Volume Flow Analysis [UAlgo]Volume Flow Analysis is a price mapped volume study that distributes historical activity across price levels and separates that activity into directional pressure, stealth style movement, imbalance zones, absorption zones, Point of Control, Value Area, and profile shape. Instead of reading volume only bar by bar, the script converts a rolling section of chart history into a horizontal market map where each price level receives its own buy pressure, sell pressure, and movement efficiency profile.
The script works on the latest bar and rebuilds the full map from a rolling historical window. That window can either use the full user selected lookback or a shorter effective depth when decay is enabled. This gives more recent bars a stronger influence while older bars gradually lose weight. The result is a profile that can behave either like a stable historical map or like a more adaptive flow view depending on the selected decay factor.
Inside each price bucket, the script estimates directional pressure by splitting volume into buy side and sell side portions based on where price closed inside the bar range. It then distributes those portions across all buckets touched by the bar using proportional overlap. At the same time, it builds a separate stealth flow style measure based on range per unit of volume, which acts as a proxy for how much price movement occurred relative to participation.
From there, the script identifies the Point of Control, expands outward to build the seventy percent Value Area, classifies the overall profile shape, highlights extreme buy or sell imbalances, detects absorption style conditions, and optionally extends those key zones across the historical range. A legend table summarizes the active state of the map so the user can read the distribution quickly.
In practical use, Volume Flow Analysis is useful for studying where participation concentrated, where directional pressure was strongest, where flow became unbalanced, and whether the profile currently resembles a balanced, short covering, long liquidation, or double distribution structure.
🔹 Features
🔸 Price Bucket Volume Mapping
The script divides the active price range into user defined buckets and allocates volume into those levels according to actual price overlap. This creates a true horizontal flow map instead of a simple vertical volume display.
🔸 Buy Pressure and Sell Pressure Separation
Each price bucket stores both estimated buy side volume and estimated sell side volume. These two components are then drawn side by side so the user can see which side dominated each price level.
🔸 Decay Weighted Historical Memory
Older bars can gradually lose influence through the decay factor. This lets the profile emphasize fresher activity while still preserving historical structure.
🔸 Stealth Flow Layer
The script includes an additional stealth flow style metric based on range relative to volume. This highlights zones where price moved efficiently with relatively less participation.
🔸 Point of Control and Value Area
The indicator automatically finds the highest volume bucket as the Point of Control and expands from that level until seventy percent of total volume is captured to form the Value Area.
🔸 Imbalance Detection
Price levels with one sided pressure above the selected imbalance ratio are highlighted as buy or sell imbalance zones. These can also be extended across the profile range.
🔸 Absorption Detection
Buckets with unusually high total volume but unusually low stealth flow are marked as absorption. This can suggest heavy participation with reduced price efficiency.
🔸 Profile Shape Classification
The script classifies the overall profile as D shape, B shape, P shape, or b shape using the distribution of volume across the upper, middle, and lower thirds of the profile.
🔸 Range Box and Historical Scope Label
A dashed range box shows the active calculation window and displays the effective number of bars used in the current map.
🔸 Built In Legend and Summary Table
A table in the lower right corner explains the map colors and also reports the current buy sell balance, profile shape, and whether imbalance or absorption layers are active.
🔹 Calculations
1) Determining the Effective Historical Window
int nCalc = i_decay == 1.0 ? i_lookback : int(math.ceil(math.log(0.01) / math.log(i_decay)))
int N = math.max(1, math.min(nCalc, i_lookback))
N := math.min(N, bar_index)
This is the first major step of the script.
If decay is set to 1.0, the script simply uses the full user selected lookback.
If decay is below 1.0, the script solves for how many bars are needed until the decay weight falls to roughly one percent of its original value. That value becomes the effective calculation depth.
Then the script clamps that depth so it never exceeds the lookback input and never exceeds available chart history.
So the map can behave in two different ways:
a full fixed history profile,
or a dynamically shortened profile where older bars become practically irrelevant.
2) Finding the Active Price Range and Bucket Size
float pH = high
float pL = low
for i = 0 to N - 1
pH := math.max(pH, high )
pL := math.min(pL, low )
float bSz = (pH - pL) / i_buckets
This block establishes the vertical bounds of the map.
The script scans the effective historical window and finds the highest price and lowest price inside it. Then it divides that full range by the selected number of price levels.
The result is the bucket size, which determines the height of every price cell in the flow map.
So the whole analysis space is always defined by the actual recent trading range rather than by arbitrary static levels.
3) Initializing Buy, Sell, and Stealth Arrays
array bVol = array.new(i_buckets, 0.0)
array sVol = array.new(i_buckets, 0.0)
array stV = array.new(i_buckets, 0.0)
These three arrays are the main storage layer of the profile.
bVol stores buy pressure per bucket.
sVol stores sell pressure per bucket.
stV stores the stealth flow style metric per bucket.
As each historical bar is processed, its weighted contribution is distributed into these arrays according to price overlap.
So the script is building three parallel price maps at the same time.
4) Splitting Each Bar Into Buy and Sell Pressure
float b_v = rng == 0 ? (v_i / 2) : (v_i * (c_i - l_i) / rng)
float s_v = v_i - b_v
This is the directional volume model.
If a bar has zero range, volume is split evenly between buy side and sell side.
Otherwise, the script estimates buy pressure from where the close sits inside the bar range. A close nearer the high gives more weight to buy pressure. A close nearer the low gives less weight to buy pressure. Sell pressure is simply the remainder.
This is not exchange level aggressor data, but it is a practical price location based estimate of directional pressure inside each candle.
So every bar contributes both a buy component and a sell component to the profile.
5) Defining the Stealth Flow Proxy
float st_m = v_i == 0 ? rng : rng / v_i
This line creates the stealth flow style measurement.
The idea is simple. If price covers a relatively large range with relatively little volume, the ratio becomes larger. If price needs heavy volume to achieve the same range, the ratio becomes smaller.
So this metric behaves like a movement efficiency proxy:
higher values suggest cleaner movement per unit of volume,
lower values suggest heavier participation per unit of movement.
It is important to interpret this as a derived proxy rather than a direct exchange measured stealth order flow.
6) Applying Decay Weight to Historical Bars
float d_m = math.pow(i_decay, i)
Every historical bar receives a decay multiplier based on how far back it is.
The most recent bar gets the largest weight. Older bars receive progressively smaller weights as long as decay is below one.
This means the final profile is not just a raw accumulation of past activity. It is a weighted accumulation where recent flow can dominate older structure if the user wants a more adaptive map.
