first it needs to calculate the Kalman source, which smooths the source which will be used.
After that, we calculate the Weighted Moving Average for " n " period on the Kalman source.
Now that we have our WMA values, we need to calculate " a ".
a is calculated in the following formula:
a = 2/(1+ n )
where n is the user defined length
Now for the last part:
KEWMA = WMAyesterday * (1-a) + WMAtoday * a
This creates a very accurate and reactive indicator, that can prove useful in many uses, beyond those I will and did talk about.
For the trend logic as mentioned before:
Long = WMA > KEWMA
Short = WMA < KEWMA
This worked best, but you might find better ways of using it.
I think that is all I have to say about it, I left it open source so you can all code it in your strategies and play around with it.
Enjoy Gs!
TT ToniTrading Adjustable Price Fee Band [%]Simple but perfectly functional indicator with Trading fee bands.
Crypto Trading is with fees and very small trades often don't make sense due to the fees we need to pay. With this band you can visualize your fees before entering a trade and take smarter decisions for tight daytrading and scalping.
You type in the fee for just one trade, the Taker Fee for a Market Order. The bands show the fees in % times 2, so what you will pay for opening and closing the trade in reality. The band therefore shows the real break-even point, with included payed fees.
It additionally helps taking trading decisions or not with very small trades (Scalping).
You can smooth the bands if you want and you can addtionally show the true datapoints if you prefer smoothend bands. I recommend no bigger smoothing than 2, if you don't want to show the datapoints. Additionally you can fill the band, and of course adjust transperency, colour and all the general TradingView stuff.
Fee Overview in the current market for the indicator input field:
BingX with 10% fee reduction code = 0,045 %
BingX: Normal = 0,050 %
Bitget, ByBit, BitUnix, Blofin, Phemex: Normal = 0,060 %
Bitget, ByBit, BitUnix, Blofin, Phemex: with 20% fee reduction code = 0,048 %
Have fun Trading, Happy Profits!
Greetings
ToniTrading
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Bollinger Band Screener [Pineify]Multi-Symbol Bollinger Band Screener Pineify – Advanced Multi-Timeframe Market Analysis
Unlock the power of rapid, multi-asset scanning with this original TradingView Pine Script. Expose trends, volatility, and reversals across your favorite tickers—all in a single, customizable dashboard.
Key Features
Screens up to 8 symbols simultaneously with individual controls.
Covers 4 distinct timeframes per symbol for robust, multi-timeframe analysis.
Integrates advanced Bollinger Band logic, adaptable with 11+ moving average types (SMA, EMA, RMA, HMA, WMA, VWMA, TMA, VAR, WWMA, ZLEMA, and TSF).
Visualizes precise state changes: Open/Parallel Uptrends & Downtrends, Consolidation, Breakouts, and more.
Highly interactive table view for instant signal interpretation and actionable alerts.
Flexible to any market: crypto, stocks, forex, indices, and commodities.
How It Works
For each chosen symbol and timeframe, the script calculates Bollinger Bands using your specified source, length, standard deviation, and moving average method.
Real-time state recognition assigns one of several states (Open Rising, Open Falling, Parallel Rising, Parallel Falling), painting the table with unique color codes.
State detection is rigorously defined: e.g., “Open Rising” is set when both bands and the basis rise, indicating strong up momentum.
All bands, signals, and strategies dynamically update as new bars print or user inputs change.
Trading Ideas and Insights
Identify volatility expansions and compressions instantly, spotting breakouts and breakdowns before they play out.
Spot multi-timeframe confluences—when trends align across several TFs, conviction increases for potential trades.
Trade reversals or continuations based on unique Bollinger Band patterns, such as squeeze-break or persistent parallel moves.
Harness this tool for scalping, swing trading, or systematic portfolio screens—your logic, your edge!
How Multiple Indicators Work Together
This screener’s core strength is its integration of multiple moving average types into Bollinger Band construction, not just standard SMA. Each average adapts the bands’ responsiveness to trend and noise, so traders can select the underlying logic that matches their market environment (e.g., HMA for fast moves or ZLEMA for smoothed lag). Overlaying 4 timeframes per symbol ensures trends, reversals, and volatility shifts never slip past your radar. When all MAs and bands synchronize across symbols and TFs, it becomes easy to separate real opportunity from market noise.
Unique Aspects
Perhaps the most flexible Bollinger Band screener for TradingView—choose from over 10 moving average methods.
Powerful multi-timeframe and multi-asset design, rare among Pine scripts.
Immediate visual clarity with color-coded table cells indicating band state—no need for guesswork or chart clutter.
Custom configuration for each asset and time slice to suit any trading style.
How to Use
Add the script to your TradingView chart.
Use the user-friendly input settings to specify up to 8 symbols and 4 timeframes each.
Customize the Bollinger Band parameters: source (price type), band length, standard deviation, and type of moving average.
Interpret the dashboard: Color codes and “state” abbreviations show you instantly which symbols and timeframes are trending, consolidating, or breaking out.
Take trades according to your strategy, using the screener as a confirmation or primary scan tool.
Customization
Fully customize: symbols, timeframes, source, band length, standard deviation multiplier, and moving average type.
Supports intricate watchlists—anything TradingView allows, this script tracks.
Adapt for cryptos, equities, forex, or derivatives by changing symbol inputs.
Conclusion
The Multi-Symbol Bollinger Band Screener “Pineify” is a comprehensive, SEO-optimized Pine Script tool to supercharge your market scanning, trend spotting, and decision-making on TradingView. Whether you trade crypto, stocks, or forex—its fast, intuitive, multi-timeframe dashboard gives you the informational edge to stay ahead of the market.
