Volume Cluster Profile [VCP] (Zeiierman)█ Overview
Volume Cluster Profile (Zeiierman) is a volume profile tool that builds cluster-enhanced volume-by-price maps for both the current market window and prior swing segments.
Instead of treating the profile as a raw histogram only, VCP detects the dominant volume peaks (clusters) inside the profile, then uses a Gaussian spread model to “radiate” those peaks into surrounding price bins. This produces a smoother, more context-aware profile that highlights where volume is most meaningfully concentrated, not just where it happened to print.
On top of the live profile, VCP automatically records historical swing profiles between pivots, wraps each segment for clarity, and can project the most recent segment’s High/Low Value extensions (VA/LV) forward to the current bar to keep key structure visible as price evolves.
█ How It Works
⚪ 1) Profile Construction (Volume-by-Price)
VCP builds a volume profile histogram over a chosen window (current lookback, or a swing segment):
Range Scan
The script finds the full min → max price range inside the window.
Bin the Range
That range is divided into a user-defined number of Price Bins (rows). More bins = finer detail, but heavier computation.
Accumulate Volume into Bins
For each bar inside the window, the script takes the bar’s close price, determines which price bin it belongs to, and adds the bar’s volume to that bin.
float step = (maxPrice - minPrice) / binsCount
for i = 0 to barsToUse - 1
int b = f_clamp(int(math.floor((close - minPrice) / step)), 0, binsCount - 1)
volBins += volume
Result: volBins becomes a standard volume-by-price histogram (close-based binning).
⚪ 2) Cluster Detection (Finding Dominant Peaks)
Once the raw histogram is built, VCP identifies cluster centers as the most meaningful volume “hills”:
Local Peak Test
A bin becomes a cluster candidate if its volume is greater than or equal to its immediate neighbors (left/right).
Filter Weak Peaks
Peaks must also be above a basic activity threshold (relative to the average bin volume) to avoid noise.
bool isPeak = v >= left and v >= right
if isPeak and v > avgVol
array.push(clusterIdxs, b)
Keep the Best Peaks Only
If too many peaks exist, the script keeps only the strongest ones, capped by: Max Cluster Centers
Result: clusterIdxs = the set of dominant profile peaks (cluster centers).
⚪ 3) Cluster Enhancement (Gaussian Spread Model)
This is what makes VCP different from a raw profile.
Instead of using volBins directly, the script builds an enhanced profile where each cluster center influences nearby price bins using a Gaussian curve:
Distance from each bin to each cluster center is computed in “bin units”
A Gaussian weight is applied so that bins near the center receive stronger influence, while bins farther away decay smoothly.
Cluster Spread (sigma) controls how wide this influence reaches: low sigma produces tight, sharp clusters, while high sigma results in wider, smoother structure zones.
enhanced += centerV * math.exp(-(dist*dist) / (2.0 * clusterSigma * clusterSigma))
volBinsAI := enhanced / szClFinal
Result: volBinsAI = the cluster-enhanced volume value for each bin.
In practice, VCP turns the profile into a structure map of dominant volume concentrations, rather than a simple “where volume printed” histogram.
⚪ 4) POC from the Enhanced Profile
After enhancement:
The bin with the highest volBinsAI becomes the POC (Point of Control)
POC is plotted at the midpoint price of that bin
if volBinsAI > maxVol
maxVol := volBinsAI , pocBin := b
So the POC reflects the cluster-enhanced profile rather than the raw histogram.
█ How to Use
⚪ Read Cluster Structure (Default = 2 Clusters)
By default, the Volume Cluster Profile (VCP) is configured to detect up to 2 dominant volume clusters within the profile. These clusters represent price zones where the market accepted trading activity, not just where volume printed randomly.