7) Distributing a Bar Across All Touched Buckets
int minIdx = math.max(0, math.floor((l_i - pL) / bSz))
int maxIdx = math.min(i_buckets - 1, math.floor((h_i - pL) / bSz))
for j = minIdx to maxIdx
float b_min = pL + j * bSz
float b_max = b_min + bSz
float ovr = math.max(0, math.min(h_i, b_max) - math.max(l_i, b_min))
if ovr > 0
float prop = ovr / rng
bVol.set(j, bVol.get(j) + b_v * prop * d_m)
sVol.set(j, sVol.get(j) + s_v * prop * d_m)
stV.set(j, stV.get(j) + st_m * prop * d_m)
This is one of the most important calculations in the whole script.
For every bar, the script determines which price buckets were touched by that bar. It then measures how much of the bar overlapped each bucket. That overlap fraction is used to distribute buy pressure, sell pressure, and stealth flow into the correct levels.
So if a bar spends more of its range inside a given bucket, more of its volume contribution goes into that bucket.
This makes the map much more realistic than assigning the full bar volume to only one price level.
8) Handling Zero Range Bars
else
int idx = math.max(0, math.min(i_buckets - 1, math.floor((c_i - pL) / bSz)))
bVol.set(idx, bVol.get(idx) + b_v * d_m)
sVol.set(idx, sVol.get(idx) + s_v * d_m)
stV.set(idx, stV.get(idx) + st_m * d_m)
If a bar has no range, the script cannot distribute it by overlap. In that case, it assigns the full weighted contribution to the bucket containing the close.
This ensures that flat or compressed bars still contribute to the profile without breaking the overlap logic.
9) Building Total Volume, Point of Control, and Summary Totals
float tVolMax = 0.0
float stMax = 0.0
float stMin = 1e10
int poc = 0
float pocV = 0.0
float sumV = 0.0
array tVol = array.new(i_buckets, 0.0)
for j = 0 to i_buckets - 1
float t = bVol.get(j) + sVol.get(j)
float st = stV.get(j)
tVol.set(j, t)
sumV += t
if t > tVolMax
tVolMax := t
if t > pocV
pocV := t
poc := j
After all bars are processed, the script combines buy and sell pressure for each bucket into total volume.
At the same time, it calculates:
the total profile volume,
the maximum bucket volume,
the Point of Control bucket,
and the minimum and maximum stealth values.
The Point of Control is simply the bucket with the largest accumulated total volume.
So this stage turns the raw arrays into a complete profile summary.
10) Calculating the Seventy Percent Value Area
float trg = sumV * 0.70
float cur = pocV
int vH = poc
int vL = poc
while cur < trg and (vH < i_buckets - 1 or vL > 0)
float vUp = vH < i_buckets - 1 ? tVol.get(vH + 1) : -1.0
float vDn = vL > 0 ? tVol.get(vL - 1) : -1.0
if vUp >= vDn and vUp >= 0
vH += 1
cur += vUp
else if vDn > vUp and vDn >= 0
vL -= 1
cur += vDn
else
break
This is the Value Area expansion algorithm.
The script starts at the Point of Control and keeps adding the next larger neighboring bucket, either above or below, until the accumulated total reaches seventy percent of overall profile volume.
The upper and lower boundaries of that expansion become the Value Area High and Value Area Low.
So the Value Area always forms around the Point of Control and grows toward whichever neighboring levels contain the most activity.
11) Classifying the Profile Shape
float vTop = 0.0
float vMid = 0.0
float vBot = 0.0
int third = math.floor(i_buckets / 3)
for j = 0 to i_buckets - 1
float v = tVol.get(j)
if j < third
vBot += v
else if j < third * 2
vMid += v
else
vTop += v
string shp = "D-Shape (Balanced)"
if vTop > sumV * 0.20 and vBot > sumV * 0.20 and vMid < sumV * 0.50
shp := "B-Shape (Double Dist)"
else if poc > i_buckets * 0.5 and vTop > vBot * 1.3
shp := "P-Shape (Short Covering)"
else if poc < i_buckets * 0.5 and vBot > vTop * 1.3
shp := "b-Shape (Long Liquidation)"
The script divides the profile into upper, middle, and lower thirds and compares how much volume sits in each section.
If upper and lower thirds both carry meaningful volume while the middle is relatively weak, the script labels the profile as a B shape.
If the Point of Control sits high and the upper section dominates, it labels the profile as a P shape.
If the Point of Control sits low and the lower section dominates, it labels the profile as a b shape.
Otherwise, the default label is D shape.
So the shape classifier is reading where the distribution is concentrated and how balanced it looks across the full price range.
12) Computing the Average Stealth Level
float avgSt = 0.0
int stCnt = 0
for j = 0 to i_buckets - 1
if stV.get(j) > 0
avgSt += stV.get(j)
stCnt += 1
avgSt := stCnt > 0 ? avgSt / stCnt : 0.0
This block computes the average positive stealth value across all populated buckets.
That average later becomes part of the absorption logic. Buckets with much lower than average stealth, combined with very high total volume, are flagged as absorption.
So the script uses the stealth map not only for display width, but also for analysis.
13) Detecting Imbalances and Absorption
bool imbB = i_showImb and s > 0 and b / s >= i_imbRatio
bool imbS = i_showImb and b > 0 and s / b >= i_imbRatio
bool absr = i_showAbs and t > avgV * 1.5 and st < avgSt * 0.5
These are the main analytical event conditions.
A buy imbalance exists when buy pressure is at least the selected ratio times larger than sell pressure.
A sell imbalance exists when sell pressure is at least the selected ratio times larger than buy pressure.
Absorption is defined differently. It requires:
total bucket volume above one and a half times the average bucket volume,
and stealth flow below half the average stealth value.
That means the bucket saw heavy participation but relatively poor movement efficiency, which can suggest absorbed flow.
So imbalances mark one sided aggression, while absorption marks heavy activity with suppressed movement.
14) Scaling the Visual Width of Each Layer
int wS = int((s / tVolMax) * i_width)
int wB = int((b / tVolMax) * i_width)
int wSt = int(((st - stMin) / math.max(1e-10, stMax - stMin)) * (i_width / 2))
The map is drawn horizontally, so the script converts each metric into width.
Sell pressure width and buy pressure width are scaled relative to the largest total bucket volume.
Stealth flow width is scaled separately relative to the stealth range and is limited to half the main map width.
So every bucket gets a visual footprint that reflects its relative pressure and stealth intensity.
15) Drawing the Buy, Sell, and Stealth Blocks
if wS > 0
_boxes.push(box.new(xStart, pHi, xStart + wS, pLo, bgcolor = cS, border_color = bc, border_width = bw))
if wB > 0
_boxes.push(box.new(xStart + wS, pHi, xStart + wS + wB, pLo, bgcolor = cB, border_color = bc, border_width = bw))
if i_showSt and wSt > 0
_boxes.push(box.new(xStart + wS + wB, pHi, xStart + wS + wB + wSt, pLo, bgcolor = c_stealth, border_color = bc, border_width = 1))
This is the actual map renderer.