Try it now to streamline your trading workflow and see all the bands, all the trends, all the time!
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend
A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model.
Original Script Link
This indicator is built on top of my volume sampling engine. See the base implementation here:
Why Volume Sampling
Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals.
Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally:
filters dead time by skipping low volume chop;
standardizes the information content per bar, improving comparability across regimes;
stabilizes volatility estimates used inside banded indicators;
gives trend and breakout logic cleaner state transitions with fewer micro flips.
What this tool does
It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock.
Core Features
Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user.
Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles.
Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars.
Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme.
Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats.
Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series.
How it works
Sampling
Pick Sampling Method = Volume or Dollar Bars.
Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant.
The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation.
Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic.
Supertrend on the sampled stream
Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle.
Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR .
Apply classic trailing band and direction rules to produce Supertrend and trend state.
Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints.
Reading the display
Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls.
Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1.
Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles.
Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop.
Settings you will use most
Data Settings
Sampling Method - Volume or Dollar Bars.
Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother.
Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes.
Max Stored Samples - Ring buffer limit for performance.
Indicator Settings
SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout.
Supertrend Source - Price field from the synthetic candle.
ATR Period and Factor - Standard Supertrend controls applied on the synthetic series.
Visuals and UI
Show Synthetic Bars - Turn synthetic candles on or off.
Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive.
Mark new samples - Puts a dot when a bucket closes.
Show Time Bars - Overlay regular candles for comparison.
Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction.
Line Width , Colors , and Stats Table toggles.
Some workflow notes:
Trend Following
Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples.
Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars.
Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries.
Breakout and Continuation
Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend.
The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts.
Mean Reversion
In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens.
Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting.
Stats table (top right)
Method and Total Samples - Sampling regime and current synthetic history length.
Current Vol or Dollar and Threshold - Live bucket fill versus the trigger.
Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress.
Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes.
Why this reduces noise
Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs.
Notes and tips
Use Dollar Bars on assets where nominal price varies widely over time or across symbols.
Median filter can resist single burst outliers when setting dynamic thresholds.
If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests.
Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching.
Link again for reference
Original Volume Based Sampling engine:
Bottom line
When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Multiple Symbol Trend Screener [Pineify]Multiple Symbol Trend Screener Pineify – Ultimate Multi-Indicator Scanner for TradingView
Empower your trading with deep market insights across multiple symbols using this feature-rich Pine Script screener. The Multiple Symbol Trend Screener Pineify enables traders to monitor and compare trends, reversals, and consolidations in real-time across the biggest equity symbols on TradingView, through a synergistic blend of popular technical indicators.
Key Features
Monitor up to 15 symbols and their trends simultaneously
Integrates 7 professional-grade indicators: MA Distance, Aroon, Parabolic SAR (PSAR), ADX, Supertrend, Keltner Channel, and BBTrend
Color-coded table display for instant visual assessment
Customizable lookback periods, indicator types, and calculation methods
SEO optimized for multi-symbol trend detection, screener, and advanced TradingView indicator
How It Works
This indicator leverages TradingView’s Pine Script v6 and request.security() to process multiple symbols across selected timeframes. Data populates a dynamic table, updating each cell based on the calculated value of every underlying indicator. MA Distance highlights deviation from moving averages; Aroon flags emerging trend strength; PSAR marks potential trend reversals; ADX assesses trend momentum; Supertrend detects bullish/bearish phases; Keltner Channel and BBTrend offer volatility and power insights.
Set up your preferred symbols and timeframes
Each indicator runs its calculation per symbol using its parameter group
All results are displayed in a table for a comprehensive dashboard view
Trading Ideas and Insights
Traders can use this screener for cross-market comparison, directional bias, entry/exit filtering, and comprehensive trend evaluation. The screener is excellent for swing trading, day trading, and portfolio tracking. It enables confirmation across multiple frameworks — for example, spotting momentum with ADX before confirming direction with Supertrend and PSAR.
Identify correlated movements or divergences across selected assets
Spot synchronized trend changes for basket trading ideas
Filter symbols by volatility, strength, or trend status for precise trade selection
How Multiple Indicators Work Together
The screener’s edge lies in its intelligent correlation of popular indicators. MA Distance measures the proximity to chosen moving averages, ideal for spotting overbought/oversold conditions. Aroon reveals the strength of new price trends, PSAR indicates reversal signals, and ADX quantifies the momentum of these trends. Supertrend provides a directional phase, while Keltner Channel & BBTrend analyze volatility shifts and band compressions. This amalgamation allows for a robust, multi-dimensional market snapshot, capturing details missed by single-indicator tools.
By displaying all key metrics side-by-side, the screener enables holistic decision-making, revealing confluence zones and contradiction areas across multiple tickers and timeframes.
Unique Aspects
Original implementation combining seven independent trend and momentum indicators for each symbol
Rich customization for symbols, timeframes, and all indicator parameters
Intuitive color-coding for quick reading of bullish/bearish/neutral signals
Comprehensive dashboard for instant actionable insights
How to Use
Load the indicator onto your TradingView chart
Go to the script’s settings and input your preferred symbols and relevant timeframes
Set your desired parameters for each indicator group: Moving Average type, Aroon length, PSAR values, ADX smoothing, etc.
Observe the results in the top-right table, then use it to filter candidates and validate trade setups
The screener is suitable for all timeframes and asset classes available on TradingView. Make sure your chart’s timeframe matches the one used in the scanner for optimal accuracy.