⚪ When TWO Clusters Appear
When VCP detects two distinct clusters, it usually indicates:
Two competing areas of value
Ongoing auction between higher and lower acceptance zones
Treat each cluster as an acceptance zone
Expect slower price action and rotation inside clusters
Expect faster movement in the low-volume space between clusters
Use cluster-to-cluster movement as:
rotation targets
range boundaries
acceptance vs rejection tests
Typical behavior:
Price enters a cluster → stalls, consolidates, rotates
Price rejects at cluster edge → moves toward the opposite cluster
⚪ When ONLY ONE Cluster Appears
If VCP detects only one cluster, or if two clusters visually merge into one:
Volume is no longer split
The market has formed a single dominant value area
Price consensus is strong
Treat the cluster as the primary value anchor
Expect pullbacks and reactions around this zone
Bias becomes directional:
Above the cluster → bullish context
Below the cluster → bearish context
Inside the cluster → balance/chop
This structure often appears during clean trends or stable equilibria.
⚪ VA/LV Extensions
VCP projects two zones from the end of the most recent swing segment:
VA extension = the segment’s highest enhanced-volume bin (dominant zone)
LV extension = the segment’s lowest enhanced-volume bin (thin/weak zone)
A breakout of the VA extension signals acceptance and potential continuation. A retest of the VA or LV extension is used to confirm acceptance or rejection, while rejection from either zone often leads to rotation back toward value.
█ Settings
Cluster Volume Profile
Lookback Bars – how many recent bars build the current profile
Price Bins – profile resolution (more bins = more detail, heavier CPU)
Cluster Spread – Gaussian sigma; higher values widen/smooth cluster influence
Max Cluster Centers – cap on detected peaks used in enhancement
Historical Swing Cluster Volume Profile
Pivot Length – swing sensitivity (larger = fewer, broader segments)
Max Profiles – how many historical segments to retain
Profile Width – thickness of each historical profile
High & Low Value Area
Profile VA/LV – extend the last segment’s top-bin and low-bin zones forward
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Volumeprofilestrategy
Multi-Distribution Volume Profile (Zeiierman)█ Overview
Multi-Distribution Volume Profile (Zeiierman) is a flexible, structure-first volume profile tool that lets you reshape how volume is distributed across price, from classic uniform profiles to advanced statistical curves like Gaussian, Lognormal, Student-t, and more.
Instead of forcing every market into a single "one-size-fits-all" profile, this tool lets you model how volume is likely concentrated inside each bar (body vs wicks, midpoint, tails, center bias, right-skew, heavy tails, etc.) and then stacks that behavior across a whole lookback window to build a rich, multi-distribution map of traded activity.
On top of that, it overlays a dynamic Center Band (value area) and a fade/gradient model that can color each price row by volume, hits, recency, volatility, reversals, or even liquidity voids, turning a plain profile into a multi-dimensional context map.
Highlights
Choose from multiple Profile Build Modes , including uniform, body-only, wick-only, midpoint/close/open, center-weighted, and a suite of probability-style distributions (Gaussian, Lognormal, Weibull, Student-t, etc.)
Flexible anchor layout: draw the profile on Right/Left (horizontal) or Bottom/Top (vertical) to fit any chart layout
Value Area / Center Band computed from volume quantiles around the POC.
Gradient-based Fade Metrics: volume, price hits, freshness (time decay), volatility impact, dwell time, reversal density, compression, and liquidity voids
Separate bullish vs bearish volume at each price row for directional structure insights
█ How It Works
⚪ Profile Construction
The script scans a user-defined Bars Included window and finds the full high–low span of that zone. It then divides this range into a user-controlled number of Price Levels (rows).
For each historical bar within the window:
It measures the candle’s price range, body, and wicks.
It assigns volume to rows according to the selected Profile Build Mode, for example:
* Range Uniform – volume spread evenly across the full high–low range.
* Range Body Only / Range Wick Only – concentrate volume inside the body or wicks only.
* Midpoint / Close / Open Only – allocate volume entirely into one price row (pinpoint modeling).
HL2 / Body Center Weighted – center weights around the middle of the range/body.
Recent-Weighted Volume – amplify newer bars using exponential time decay.
Volume Squared (Hard) – aggressively boost bars with large volume.
Up Bars Only / Down Bars Only – filter volume to only bullish or bearish bars.