The sell block is drawn first.
The buy block is drawn immediately after it.
If stealth flow display is enabled, the stealth block is drawn after both pressure blocks.
So each price level becomes a compact three part flow bar:
sell pressure,
buy pressure,
and optional stealth flow.
16) Extending Imbalance and Absorption Zones Across the Range
if i_showZones
if imbB
_boxes.push(box.new(bar_index - N + 1, pHi, bar_index + 1, pLo, bgcolor = color.new(c_buy, 90), border_color = na))
if imbS
_boxes.push(box.new(bar_index - N + 1, pHi, bar_index + 1, pLo, bgcolor = color.new(c_sell, 90), border_color = na))
if absr
_boxes.push(box.new(bar_index - N + 1, pHi, bar_index + 1, pLo, bgcolor = color.new(color.rgb(255, 0, 255), 85), border_color = na))
If zone extension is enabled, the script projects imbalance and absorption buckets horizontally across the entire historical calculation window.
This makes key buckets easier to see in relation to actual price bars rather than only inside the right side profile map.
So the indicator can show both a profile view and a chart level zone view at the same time.
17) Drawing the Range Box and Historical Scope Label
if i_showRng
_boxes.push(box.new(bar_index - N + 1, pH, bar_index + 1, pL, bgcolor = na, border_color = c_range, border_style = line.style_dashed))
_labels.push(label.new(bar_index - int(N / 2) + 1, pH, "N: " + str.tostring(N), textcolor = c_range, style = label.style_label_down, color = color.new(color.black, 100), size = size.small))
This block outlines the active analysis window on the chart.
The dashed box marks the highest and lowest prices used by the profile, and the label shows the effective bar count N.
So the user can always see exactly which portion of chart history is feeding the current flow map.
18) Drawing the Point of Control
if i_showPOC
float pPrice = pL + (poc + 0.5) * bSz
int endX = i_extPOC ? bar_index + i_width : bar_index + 1
_lines.push(line.new(bar_index - N + 1, pPrice, endX, pPrice, color = c_poc, width = 2))
The Point of Control line is drawn at the midpoint of the highest volume bucket.
If extension is enabled, the line continues forward through the map width. Otherwise it stops at the right edge of the historical window.
So the Point of Control remains a clear reference level for the most active price area inside the map.
19) Drawing the Value Area
if i_showVA
float vaTop = pL + (vH + 1) * bSz
float vaBot = pL + vL * bSz
_boxes.push(box.new(bar_index + 1, vaTop, bar_index + 1 + i_width, vaBot, border_color = c_va, bgcolor = color.new(c_va, 90), border_style = line.style_dashed))
This draws the seventy percent Value Area as a translucent box on the right side of the profile.
The top and bottom are derived from the expanded Value Area bucket boundaries, and the box spans the full map width.
So the user can immediately see where most of the profile activity was concentrated around the Point of Control.
20) Buy Sell Dominance Summary
float tB = bVol.sum()
float tS = sVol.sum()
float tV = tB + tS
float pB = tV > 0 ? (tB / tV) * 100 : 0
float pS = tV > 0 ? (tS / tV) * 100 : 0
string dTxt = pB >= pS ? "Bullish " + str.tostring(pB, "#") + "%" : "Bearish " + str.tostring(pS, "#") + "%"
This block calculates the total buy side share and total sell side share across the whole profile.
Whichever side holds the greater percentage becomes the dominant flow label in the table.
So the summary does not only show local bucket conditions. It also provides a broad view of which side controlled more of the weighted participation inside the entire mapped range. Indicator
Institutional Footprint Divergence Engine🔹 Introduction
This indicator, the Institutional Footprint Divergence Engine, attempts to identify moments where price action and genuine order flow diverge — a condition that historically precedes reversals driven by smart money absorption and distribution. The core idea is this: if price makes a new swing high but the underlying buy-sell delta is contracting, the market is printing a higher high on less aggressive buying pressure, suggesting the move is being distributed into rather than genuinely accumulated. The inverse is equally meaningful at lows.
Unlike traditional divergence indicators that use derivative oscillators like RSI or MACD as the proxy for momentum, this script uses volume delta — the direct arithmetic difference between buying and selling volume at the bar level — sourced natively from PulseWire's newly released request.footprint() function where a Premium or Ultimate subscription is active. On standard charts, the indicator falls back to a tick-estimated delta approximation. The distinction matters, and I'll cover precisely why throughout this description.
Every detected divergence is assigned a composite quality score from 0 to 100, computed across five weighted dimensions that assess the structural strength, volume context, cumulative delta alignment, and volatility regime at the moment of detection. Only divergences that clear a user-defined score threshold are displayed — filtering the noise that plagues most divergence tools.
🔹 The Premise — Why Delta Divergence Reveals Institutional Behavior
🔸 What volume delta actually measures
Every transaction in a liquid market has a buyer and a seller. Volume delta measures the net directional aggression of those transactions: it is the sum of volume that traded at the ask (aggressive buying) minus the volume that traded at the bid (aggressive selling) within a single bar. A positive delta bar means buyers were more aggressive. A negative delta bar means sellers were more aggressive.
This is categorically different from price direction. A bar can close higher while posting a negative delta — meaning price moved up, but sellers were the more aggressive counterparty throughout the move. This is the fingerprint of absorption: a large participant or group of participants quietly selling into rising price, absorbing aggressive buy orders without allowing the market to fall. They want retail to push price higher. They're using that momentum as liquidity to distribute their position.
Delta divergence is the systematic detection of this condition across swing structures.
🔸 The mechanics of absorption at swing highs
Assume price has been in an uptrend and just made a swing high at $4,200 with a delta of +850 contracts — strong buyer aggression confirming the high. Price retraces, then pushes up again to $4,215, printing a higher high. But this time, the delta is only +210. Price went higher. The aggressive buying volume did not.
What does this tell you? The move to $4,215 required proportionally far less buyer aggression than the move to $4,200. Two possibilities explain this: either sellers are absorbing the buying (distribution), or organic buying interest is fading and the move is increasingly resting on passive limit sell orders being consumed by declining buy-side momentum. Either way, the structural message is identical — the higher high is not supported by the order flow that created it, and the probability of continuation has deteriorated meaningfully.
This is the ICT and Smart Money Concepts concept of distribution rendered in order flow terms rather than price structure terms alone.