Customization
Choose up to 15 symbols to monitor in a single dashboard
Customize lookback periods, indicator types, colors, and display settings
Configure alerting options and thresholds for advanced trade automation
Conclusion
The Multiple Symbol Trend Screener Pineify sets a new standard for multi-asset screening on TradingView. By elegantly merging seven proven technical indicators, the screener delivers powerful trend detection, reversal analysis, and volatility monitoring — all in one dashboard. Take your trading to new heights with in-depth, customizable market surveillance.
Whale Breaker — HTF Order Blocks + Market Structure HUDWhale Breaker (Debug Edition) is an advanced Smart Money Concept (SMC) tool designed to project High Timeframe (HTF) order blocks onto your Lower Timeframe (LTF) charts while tracking market structure breaks (BOS / CHoCH).
This debug build adds extra transparency: the mini-HUD not only shows HTF trend, last signal, and active order blocks, but also explains why no new block was created (e.g. no HTF BOS, body not found, ATR filter too strict, max-per-side limit). This makes it easier to fine-tune your settings and understand the logic behind the indicator.
Key features:
- HTF order blocks (e.g. 1h) projected into LTF charts (e.g. 15m)
- Automatic right-extension until mitigation (MB)
- Mitigation detection: blocks shaded once filled
- ATR filter to remove insignificant micro-zones
- Per-side cap: limit the maximum active BU/B blocks
- Lookback-based pruning for clean charts
- BOS/CHoCH arrows on chart (▲ green = bullish, ▼ red = bearish)
- Compact HUD with trend, last signal, active OBs, legend, and debug reasons
Usage:
- Define your HTF (e.g. 1h) and trade entries on the LTF (e.g. 15m).
- Wait for a BOS in HTF direction, then target the projected order block.
- Stop Loss just beyond the OB, Take Profit at next opposite OB or using a fixed RRR.
Note: This is a debugging/educational version to understand order block creation logic.
For live trading, consider using the standard Whale Breaker.
VWAP Deviation Oscillator [BackQuant]VWAP Deviation Oscillator
Introduction
The VWAP Deviation Oscillator turns VWAP context into a clean, tradeable oscillator that works across assets and sessions. It adapts to your workflow with four VWAP regimes plus two rolling modes, and three deviation metrics: Percent, Absolute, and Z-Score. Colored zones, optional standard deviation rails, and flexible plot styles make it fast to read for both trend following and mean reversion.
What it does
This tool measures how far price is from a chosen VWAP and expresses that gap as an oscillator. You can view the deviation as raw price units, percent, or standardized Z-Score. The plot can be a histogram or a line with optional fills and sigma bands, so you can quickly spot polarity shifts, overbought and oversold conditions, and strength of extension.
VWAP modes track a session VWAP that resets (4H, Daily, Weekly) or a rolling VWAP that updates continuously over a fixed number of bars or days.
Deviation modes let you choose the lens: Percent, Absolute, or Z-Score. Each highlights different aspects of stretch and mean pressure.
Visual encoding uses a 10-zone color palette to grade the magnitude of deviation on both sides of zero.
Volatility guards compute mode-specific sigma so thresholds are stable even when volatility compresses.
Why this works
VWAP is a high signal anchor used by institutions to gauge fair participation. Deviations around VWAP cluster in regimes: mild oscillations within a band, decisive pushes that signal imbalance, and standardized extremes that often precede either continuation or snapback. Expressing that distance as a single time series adds clarity: bias is the oscillator’s sign, risk context is its magnitude, and regime is the way it behaves around sigma lines.
How to use it
Trend following
Favor the side of the zero line. Bullish when the oscillator is above zero and making higher swing highs. Bearish when below zero and making lower swing lows. Use +1 sigma and +2 sigma in your mode as strength tiers. Pullbacks that hold above zero in uptrends, or below zero in downtrends, are often continuation entries.
Mean reversion
Fade stretched readings when structure supports it. Look for tests of +2 sigma to +3 sigma that fail to progress and roll back toward zero, or the mirror on the downside. Z-Score mode is best when you want standardized gates across assets. Percent mode is intuitive for intraday scalps where a given percent stretch tends to mean revert.
Session playbook
Use Daily or Weekly VWAP for intraday or swing context. Rolling modes help when the asset lacks clean session boundaries or when you want a continuous anchor that adapts to liquidity shifts.
Key settings
VWAP computation
VWAP Mode = 4 Hours, Daily, Weekly, Rolling (Bars), Rolling (Days). Session modes reset the VWAP when a new session begins. Rolling modes compute VWAP over a fixed trailing window.
Rolling (Lookback: Bars) controls the trailing bar count when using Rolling (Bars).
Rolling (Lookback: Days) converts days to bars at runtime and uses that trailing span.
Use Close instead of HLC3 switches the price reference. HLC3 is smoother. Close makes the anchor track settlement more tightly.
Deviation measurement
Deviation Mode
Percent : 100 * (Price / VWAP - 1). Good for uniform scaling across instruments.
Absolute : Price - VWAP. Good when price units themselves matter.
Z-Score : Standardizes the absolute residual by its own mean and standard deviation over Z/Std Window . Ideal for cross-asset comparability and regime studies.
Z/Std Window sets the mean and standard deviation window for Z-Score mode.
Volatility controls
Percent Mode Volatility Lookback estimates sigma for percent deviations.
Absolute Mode Volatility Lookback estimates sigma for absolute deviations.
Minimum Sigma Guard (pct pts) prevents the percent sigma from collapsing to near zero in extremely quiet markets.
Visualization
Plot Type = Histogram or Line. Histogram emphasizes impulse and polarity changes. Line emphasizes trend waves and divergences.