For more advanced shapes, the script uses continuous distributions across the bar’s span:
Linear, Triangular, Exponential to High
Cosine Centered, PERT
Gaussian, Lognormal, Cauchy, Laplace
Pareto, Weibull, Logistic, Gumbel
Gamma, Beta, Chi-Square, Student-t, F-Shape
Each distribution produces a weight for each row within the bar’s range, normalized so the total volume remains consistent, but the shape of where that volume lands changes.
⚪ POC & Center Band (Value Area)
Once all rows are accumulated:
The row with the highest total volume becomes the Point of Control (POC)
The script computes cumulative volume and finds the band that wraps a user-defined Center of Profile % (e.g., 68%) around the center of distribution.
This range is displayed as a central band, often treated like a value area where price has spent the most “effort” trading.
⚪ Gradient Fade Engine
Each row also gets a fade metric, chosen in Fade Metric:
Volume – opacity based on relative volume.
Price Hits – how frequently that row was touched.
Blended (Vol+Hits) – average of volume & hits.
Freshness – emphasizes recent activity, controlled by Decay.
Volatility Impact – rows that saw larger ranges contribute more.
Dwell Time – where price “camped” the longest.
Reversal Density – where direction changes cluster.
Compression – tight-range compression zones.
Liquidity Void – inverse of volume (thin liquidity zones).
When Apply Gradient is enabled, the row’s bullish/bearish colors are tinted from faint to strong based on this chosen metric, effectively turning the profile into a heatmap of your chosen structural property.
█ How to Use
⚪ Explore Different Distribution Assumptions
Switch between multiple Profile Build Modes to see how your assumptions about intrabar volume affect structure:
Use Range Uniform for classical profile reading.
Deploy Gaussian, Logistic, or Cosine shapes to emphasize central clustering.
Try Pareto, Lognormal, or F-Shape to focus on tail / extremal activity.
Use Recent-Weighted Volume to prioritize the most recent structural behavior.
This is especially useful for traders who want to test how different modeling assumptions change perceived value areas and levels of interest.
⚪ Identify Value, Acceptance & Rejection Zones
Use the POC and Center of Profile (%) band to distinguish:
High-acceptance zones – wide central band, thick rows, strong gradient → fair value areas
Rejection zones & tails – thin extremes, low dwell time, high volatility or reversal density
These regions can be used as:
Targets and origin zones for mean reversion
Context for breakout validation (leaving value)
Bias reference for intraday rotations or swing rotations
⚪ Read Directional Structure Within the Profile
Because each row is split into bullish vs bearish contributions, you can visually read:
Where buyers dominated a price region (large bullish slice)
Where sellers absorbed or defended (large bearish slice)
Combining this with Fade Metrics like Reversal Density, Dwell Time, or Freshness turns the profile into a structural order-flow map, without needing raw tick-by-tick volume data.
⚪ Use Fade Metrics for Contextual Heatmaps
Each Fade Metric can be used for a different analytical lens:
Volume / Blended – emphasize where volume and activity are concentrated.
Freshness – highlight the most recently active zones that still matter.
Volatility Impact & Compression – spot areas of explosive moves vs coiled ranges.
Reversal Density – locate micro turning points and battle zones.
Liquidity Void – visually pop out thin regions that may act as speedways or magnets.
█ Settings
Profile Build Mode – Selects how each bar’s volume is distributed across its price range (uniform, body/wick, midpoint/close/open, center-weighted, or statistical distribution families).
Bars Included – Number of bars used to build the profile from the current bar backward.
Price Levels – Vertical resolution of the profile: more levels = smoother but heavier.
Anchor Side – Where the profile is drawn on the chart: Right, Left, Bottom, or Top.
Offset (bars) – Horizontal offset from the last bar to the profile when using Right/Left modes.
Apply Gradient – Toggles the fade/heatmap coloring based on the selected metric.
Fade Metric – Chooses the property driving row opacity (Volume, Hits, Freshness, Volatility Impact, Dwell Time, Reversal Density, Compression, Liquidity Void).
Decay – Time-decay factor for Freshness (values close to 1 keep older activity relevant for longer).
Profile Thickness – Relative thickness of the profile along the time axis, as a % of the lookback window.
Center of Profile (%) – Volume percentage used to define the central band (value area) around the POC.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