🔸 The symmetric argument at swing lows
At swing lows, the bullish divergence condition is: price makes a lower low, but the negative delta at that low is less negative than the prior swing low. Less aggressive selling at a lower price. This is absorption at the demand side — large buyers accumulating into weakness, absorbing retail sell orders without allowing price to collapse further. The lower low prints because they let it — they need the price to be there to fill their orders. But the delta tells you that sellers were unable to drive the same aggression they managed at the prior low.
Harris (2003), in his foundational text on market microstructure, describes this phenomenon as informed traders systematically positioning against the uninformed flow — using the uninformed participants' aggression as liquidity.
Cont, Stoikov & Talreja (2010), in their research on limit order book dynamics, demonstrate empirically that large passive participants consistently exploit periods of high aggressive flow imbalance to establish positions at favorable prices.
Delta divergence is not a leading indicator in the traditional sense. It is a coincident indicator of order flow context that becomes meaningful when paired with a confirmed swing structure.
🔸 Why native footprint data changes the calculus
Prior to January 2026, Pine Script had no access to true intrabar volume distribution. Every "delta" calculation in PulseWire scripts was an estimate — typically assigning the bar's total volume directionally based on close position within the bar's range, or using up/down tick counting approximations. These methods are reasonable proxies but they introduce systematic errors: a bar that closes at its midpoint with heavy two-way activity looks identical to a quiet, directionless bar.
PulseWire's request.footprint() function changes this entirely. It exposes the actual buy and sell volume recorded at each price level (row) within the bar — the genuine transaction-level data that footprint chart platforms like Sierra Chart and Bookmap have historically required separate subscriptions and data feeds to access. The delta returned by fp.delta() is not an estimate. It is the arithmetic difference between actual ask-side and bid-side transactions aggregated across the bar.
This is the first time this data has been natively programmable in Pine Script, and IFDE is built specifically around it.
🔹 How It Works
🔸 Footprint Data and the Delta Fallback
On a Premium or Ultimate PulseWire account with a compatible symbol, request.footprint() returns a footprint object for each bar. IFDE calls fp.buy_volume() and fp.sell_volume() to get true directional volume, and fp.delta() for the bar's net delta. It also iterates every price row via fp.rows() and evaluates row.has_buy_imbalance() and row.has_sell_imbalance() — flagging bars where a disproportionate volume cluster exists at a specific price level, which often marks the precise price where institutional absorption occurred.
When footprint data is unavailable (standard account or non-supported symbol), the indicator falls back to a tick-estimated delta: up-close bars assign 100% of volume to the buy side; down-close bars assign 100% to the sell side; inside bars distribute proportionally based on close position within the range. This fallback is clearly flagged in the status label as ⚠️ ESTIMATED. The divergence logic functions identically in both modes — only the precision of the underlying delta changes.
The Ticks Per Footprint Row input controls the price granularity of the footprint: smaller values create more rows with finer resolution, larger values consolidate into fewer, broader rows. For index futures like ES and NQ, 4–10 ticks per row is typically appropriate. For crypto, you may need to experiment depending on the instrument's tick size.
🔸 Swing Pivot Detection
The indicator uses Pine's native ta.pivothigh() and ta.pivotlow() functions to identify confirmed swing highs and lows. The Swing Pivot Length input defines the lookback and lookahead symmetry of the pivot — a value of 10 means a bar must be the highest high within 10 bars on both sides to qualify as a pivot. Higher values find more significant structural swings but introduce more lag. Lower values are more responsive but noisier.
Critically, delta is sampled at the confirmed pivot bar using ta.valuewhen() — not at the current bar. This eliminates the most common repainting failure mode in divergence indicators: using the current bar's momentum reading to classify a past pivot. The delta value associated with each pivot is locked in the moment the pivot is confirmed.
🔸 Divergence Logic
Each time a new pivot high is confirmed, IFDE compares it against the previous confirmed pivot high. If the current price is higher but the current delta is lower, a bearish divergence is registered. The same comparison runs at pivot lows for bullish divergence, where current price lower and current delta less negative triggers the signal.
The Divergence Lookback setting controls the maximum bar distance between the two pivots being compared. Setting this too wide increases the chance of detecting structurally irrelevant comparisons — swings separated by 150 bars on a 5-minute chart may have no meaningful relationship. Setting it too tight misses legitimate multi-leg divergences. 40–60 bars is a reasonable starting point for most timeframes.
🔸 The ML Quality Score (0–100)
This is the engine's core differentiating feature. Every detected divergence is not displayed by default — it must first pass a composite quality score threshold. The score is calculated across five weighted dimensions:
Delta Magnitude is the most heavily weighted dimension by default (30%). It measures how extreme the opposing delta pressure is, normalised against the rolling maximum delta magnitude over the lookback window. A divergence where the delta is merely slightly less positive scores lower than one where the delta has completely reversed sign.
Volume Confirmation (25%) assesses whether total bar volume at the divergence pivot is above the 14-bar average. Low-volume divergences are structurally weaker — the absorption signal requires meaningful participation to be credible.
CVD Alignment (20%) checks whether the Cumulative Volume Delta — the running sum of all bar-level deltas, mean-reverted against its own moving average — is trending in the direction that supports the divergence. A bullish divergence at a price low carries far more weight when CVD has been quietly rising even as price made new lows.
Price Structure (15%) scores the magnitude of the price swing itself, relative to the current ATR. A divergence across a 0.5 ATR swing scores lower than one across a 2.5 ATR swing. Trivially small swings produce trivially meaningful divergence signals.
Regime Bonus (10%) applies a bonus or penalty based on the current volatility regime, described in detail below.
The weights are fully user-configurable in the 🤖 ML Score Weights input group. Shifting weight toward CVD Alignment, for example, will make the score more conservative and context-dependent. Shifting weight toward Delta Magnitude makes it more responsive to extreme single-bar order flow events. The scores are normalised internally so they always sum to 100 regardless of how you distribute the weights.
Only divergences scoring above the Min Quality Score threshold are displayed. The default of 55 is intentionally permissive to begin with. As you develop familiarity with the indicator on your instrument and timeframe, raising this to 65 or 70 will progressively filter toward only the highest-conviction setups.
🔸 Adaptive Regime Detection
The indicator compares the current 14-period ATR against its own simple moving average over the Regime Detection Period to classify the current volatility environment into three states: HIGH VOLATILITY, NORMAL, and LOW VOLATILITY.
In high volatility regimes, the score threshold is automatically scaled up by 20% — making it harder for a divergence to pass. This is because high-volatility environments produce frequent large delta swings that generate divergence signals with greater frequency but lower predictive value. The regime is tightening the filter precisely when noise is highest.