Positive Color / Negative Color define the palette for line mode. Histogram uses a 10-bucket gradient automatically.
Show Standard Deviations plots symmetric rails at ±1, ±2, ±3 sigma in the current mode’s units.
Fill Line Oscillator and Fill Opacity add a soft bias band around zero for line mode.
Line Width affects both the oscillator and the sigma rails.
Reading the zones
The oscillator’s color and height map deviation to nine graded buckets on each side of zero, with deeper greens above and deeper reds below. In Percent and Absolute modes, those buckets are scaled by their mode-specific sigma. In Z-Score mode the bucket edges are fixed at 0.5, 1.0, 2.0, and 2.8.
0 to +1 sigma weak positive bias, usually rotational.
+1 to +2 sigma constructive impulse. Pullbacks that hold above zero often continue.
+2 to +3 sigma strong expansion. Watch for either trend continuation or exhaustion tells.
Beyond +3 sigma statistical extreme. Requires structure to avoid fading too soon.
Mirror logic applies on the negative side.
Suggested workflows
Trend continuation checklist
Pick a session VWAP that matches your timeframe, for example Daily for intraday or Weekly for position trades.
Wait for the oscillator to hold the correct side of zero and for a sequence of higher swing lows in the oscillator (uptrend) or lower swing highs (downtrend).
Buy pullbacks that stabilize between zero and +1 sigma in an uptrend. Sell rallies that stabilize between zero and -1 sigma in a downtrend.
Use the next sigma band or a prior price swing as your target reference.
Mean reversion checklist
Switch to Z-Score mode for standardized thresholds.
Identify tests of ±2 sigma to ±3 sigma that fail to extend while price meets support or resistance.
Enter on a polarity change through the prior histogram bar or a small hook in line mode.
Fade back to zero or to the opposite inner band, then reassess.
Notes on the three modes
Percent is easy to reason about when you care about proportional stretch. It is well suited to intraday and multi-asset dashboards.
Absolute tracks cash distance from VWAP. This is useful when instruments have tight ticks and you plan risk in price units.
Z-Score standardizes the residual and is best for quant studies, cross-asset comparisons, and threshold research that must be scale invariant.
What the alerts can tell you
Polarity changes at zero can mark the start or end of a leg.
Crosses of ±1 sigma identify overbought or oversold in the current mode’s units.
Zone changes signal an upgrade or downgrade in deviation strength.
Troubleshooting and edge cases
If your instrument has long flat periods, keep Minimum Sigma Guard above zero in Percent mode so the rails do not vanish.
In Rolling modes, very short windows will respond quickly but can whip around. Session modes smooth this by resetting at well known boundaries.
If Z-Score looks erratic, increase Z/Std Window to stabilize the estimate of mean and sigma for the residual.
Final thoughts
VWAP is the anchor. The deviation oscillator is the narrative. By separating bias, magnitude, and regime into a simple stream you can execute faster and review cleaner. Pick the VWAP mode that matches your horizon, choose the deviation lens that matches your risk framework, and let the color graded zones guide your decisions.
TTM Squeeze Screener [Pineify]TTM Squeeze Screener for Multiple Crypto Assets and Timeframes
This advanced TradingView Pine script, TTM Squeeze Screener, helps traders scan multiple crypto symbols and timeframes simultaneously, unlocking new dimensions in momentum and volatility analysis.
Key Features
Screen up to 8 crypto symbols across 4 different timeframes in one pane
TTM Squeeze indicator detects volatility contraction and expansion (“squeeze”) phases
Momentum filter reveals potential breakout direction and strength
Visual screener table for intuitive multi-asset monitoring
Fully customizable for symbols and timeframes
How It Works
The heart of this screener is the TTM Squeeze algorithm—a hybrid volatility and momentum indicator leveraging Bollinger Bands, Keltner Channels, and linear momentum analysis. The script checks whether Bollinger Bands are “squeezed” inside Keltner Channels, flagging periods of low volatility primed for expansion. Once a squeeze is released, the included momentum calculation suggests the likely breakout direction.
For each selected symbol and timeframe, the screener runs the TTM Squeeze logic, outputs “SQUEEZE” or “NO SQZ”, and tags momentum values. A table layout organizes the results, allowing rapid pattern recognition across symbols.
Trading Ideas and Insights
Spot multi-symbol volatility clusters—ideal for finding synchronized market moves
Assess breakout potential and direction before entering trades
Scalping and swing trading decisions are enhanced by cross-timeframe momentum filtering
Portfolio managers can quickly identify which assets are about to move
How Multiple Indicators Work Together
This screener unites three essential concepts:
Bollinger Bands : Measure volatility using standard deviation of price
Keltner Channels : Define expected price range based on average true range (ATR)
Momentum : Linear regression calculation to evaluate the direction and intensity after a squeeze
By combining these, the indicator not only signals when volatility compresses and releases, but also adds directional context—filtering false signals and helping traders time entries and exits more precisely.
Unique Aspects
Multi-symbol, multi-timeframe architecture—optimized for crypto traders and market scanners
Advanced table visualization—see all signals at a glance, minimizing cognitive overload
Modular calculation functions—easy to adapt and extend for other asset classes or strategies
Real-time, low-latency screening—built for actionable alerts on fast-moving markets
How to Use
Add the script to a TradingView chart (works on custom layouts)
Select up to 8 symbols and 4 timeframes using input fields (defaults to BTCUSD, ETHUSD, etc.)