In low volatility regimes, the threshold is scaled down by 15%. Quiet, low-volatility markets are where institutional accumulation and distribution most commonly occurs under the radar — smaller delta contrasts carry more informational weight when total market activity is compressed.
The current regime and adjusted score floor are displayed in the status label in the top-left corner of the pane. A subtle background colour (green tint for low vol, red tint for high vol) is painted on the price chart to give continuous regime context at a glance.
🔸 The Pane Display
The indicator runs in its own pane below the price chart, containing three visual elements:
The delta histogram plots the smoothed EMA of bar-level delta as coloured columns — cyan for positive (net buying) and red for negative (net selling). The colour intensity scales with the magnitude of the delta relative to the recent maximum, so visually dominant bars correspond to the highest-conviction order flow readings.
The CVD deviation line in yellow shows the cumulative volume delta minus its moving average baseline. This is more useful than raw CVD for divergence context because it removes the secular trend in cumulative flow and focuses on relative shifts — making it easy to spot when CVD is rising or falling against price.
The zero line serves as the delta neutrality reference. Bars crossing from negative to positive delta, or vice versa, in the context of a divergence signal are particularly significant.
On the price chart, divergence lines connect the two pivot points being compared, with opacity scaling to score strength — higher-scoring divergences are rendered more vividly. Labels mark each divergence with its star rating (★ for score 55–69, ★★ for 70–84, ★★★ for 85–100) and the actual score value, along with whether live footprint data or tick estimation is in use.
🔹 Settings Reference
Swing Pivot Length — Controls pivot sensitivity. Lower = more signals, higher = more structural significance. Recommended: 8–15.
Divergence Lookback — Maximum bars between the two pivots being compared. Recommended: 30–75.
Min Quality Score — Score threshold below which divergences are hidden. Start at 55, tune upward as you calibrate to your instrument.
Ticks Per Footprint Row — Footprint granularity. Only relevant with live FP data. Tighter rows = more precision, more computation.
Delta Smoothing Period — EMA period applied to raw delta before divergence comparison. Smoothing reduces false triggers from single noisy bars. Recommended: 2–5.
CVD Baseline Length — Period of the SMA used to mean-revert the cumulative delta. Shorter = more responsive CVD; longer = smoother trend.
Alert Min Score — Score threshold for alert conditions. Set higher than the display threshold if you want alerts only for the strongest signals.
🔹 Closing Remarks
Delta divergence is one of the few conditions in technical analysis that has a genuinely defensible mechanical explanation rooted in market microstructure — it is not a pattern-matching heuristic but a direct observation of the imbalance between aggressive buying and selling pressure across a swing structure. The availability of native footprint data in Pine Script for the first time makes it possible to build this kind of tool without the estimations and approximations that have historically compromised order flow analysis within PulseWire.
That said, this indicator is a probabilistic model, not a signal generator. A score of 90 does not mean the trade works. It means the order flow context at that divergence was unusually well-structured relative to the five dimensions measured. Markets can and do continue trending through well-formed divergences, particularly in strongly trending regimes where institutional participants are not distributing but rather re-accumulating on every pullback.
The most effective use of IFDE is as a confluence filter — a condition that must be present alongside your existing structural, session, or macro framework before you engage a level. A bearish divergence at a weekly resistance level, in a high-volatility regime, scoring 82, with live footprint data showing 7 sell imbalance clusters, is a meaningfully different proposition than a 56-scoring divergence on estimated delta at a randomly selected intraday high.
Use the score. Respect the regime. Verify the data source. The rest is your edge.
🔹 References
Market Microstructure & Order Flow
Harris, L. (2003). Trading and Exchanges: Market Microstructure for Practitioners. Oxford University Press.
Cont, R., Stoikov, S., & Talreja, R. (2010). A stochastic model for order book dynamics. Operations Research, 58(3), 549–563.
Volume and Delta Analysis
Easley, D., & O'Hara, M. (1992). Time and the process of security price adjustment. Journal of Finance, 47(2), 577–605.
Easley, D., Hvidkjaer, S., & O'Hara, M. (2002). Is information risk a determinant of asset returns? Journal of Finance, 57(5), 2185–2221.
Institutional Order Flow & Smart Money
Chordia, T., Roll, R., & Subrahmanyam, A. (2002). Order imbalance, liquidity, and market returns. Journal of Financial Economics, 65(1), 111–130.
Grinblatt, M., & Keloharju, M. (2000). The investment behavior and performance of various investor types. Journal of Financial Economics, 55(1), 43–67. Indicator
CandelaCharts - HTF Footprint Candles📝 Overview
The CandelaCharts - HTF Footprint Candles is a professional-grade visualization tool that overlays High-Timeframe (HTF) candles onto your current chart while integrating a volume footprint profile. This gives traders the ability to analyze structural behavior and internal volume distribution of institutional candles without switching timeframes.
📦 Features
Multi-HTF Visualization : Display up to 60 historical HTF candles as ghost overlays on the active chart.
Volume Footprint Integration : Sourced from a Lower Timeframe (LTF) using request.security_lower_tf for granular precision.
Multiple Footprint Modes :
- POC + Voids : Highlights the Point of Control and areas of low volume.
- Delta : Visualizes net buying vs selling pressure.
- Total Volume : Relative volume intensity at each price level.
- Voids : Specifically targets "gap" areas in price action.
New York Midnight Anchor : Option to anchor HTF candles to the NY 00:00 open for consistent institutional session analysis.
Dynamic Labels : Auto-updating labels for HTF period, remaining time until candle close, and candle timestamps.
⚙️ Settings
🕒 Timeframe Control (Hierarchical Logic)
To ensure the drawings display correctly, you must understand the relationship between the three timeframes involved:
HTF (Higher Timeframe) : This is the timeframe of the "Ghost Candles" (e.g., 4H, Daily). It must be higher than your chart period.
Chart Timeframe : The timeframe you are currently looking at.
LTF (Lower Timeframe) : Found in the HTF I group as "LTF". This is the source for the footprint calculation.
- 💡 Crucial Note : Your Chart Timeframe must be equal to or higher than the LTF setting. If you view a 1m chart but have LTF set to 5m, the footprint cannot be calculated.
📊 LOT (Bin Size) Control
The Lot setting (found in the HTF I group) controls the vertical resolution of the footprint.
Definition : It represents the percentage of price movement that defines a single footprint "bin" or level.
Configuration :
- Volatile Assets (e.g., BTC/NVDA) : Use a higher Lot value (e.g., 0.05 or 0.1) to avoid creating too many bins.
- Stable Assets (e.g., EURUSD/Stablecoins) : Use a lower Lot value (e.g., 0.005 or 0.01) for more granularity.
- ⚠️ Warning : Setting the Lot too small on a highly volatile asset can exceed PulseWire's label limits, causing footprints to disappear or "evict" other chart annotations.
⚡️ Showcase
💎 Footprint Mode Presets
Point of Control (POC) : Highlights the single price level with the highest volume (Label count). Essential for spotting where the most trading activity occurred.
Delta : Displays net buyer vs seller pressure at each level. Positive delta shows buying aggression; negative delta shows selling aggression.
Total Volume : Visualizes the total activity at each price point, regardless of direction. Great for identifying high-activity ranges.
POC + Voids : A hybrid mode that shows both high-volume interest (POC) and low-volume gaps.
Voids : Specifically filters for "liquidity gaps"—price levels that the bar moved through so quickly that very little volume was transacted.
🚨 Alerts
The indicator includes on-chart warnings if your Timeframe settings are incompatible (e.g., Chart TF < LTF).
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Indicator
TickCharts [crlmx]Volume-based candlestick chart - each candle represents a fixed dollar volume, rather than a time interval. A configurable bar statistics table shows delta, CVD, and volume breakdowns per candle. Reveals market participation pace, institutional activity, and regime shifts through candle formation speed.
Key Features
Dollar volume threshold candles (default $1M)
Tick-accurate volume via PulseWire footprint API (Premium or above)
Bar statistics table with 6 configurable rows below candles
9 data types per row: Time, Volume, Delta, Buy, Sell, Delta %, Buy %, Sell %, Session CVD
Volume progress label showing dollar amount, threshold and percentage on the live candle
Streamlined input / UI brought to you by crlmx
Trading Applications
Volume candles compress during consolidation and expand during breakouts
Fast candle succession signals high participation; slow formation signals stalling
CVD tracks cumulative order flow direction across the visible range
Delta and CVD rows show buyer/seller dominance per candle
Recommended settings: Crypto (BTC/ETH): Candle Volume: $5M-$10M Index Futures (ES/NQ): Candle Volume: $1M-$2M
Commodities (Gold): Candle Volume: $500K-$1M
Version History
v0.42 (Latest - 07 Mar 2026)
Updated LTF Volume calculation to Footprint API
Added Bar statistics table with 6 configurable rows and 9 data types
Added row customisation Indicator
Footprint Data Test [Zofesu]Overview
Verify your Data Integrity with Institutional Precision.
This diagnostic tool is a professional-grade utility designed to verify if your current broker and symbol provide real-time Footprint Data (Intrabar Volume). In the world of high-stakes trading, especially when scalping Nasdaq or BTC, your strategies are only as good as the data feeding them. This script ensures your "data fuel" is active before you rely on complex Order Flow or Delta-based indicators.
Why this is Original and Useful
PulseWire's Public Library is filled with Order Flow indicators, but many traders fail to realize that their broker might not even provide the necessary tick-level data for these tools to function.
This script is unique because:
Direct Engine Access: It utilizes the latest Pine Script™ v6 request.footprint method to probe the exchange’s database directly.
Diagnostic Transparency: Instead of guessing why an indicator isn't plotting, this tool provides a clear "Green Light" status.
Educational Value: It bridges the gap between retail charting and institutional data requirements, helping traders understand the difference between simulated volume and real footprint distribution.
How it Works
The script attempts to request footprint data for the last 10 bars. In Pine Script™ v6, if the broker (e.g., certain CFD providers) does not support this data, the method returns na. The tool captures this state and translates it into a simplified UI.
Core Components
Status Table: A clean, non-intrusive UI element at the bottom center of your chart for instant diagnostics.
Data Active ✅: Confirms your broker provides real-time footprint/tick data. You can safely proceed with Order Flow and Volume Profile strategies.
No Data / Not Supported: Indicates the symbol or broker lacks the necessary granularity. Footprint-based indicators will not function correctly in this environment. Next to the indicator, at the top left, you will see a red exclamation point.
Strategic Application
Broker Verification: Compare data quality between different providers (e.g., IC Markets vs. Binance vs. CME).
Symbol Compatibility: Essential for testing Nasdaq (NQ), S&P 500 (ES), or Crypto pairs before deploying capital.
Data Subscriptions: If you see a red status on Indices, it often confirms the need for a "Real-Time Data Subscription" from the exchange. Switch time frames to see where the real data is. Indicator
Institutional absorption scoreInstitutional Absorption Score (IAS)
Institutions don't buy all at once they accumulate slowly, hiding their footprint inside boring, low-range candles with high volume. By the time the breakout is obvious, they're already in. This indicator tries to catch them in the act by scoring how much of that absorption is happening right now.
How It Works
The score runs from 0 to 100 and checks for these things -> Is volume elevated but the candle barely moved? Is the range tight relative to recent volatility? Someone's holding price in a zone. Are lows quietly stepping up even though the chart looks sideways?. Each of these gets weighted and combined into a single score.
Reading the Score
Red means nothing interesting is happening, move on. Orange is worth a second look but don't act yet. Yellow is where you start watching closely absorption is building. Green means multiple things are aligning and institutions are likely active. Lime is the serious zone — this is where breakouts tend to come from, often when most traders are still bored.
Settings
Lookback Period — how far back the indicator looks to define "normal" volume and volatility. Increase it on noisy assets, lower it if you want faster reactions.
Volume Multiplier — sets the bar for what counts as high volume. If your asset is naturally volatile, push this higher so random spikes don't inflate the score.
Max Body/Range Ratio — how small the candle body needs to be. Lower values mean only very indecisive candles count, which is stricter but more precise.
Max Range % of ATR — filters for compressed candles. If price is moving freely, it's not being absorbed — this setting enforces that.
Higher Lows Lookback — how many bars back to check for a higher low structure forming underneath.
Score Smoothing — irons out bar-to-bar noise. Crank it up if the score feels jumpy, lower it if you want to catch signals earlier. Indicator
Delta Strike: Order Flow Absorption & Momentum Confirmation**Delta Strike** is a professional-grade quantitative tool designed for traders who prioritize institutional logic over simple price action. It moves beyond traditional "buy/sell" indicators by dissecting the battle between **Passive Absorption** and **Aggressive Initiative** using underlying Order Flow data.
### 🛡️ The Core Philosophy: "Wait for the Trap, Trade the Escape"
Markets rarely reverse instantly. **Delta Strike** follows a rigorous two-step verification process to filter out noise and hunt for high-probability institutional footprints:
1. **Phase 1: Institutional Absorption (Left-Side Setup)**
The system identifies "Base Bars" where high volume and extreme Delta (passive buying/selling) occur, but price fails to continue. This indicates that a large player is absorbing the current move.