Monitor the screener table; “SQUEEZE” highlights assets in potential breakout phase
Use momentum values to judge if the squeeze is likely bullish or bearish
Combine screener insights with manual chart analysis for optimal results
Customization
Symbols: Easily set any ticker for deep market scanning
Timeframes: Adjust to match your trading horizon (scalping, swing, long-term)
Indicator parameters: Refine Bollinger/Keltner/Momentum settings for sensitivity
Visuals: Personalize table layout, color codes, and formatting for clarity
Conclusion
In summary, the TTM Squeeze Screener is a robust, original TradingView indicator designed for crypto traders who demand a sophisticated multi-symbol, multi-timeframe edge. Its combination of volatility and momentum analytics makes it ideal for catching explosive breakouts, managing risk, and scanning the market efficiently. Whether you’re a scalper or swing trader, this screener provides the insights needed to stay ahead of the curve.
Seasonal Pattern DecoderSeasonal Pattern Decoder
The Seasonal Pattern Decoder is a powerful tool designed for traders and analysts who want to uncover and leverage seasonal tendencies in financial markets. Instead of cluttering your chart with complex visuals, this indicator presents a clean, intuitive table that summarizes historical monthly performance, allowing you to spot recurring patterns at a glance.
How It Works
The indicator fetches historical monthly data for any symbol and calculates the percentage return for each month over a specified number of years. It then organizes this data into a comprehensive table, providing a clear, year-by-year and month-by-month breakdown of performance.
Key Features
Historical Performance Table: Displays monthly returns for up to a user-defined number of years, making it easy to compare performance across different periods.
Color-Coded Heatmap: Each cell is colored based on the performance of the month. Strong positive returns are shaded in green, while strong negative returns are shaded in red, allowing for immediate visual analysis of monthly strength or weakness.
Annual Summary: A "Σ" column shows the total percentage return for each full calendar year.
AVG Row: Calculates and displays the average return for each month across all the years shown in the table.
WR Row: Shows the "Win Rate" for each month, which is the percentage of time that month had a positive return. This is crucial for identifying high-probability seasonal trends.
How to Use
Add the "Seasonal Pattern Decoder" indicator to your chart. Note that it works best on Daily, Weekly, or Monthly timeframes. A warning message will be displayed on intraday charts.
In the indicator settings, adjust the "Lookback Period" to control how many years of historical data you want to analyze.
Use the "Show Years Descending" option to sort the table from the most recent year to the oldest.
The "Heat Range" setting allows you to adjust the sensitivity of the color-coding to fit the volatility of the asset you are analyzing.
This tool is ideal for confirming trading biases, developing seasonal strategies, or simply gaining a deeper understanding of an asset's typical behavior throughout the year.
## Disclaimer
This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management.
Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
Volume Percentile Supertrend [BackQuant]Volume Percentile Supertrend
A volatility and participation aware Supertrend that automatically widens or tightens its bands based on where current volume sits inside its recent distribution. The goal is simple: fewer whipsaws when activity surges, faster reaction when the tape is quiet.
What it does
Calculates a standard Supertrend framework from an ATR on a volume weighted price source.
Measures current volume against its recent percentile and converts that context into a dynamic ATR multiplier.
Widens bands when volume is unusually high to reduce chop. Tightens bands when volume is unusually low to catch turns earlier.
Paints candles, draws the active Supertrend line and optional bands, and prints clear Long and Short signal markers.
Why volume percentile
Fixed ATR multipliers assume all bars are equal. They are not. When participation spikes, price swings expand and a static band gets sliced.
Percentiles place the current bar inside a recent distribution. If volume is in the top slice, the Supertrend allows more room. If volume is in the bottom slice, it expects smaller noise and tightens.
This keeps the same playbook usable across busy sessions and sleepy ones without constant manual retuning.
How it works
Volume distribution - A rolling window computes the Pth percentile of volume. Above that is flagged as high volume. A lower reference percentile marks quiet bars.
Dynamic multiplier - Start from a Base Multiplier. If bar is high volume, scale it up by a function of volume-to-average and a Sensitivity knob. If bar is low volume, scale it down. Smooth the result with an EMA to avoid jitter.
VWMA source - The price input for bands is a short volume weighted moving average of close. Heavy prints matter more.
ATR envelope - Compute ATR on your length. UpperBasic = VWMA + Multiplier x ATR. LowerBasic = VWMA - Multiplier x ATR.
Trailing logic - The final lines trail price so they only move in a direction that preserves Supertrend behavior. This prevents sudden flips from transient pokes.
Direction and signals - Direction flips when price crosses through the relevant trailing line. SupertrendLong and SupertrendShort mark those flips. The plotted Supertrend is the active trailing side.
Inputs and what they change
Volume Lookback - Window for percentile and average. Larger window = stabler percentile, smaller = snappier.
Volume Percentile Level - Threshold that defines high volume. Example 70 means top 30 percent of recent bars are treated as high activity.
Volume Sensitivity - Gain from volume ratio to the dynamic multiplier. Higher = bands expand more when volume spikes.
VWMA Source Length - Smoothing of the volume weighted price source for the bands.
ATR Length - Standard ATR window. Larger = slower, smaller = quicker.
Base Multiplier - Core band width before volume adjustment. Think of this as your neutral volatility setting.
Multiplier Smoothing - EMA on the dynamic multiplier. Reduces back and forth changes when volume oscillates around the threshold.
Show Supertrend on chart - Toggles the active line.
Show Upper Lower Bands - Draws both sides even when inactive. Good for context.
Paint candles according to Trend - Colors bars by trend direction.
Show Long and Short Signals - Prints 𝕃 and 𝕊 markers at flips.
Colors - Choose your long and short palette.