2. **Phase 2: Aggressive Strike (Right-Side Confirmation)**
We do not "catch the knife." Instead, the indicator monitors the next **N bars** for a confirmed strike. A signal is only triggered when price engulfs the base bar and is backed by a significant **Active Delta Percentage**, proving that the "absorber" has now become the "aggressor."
### 🚀 Key Technical Features
* **Dual-Cycle Volume Matrix**: Unlike standard indicators, Delta Strike analyzes volume across two lookback periods simultaneously (Short-term 20 & Long-term 50). It classifies setups into three categories:
* 🔥 **Dual-Cycle Convergence** (Maximum Strength)
* ⚡ **Short-term Spike** (Local Volatility)
* 🌊 **Macro Volume Surge** (Long-term Accumulation)
* **Active Delta Intensity Filter**: Every confirmation bar is evaluated for its "Net Win Ratio." By filtering out low-conviction, low-volume breakouts, it ensures you only follow moves with real institutional backing.
* **RSI Environment Guard**: Integrated RSI logic ensures that bottom absorption is only hunted in "Oversold" zones and top absorption in "Overbought" zones, significantly reducing whipsaws in sideways markets.
* **Validated SuperTrend (Delta-Sync)**: A modified SuperTrend algorithm that requires a "Delta Handshake." A trend flip is only considered valid if price and Delta move in the same direction, preventing "fake-outs" during low-liquidity periods.
### 📊 Clean & Actionable UI
* **Base Bar Highlight**: When a setup is confirmed, the script retroactively draws a **Yellow (Bullish)** or **Fuchsia (Bearish)** box around the original absorption bar.
* **Trace Lines**: Dashed lines connect the original institutional entry to your current entry point, providing immediate visual context for the trade's logic.
* **Momentum Rating (🐂/🐻)**:
* **3 Stars (🐂🐂🐂)**: Extreme Delta Strike (>20% Net Win).
* **2 Stars (🐂🐂)**: High Conviction Strike (>10% Net Win).
* **1 Star (🐂)**: Standard Confirmation.
### 🔔 Smart Alert System
Equipped with a fully customizable alert suite. You can set alerts for:
* **Absorption Confirmations** (Long/Short)
* **Validated SuperTrend Breakouts**
*Note: For the most accurate results, it is recommended to use "Any alert() function call" and set frequency to "Once Per Bar Close" to avoid repainting during intra-bar fluctuations.*
---
### How to use:
1. Look for the ** ** label and highlighted box.
2. Wait for the **Strike icons (🐂/🐻)** to appear within the N-bar window.
3. Combine with your existing Support/Resistance levels for optimal strike rates.
--- Indicator
Smart Trader, Concentric Candles & Aristotelian Cycloids
Smart Trader, Episode 05
Concentric Candles & Aristotelian Cycloids
by Ata Sabanci
The Spark — How a 2,000-Year-Old Paradox Found the Charts
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It started with a film about Aristotle's Wheel
Paradox — a problem that puzzled mathematicians
for two millennia. The setup is deceptively
simple: two circles, one inside the other, share
the same center and roll together along a
straight line. The outer circle traces a distance
equal to its circumference. But the inner circle,
attached rigidly to the outer, also travels the
same distance — yet its circumference is smaller.
How?
The answer lies in slipping . The inner circle
doesn't truly roll — it is dragged . And as it
moves, a point on its rim traces a beautiful
curve called a curtate cycloid — a compressed
wave that never reaches the full height of the
outer wheel's standard cycloid.
The moment I saw those curves being drawn in the
film — the elegant, rhythmic arches of the
cycloid — a thought struck me: what if this
geometry lives inside price charts too? What if
each candle, with its High, Low, Open, and Close,
could be mapped onto a rolling circle — and the
resulting cycloid curves could reveal hidden
structure in market behavior?
That question became this indicator.
The Problem — Why Raw Charts Break Geometry
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A financial chart has two axes that measure
completely different things : the horizontal
axis counts bars (time) , the vertical axis
measures price (currency) . Drawing a circle on
such a chart is meaningless — it stretches and
distorts with every zoom or rescale. A "circle"
on a 1-minute chart looks nothing like the same
"circle" on a daily chart.
To draw real geometry on a price chart, both
axes must speak the same language . I needed a
scientifically rigorous way to convert between
time and price — not an arbitrary ratio, but one
derived from the market itself.
The Bridge — Volatility-Diffusion Normalization (σ√t)
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The answer comes from the σ√t scaling law in
financial mathematics. Under Geometric Brownian
Motion, the standard deviation of log-returns
scales as the square root of time:
std(Δ ln P) = σ × √Δt
This means 1 bar of time is equivalent to
σ_bar units of log-price . Once you know σ_bar,
both axes measure the same thing. Geometry
becomes invariant — it doesn't distort with
zoom, timeframe, or instrument.
For σ_bar, I use the Yang-Zhang volatility
estimator — the most statistically efficient
single-bar estimator in the literature. It uses
all four OHLC prices plus the overnight gap
between consecutive bars, combining three variance
components into one optimal estimate. After
extensive testing, a lookback of 20 bars proved
to be the best balance between responsiveness and
stability for geometric calibration.
Candle Selection — Finding the Dominant Voices
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Not every candle deserves a rolling wheel. The
indicator selects maxima candles — candles whose
H−L range is strictly larger than their immediate
chronological predecessor. These represent
volatility expansion events — moments when the
market spoke louder than the bar before it.
Two selection methods work in parallel:
1. Predecessor-Comparison (M0, M1): The scanner
walks backward from the basis candle. At each
step, it compares a candle's range to its
predecessor. When it finds one that is strictly
larger, that candle becomes a maxima. Two are
found this way.
2. Period Largest (M2): A separate scan finds
the single biggest candle (by H−L range) within
the last N bars (default 20). If it differs from
M0 and M1, it's appended as a third maxima — the
"biggest voice in the room."
Live vs. Closed Basis: The user can choose
whether the scanner starts from the live candle
(real-time, updates every tick) or the last closed
candle (stable, confirmed data). This affects both
the backward scan starting point and the CVCA
contact detection basis.
The Geometry — Three Concentric Circles per Candle
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Each selected maxima candle defines three
concentric circles in the normalized space — all
sharing the same center (the geometric midpoint
of the candle):
Outer Circle — diameter = H − L (full candle
range). This is the primary rolling wheel. A point
at its apex (the High) traces a standard cycloid .
Upper Wick Circle — diameter = H − max(O, C)
(upper wick). This inner wheel is dragged by the
outer — it slips along the baseline (Aristotle's
paradox). Traces a curtate cycloid with reduced
amplitude.
Lower Wick Circle — diameter = min(O, C) − L
(lower wick). Also dragged. Also traces a curtate
cycloid.