Reading the plot
Supertrend line - Thick line that hugs price from above in downtrends and from below in uptrends. Its distance breathes with volume.
Bands - Optional upper and lower rails. Useful to see the inactive side and judge how wide the envelope is right now.
Signals - 𝕃 prints when the trend flips long. 𝕊 prints when the trend flips short.
Candle colors - Quick bias read at a glance when painting is enabled.
Typical workflows
Trend following - Use 𝕃 flips to initiate longs and ride while bars remain colored long and price respects the lower trailing line. Mirror for shorts with 𝕊 and the upper trailing line. During high volume phases the line will give more room, which helps stay in the move.
Pullback adds - In an established trend, shallow tags toward the active line after a high volume expansion can be add points. The dynamic envelope adjusts to the session so your add distance is not fixed to a stale volatility regime.
Mean reversion filter - In quiet tape the multiplier contracts and flips come earlier. If you prefer fading, watch for quick toggles around the bands when volume percentile remains low. In high volume, avoid fading into the widened line unless you have other strong reasons.
Notes on behavior
High volume bar: the percentile gate opens, volRatio > 1 powers up the multiplier through the Sensitivity lever, bands widen, fewer false flips.
Low volume bar: multiplier contracts, bands tighten, flips can happen earlier which is useful when you want to catch regime changes in quiet conditions.
Smoothing matters: both the price source (VWMA) and the multiplier are smoothed to keep structure readable while still adapting.
Quick checklist
If you see frequent chop and today feels busy: check that volume is above your percentile. Wider bands are expected. Consider letting the trend prove itself against the expanded line before acting.
If everything feels slow and you want earlier entries: percentile likely marks low volume, so bands tighten and 𝕃 or 𝕊 can appear sooner.
If you want more or fewer flips overall: adjust Base Multiplier first. If you want more reaction specifically tied to volume surges: raise Volume Sensitivity. If the envelope breathes too fast: raise Multiplier Smoothing.
What the signals mean
SupertrendLong - Direction changed from non-long to long. 𝕃 marker prints. The active line switches to support below price.
SupertrendShort - Direction changed from non-short to short. 𝕊 marker prints. The active line switches to resistance above price.
Trend color - Bars painted long or short help validate context for entries and management.
Summary
Volume Percentile Supertrend adapts the classic Supertrend to the day you are trading. Volume percentile sets the mood, sensitivity translates it into dynamic band width, and smoothing keeps it clean. The result is a single plot that aims to stay conservative when the tape is loud and act decisively when it is quiet, without you having to constantly retune settings.
Opening Candle Zone with ATR Bands by nkChartsThis indicator highlights the opening range of each trading session and projects dynamic ATR-based zones around it.
Key Features
Plots high and low levels of the opening candle for each new daily session.
Extends these levels across the session, providing clear intraday support and resistance zones.
Adds ATR-based offset bands above and below the opening range for volatility-adjusted levels.
Customizable colors, ATR length, and multiplier for flexible use across markets and timeframes.
Adjustable session history limit to control how many past levels remain on the chart.
How to Use:
The opening range high/low often acts as strong intraday support or resistance.
The ATR bands give an adaptive volatility buffer, useful for breakout or mean-reversion strategies.
Works on any market with clear session opens.
This tool is designed for traders who want to combine session-based price action with volatility insights, helping identify potential breakouts, reversals, or consolidation areas throughout the day.
⚠️ Disclaimer: This indicator is for educational purposes only. It does not provide financial advice or guarantee profits. Always perform your own analysis before making trading decisions.
Z-Score Trend Channels [BackQuant]Z-Score Trend Channels
A self-contained price-statistics framework that turns a rolling z-score into price channels, bias states, and trade markers. Run either trend-following or mean-reversion from the same tool with clear, on-chart context.
What it is
A rolling statistical map that measures how far price is from its recent average in standard-deviation units (z-score).
Adaptive channels drawn in price space from fixed z thresholds, so the rails breathe with volatility.
A simple trend proxy from z-score momentum to separate trending from ranging conditions.
On-chart signals for pullback entries, stretched extremes, and practical exits.
Core idea (plain English math)
Rolling mean and volatility - Over a lookback you get the average price and its standard deviation.
Z-score - How many standard deviations the current price is above or below its average: z = (price - mean) / stdev. z near 0 means near average; positive is above; negative is below.
Noise control - An EMA smooths the raw z to reduce jitter and false flickers.
Channels back in price - Fixed z levels are converted back to price to form the upper, lower, and extreme rails.
Trend proxy - A smoothed change in z is used as a lightweight trend-strength line. Positive strength with positive z favors uptrend; negative strength with negative z favors downtrend.
What you see on the chart
Channels and fills - Mean, upper, lower, and optional extreme lines. The area mean->upper tints with the bearish color, mean->lower tints with the bullish color.
Background tint (optional) - Soft green, red, or neutral based on detected trend state.
Signals - Bullish Entry (triangle up) when z exits the oversold zone upward; Bearish Entry (triangle down) when z exits the overbought zone downward; Extreme markers (diamonds) at the extreme bands with a one-bar turn.
Table - Current z, trend state, trend strength, distance to bands, market state tag, and a quick volatility regime label.
Edge labels - MEAN, OB, and OS labels slightly projected forward with level values.
Inputs you will actually use
Z-Score Period - Lookback for mean and stdev. Larger = slower and steadier rails, smaller = more reactive.
Smoothing Period - EMA on z. Lower = earlier but choppier flips; higher = later but cleaner.
Price Source - Default hlc3. Choose close if you prefer session-close logic.
Upper and Lower Thresholds - Default around +2.0 and -2.0. Tighten for more signals, widen for fewer and stronger.
Extreme Upper and Lower - Deeper stretch guards, e.g., +/- 2.5.
Strength Period - EMA on z momentum. Sets how fast the trend proxy flips.
Trend Threshold - Minimum absolute z to accept a directional bias.
Visual toggles - Channels, signals, background tint, stats table, colors, and optional last-bar trend label.
How to use it: trend-following playbook
Read the state - Uptrend when z > Trend Threshold and trend strength > 0. Downtrend when z < -Trend Threshold and trend strength < 0. Neutral otherwise.
Entries - In an uptrend, prefer Bullish Entry signals that fire near the lower channel. In a downtrend, prefer Bearish Entry signals that fire near the upper channel.
Stops - Conservative: beyond the extreme channel on your side. Tighter: just outside the standard band that framed the signal.
Exits - For longs, exit or trim on a cross back through z = 0 or a clean tag of the upper threshold. For shorts, mirror with z = 0 up-cross or tag of the lower threshold. You can also reduce if trend strength flips against you.
Adds - In strong trends, additional signals near your side’s band can be add points. Avoid adding once z hovers near the opposite band for several bars.
How to use it: mean-reversion playbook
Find stretch - Standard reversions: Bullish Entry when z leaves the oversold zone upward; Bearish Entry when z leaves the overbought zone downward. Aggressive reversions: Extreme markers at extreme bands with a one-bar turn.
Entries - Take the signal as price exits the zone. Prefer setups where trend strength is near zero or tilting against the prior push.
Targets - First target is the mean line. A runner can aim for the opposite standard channel if momentum keeps flipping.
Stops - Outside the extreme band beyond your entry. If fading without extremes, place risk just beyond the opposite standard band.
Filters - Optional: skip counter-trend fades against a very strong trend state unless your risk is tight and predefined.
Reading the stats table
Current Z-Score - Magnitude and sign of displacement now.
Trend State - Uptrend, Downtrend, or Ranging.
Trend Strength - Smoothed z momentum. Higher absolute values imply stronger directional conviction.
Distance to Upper/Lower - Percent distance from price to each band, useful for sizing targets or judging room left.
Market State - Overbought, Oversold, Extreme OB, Extreme OS, or Normal.
Volatility Regime - High, Normal, or Low relative to recent distribution. Expect bands to widen in High and tighten in Low.
Parameter guidance (conceptual)
Z-Score Period - Choose longer for a structural mean, shorter for a reactive mean.
Smoothing Period - Lower for earlier but noisier reads; higher for slower but steadier reads.
Thresholds - Start around +/- 2.0. Tighten for scalping or quiet ranges. Widen for noisy or fast markets.
Trend Threshold and Strength Period - Raise to avoid weak, transient bias. Lower to capture earlier regime shifts.
Practical examples
Trend pullback long - State shows Uptrend. Price tests the lower channel; z dips near or below the lower threshold; a Bullish Entry prints. Stop just below extreme lower; first target mean; keep a runner if trend strength stays positive.
Mean-revert short - State is Ranging. z tags the extreme upper, an Extreme Bearish marker prints, then a Bearish Entry prints on the leave. Stop above extreme upper; target the mean; consider a runner toward the lower channel if strength turns negative.
Potential Questions you might have
Why z-score instead of fixed offsets - Because the bands adapt with volatility. When the tape gets quiet the rails tighten, when it runs hot the rails expand. Your entries stay normalized.
Do I need both modes - No. Many users run only trend pullbacks or only mean-reversions. The tool lets you toggle what you need and keep the chart readable.
Multi-timeframe workflow - A common approach is to set bias from a higher timeframe’s trend state and execute on a lower timeframe’s signals that align with it.
Summary
Z-Score Trend Channels gives you an adaptive mean, volatility-aware rails, a simple trend lens, and clear signals. Trade the trend by buying pullbacks in green and selling pullbacks in red, or fade stretched extremes back to the mean with defined risk. One framework, two strategies, consistent logic.
MACD Josh MACD Study — Visual Crossover Tags
Overview:
This script displays MACD signals in a clear, visual way by showing:
Histogram = EMA(Fast) − EMA(Slow)
Signal = EMA(Histogram, Signal Length)
It adds labels and arrows to help you see crossover events between the Histogram and the Signal line more easily.
⚠️ Disclaimer: This tool is for educational and research purposes only. It is not financial advice or an investment recommendation. Past performance does not guarantee future results. Users should make their own decisions and manage risk responsibly.
Features
Central Zero Line with Signal and Histogram plots
Optional labels/arrows to highlight Histogram–Signal crossovers
Alerts for crossover and crossunder events, integrated with TradingView’s alert system
Standard adjustable inputs: Fast EMA, Slow EMA, Signal EMA
How to Interpret (for study only)
When the Histogram crosses above the Signal, a visual label/arrow marks a positive MACD event
When the Histogram crosses below the Signal, a visual label/arrow marks a negative MACD event
The “BUY/SELL” labels are visual study tags only — they do not represent trade instructions or recommendations
Responsible Usage Tips
Test across multiple timeframes and different assets
Combine with higher-timeframe trend, support/resistance, or volume for confirmation
Use alerts with caution, and always test in a demo environment first
Technical Notes
The script does not use future data and does not repaint signals once bars are closed
Results depend on market conditions and may vary across assets and timeframes
License & Credits
Written in Pine Script® v5 for TradingView
The indicator name shown on chart is for labeling purposes only and carries no implication of advice or solicitation
Options Max Pain Calculator [BackQuant]Options Max Pain Calculator
A visualization tool that models option expiry dynamics by calculating "max pain" levels, displaying synthetic open interest curves, gamma exposure profiles, and pin-risk zones to help identify where market makers have the least payout exposure.
What is Max Pain?
Max Pain is the theoretical expiration price where the total dollar value of outstanding options would be minimized. At this price level, option holders collectively experience maximum losses while option writers (typically market makers) have minimal payout obligations. This creates a natural gravitational pull as expiration approaches.
Core Features
Visual Analysis Components:
Max Pain Line: Horizontal line showing the calculated minimum pain level
Strike Level Grid: Major support and resistance levels at key option strikes
Pin Zone: Highlighted area around max pain where price may gravitate
Pain Heatmap: Color-coded visualization showing pain distribution across prices
Gamma Exposure Profile: Bar chart displaying net gamma at each strike level
Real-time Dashboard: Summary statistics and risk metrics
Synthetic Market Modeling**
Since Pine Script cannot access live options data, the indicator creates realistic synthetic open interest distributions based on configurable market parameters including volume patterns, put/call ratios, and market maker positioning.
How It Works
Strike Generation:
The tool creates a grid of option strikes centered around the current price. You can control the range, density, and whether strikes snap to realistic market increments.
Open Interest Modeling:
Using your inputs for average volume, put/call ratios, and market maker behavior, the indicator generates synthetic open interest that mirrors real market dynamics:
Higher volume at-the-money with decay as strikes move further out
Adjustable put/call bias to reflect current market sentiment
Market maker inventory effects and typical short-gamma positioning
Weekly options boost for near-term expirations
Pain Calculation:
For each potential expiry price, the tool calculates total option payouts:
Call options contribute pain when finishing in-the-money
Put options contribute pain when finishing in-the-money
The strike with minimum total pain becomes the Max Pain level
Gamma Analysis:
Net gamma exposure is calculated at each strike using standard option pricing models, showing where hedging flows may be most intense. Positive gamma creates price support while negative gamma can amplify moves.
Key Settings
Basic Configuration:
Number of Strikes: Controls grid density (recommended: 15-25)
Days to Expiration: Time until option expiry
Strike Range: Price range around current level (recommended: 8-15%)
Strike Increment: Spacing between strikes
Market Parameters:
Average Daily Volume: Baseline for synthetic open interest
Put/Call Volume Ratio: Market sentiment bias (>1.0 = bearish, <1.0 = bullish) It does not work if set to 1.0
Implied Volatility: Current option volatility estimate
Market Maker Factors: Dealer positioning and hedging intensity
Display Options:
Model Complexity: Simple (line only), Standard (+ zones), Advanced (+ heatmap/gamma)
Visual Elements: Toggle individual components on/off
Theme: Dark/Light mode
Update Frequency: Real-time or daily calculation
Reading the Display
Dashboard Table (Top Right):
Current Price vs Max Pain Level
Distance to Pain: Percentage gap (smaller = higher pin risk)
Pin Risk Assessment: HIGH/MEDIUM/LOW based on proximity and time
Days to Expiry and Strike Count
Model complexity level
Visual Elements:
Red Line: Max Pain level where payout is minimized
Colored Zone: Pin risk area around max pain
Dotted Lines: Major strike levels (green = support, orange = resistance)
Color Bar: Pain heatmap (blue = high pain, red = low pain/max pain zones)
Horizontal Bars: Gamma exposure (green = positive, red = negative)
Yellow Dotted Line: Gamma flip level where hedging behavior changes
Trading Applications
Expiration Pinning:
When price is near max pain with limited time remaining, there's increased probability of gravitating toward that level as market makers hedge their positions.
Support and Resistance:
High open interest strikes often act as magnets, with max pain representing the strongest gravitational pull.
Volatility Expectations:
Above gamma flip: Expect dampened volatility (long gamma environment)
Below gamma flip: Expect amplified moves (short gamma environment)
Risk Assessment:
The pin risk indicator helps gauge likelihood of price manipulation near expiry, with HIGH risk suggesting potential range-bound action.
Best Practices
Setup Recommendations
Start with Model Complexity set to "Standard"
Use realistic strike ranges (8-12% for most assets)
Set put/call ratio based on current market sentiment
Adjust implied volatility to match current levels
Interpretation Guidelines:
Small distance to pain + short time = high pin probability
Large gamma bars indicate key hedging levels to monitor
Heatmap intensity shows strength of pain concentration
Multiple nearby strikes can create wider pin zones
Update Strategy:
Use "Daily" updates for cleaner visuals during trading hours
Switch to "Every Bar" for real-time analysis near expiration
Monitor changes in max pain level as new options activity emerges
Important Disclaimers
This is a modeling tool using synthetic data, not live market information. While the calculations are mathematically sound and the modeling realistic, actual market dynamics involve numerous factors not captured in any single indicator.
Max pain represents theoretical minimum payout levels and suggests where natural market forces may create gravitational pull, but it does not guarantee price movement or predict exact expiration levels. Market gaps, news events, and changing volatility can override these dynamics.
Use this tool as additional context for your analysis, not as a standalone trading signal. The synthetic nature of the data makes it most valuable for understanding market structure and potential zones of interest rather than precise price prediction.
Technical Notes
The indicator uses established option pricing principles with simplified implementations optimized for Pine Script performance. Gamma calculations use standard financial models while pain calculations follow the industry-standard definition of minimized option payouts.
All visual elements use fixed positioning to prevent movement when scrolling charts, and the tool includes performance optimizations to handle real-time calculation without timeout errors.