How the candle maps to circles:
⊚ Outer circle: diameter = H − L (full range)
→ traces a standard cycloid
▲ Upper wick circle: diameter = H − max(O,C)
→ traces a curtate cycloid
▼ Lower wick circle: diameter = min(O,C) − L
→ traces a curtate cycloid
All three share the same center (candle midpoint).
The outer circle is the driving wheel. The two
inner circles are dragged — they slip along the
rolling surface (Aristotle's paradox in action).
Drawing these curves in Pine Script was itself a
challenge — there's no native circle or parametric
curve function. By defining the normalized
coordinate space (where 1 bar = σ_bar units of
log-price) and using polylines with a hybrid
Newton-Bisection root solver to invert x(θ) → θ
at each bar index, I was able to render the
cycloid curves directly on the price chart with
high fidelity.
The parametric equations for each curve follow the
two-radius Aristotle's Wheel formulation:
x(θ) = R·θ − r·sin(θ+φ₀) + r·sin(φ₀)
y(θ) = R − r·cos(θ+φ₀)
Where R = outer rolling radius, r = traced
point's circle radius, and φ₀ = π (apex start,
clockwise rolling). The inverse transform
price = exp(lnLow + y_norm × σ_bar) maps the
normalized cycloid back to the price chart —
geometry anchored at the candle's Low.
On the chart, the curves appear as follows:
⊚ Outer Apex (y = 2R): highest cycloid point
▲ Upper Pin Apex (y = R + r_up): curtate peak
▲ Upper Pin Trough (y = R − r_up): curtate min
⊚ Outer Trough (y = 0): the rolling surface
= candle's Low price
The outer cycloid arches from Low up to 2R and
back. The pin cycloids oscillate within the outer
envelope with reduced amplitude — visible as
nested waves inside the main curve.
The Signal — Cycloid-Volume Contact Analysis (CVCA)
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Drawing beautiful curves is one thing. The real
question is: what happens when price touches a
cycloid curve?
The CVCA engine detects real-time intersections
between the live candle and all active cycloid
curves. When contact is detected, it runs a
7-axis prediction matrix that combines geometry
with volume analysis:
Axis 1 — Contact Direction: Did the body cross
the curve? Did a wick test it? Five states: Passed
Up, Passed Down, Stopped, Wick Bounce, Wick
Reject.
Axis 2 — Curve Type: Which circle generated
this curve? Outer (strongest), Upper Pin, or Lower
Pin.
Axis 3 — Curve Zone: Is the contact near the
Apex (peak), Trough (bottom), or Mid-range of the
cycloid?
Axis 4 — Volume Magnitude: How does current
volume at the contact price compare to the maxima
candle's volume at the same price? Amplified,
Proportional, or Depleted.
Axis 5 — Delta Character: How has the buy/sell
imbalance changed since the maxima candle?
Continued, Weakened, or Flipped.
Axis 6 — Absorption Detection: Is heavy
opposing volume being absorbed while price holds?
Buy Absorption, Sell Absorption, or None.
Axis 7 — Multi-Cycloid Confluence: How many
other cycloid curves pass through the same price
level? Single, Double, or Triple+ confluence.
All seven axes feed into a continuous scoring
engine using logistic-sigmoid soft-clamping — no
hard thresholds, no cliff-edge label flips. The
output is a directional probability P(↑), a
conviction score, and a behavior classification
(Strong Bounce, Breakout, Exhaustion, Absorption,
Battle Zone, Delta Flip, Confluence Wall, and
more).
When footprint data is available (PulseWire
Premium/Ultimate), CVCA operates at tick-level
precision — comparing buy and sell volume at the
exact contact price row between the maxima candle
and the current candle. Without footprint, it
falls back to geometry-only analysis using the
first three axes.
Scientific Foundations
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This indicator draws on the following mathematical
and statistical frameworks:
• Geometric Brownian Motion — dS/S = μdt + σdW
— the σ√t diffusion scaling law that bridges
time and price axes.
• Yang-Zhang Volatility Estimator — Uses
O/H/L/C + overnight gaps; the most statistically
efficient single-bar σ estimator in the
literature.
• Rogers-Satchell Volatility — Drift-independent
variance component inside the Yang-Zhang
estimator.
• Aristotle's Wheel Paradox — Concentric circles
rolling together — the inner circle slips,
creating curtate cycloids.
• Cycloid Curves — Standard (outer) + curtate
(inner pin circles) — called the "Helen of
Geometry" by Galileo.
• Parametric Phase-Anchored Equations —
Two-radius cycloid:
x(θ)=Rθ−r·sin(θ+φ₀), y(θ)=R−r·cos(θ+φ₀).
• Hybrid Newton-Bisection Root Solver —
Numerical inversion of x(θ)→θ at each bar for
accurate curve rendering.
• Kyle-Obizhaeva Impact Law — σ√(Q/V) —
volume magnitude analysis for CVCA Axis 4.
• Easley-O'Hara PIN/VPIN — Delta as informed
trading proxy — CVCA Axis 5.
• Cont et al. (2014) OFI — Order Flow Imbalance
linear impact model — absorption detection in
CVCA Axis 6.
• Xu et al. (2019) MLOFI — Multi-Level Order
Flow Imbalance — confluence scoring for CVCA
Axis 7.
• Logistic Sigmoid Soft-Clamping — Continuous
scoring without cliff-edge thresholds — used
across all CVCA axes.
Architecture — How It All Connects
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The indicator processes data in the following
pipeline:
Stage 1: Raw Input
OHLC price data + volume arrive per bar.
Stage 2: Two Parallel Engines
→ Yang-Zhang σ_bar Estimator (Lookback = N):
Computes overnight variance, close-open
variance, and Rogers-Satchell variance.
Combines them into σ_bar.
→ Volume Engine (Geometric or Intrabar):
Splits total volume into buy/sell.
Stores per-bar for historical comparison.
Stage 3: Normalization
Converts axes: 1 bar = σ_bar, Y = ln(P) / σ.
Both axes now measure the same units.
Stage 4: Candle Selection
→ Predecessor-Comparison scan → M0, M1
→ Period-Largest scan → M2 (if unique)
Stage 5: Concentric Circles
Per maxima candle, 3 circles are defined:
⊚ Outer (H−L)
▲ Upper (H−max(O,C))
▼ Lower (min(O,C)−L)
Stage 6: Cycloid Math
Parametric equations + Newton-Bisection solver.
Phase φ₀ = π. Auto-revolutions extend curves
to the live bar.
Stage 7: Two Outputs
→ Polyline Render: 3 curves per Mi, bowl fill,
reference lines, geometric markers.
→ CVCA Engine: Contact detection, 7-axis
matrix, P(↑), conviction, behavior label.
Stage 8: Dashboard Table
Title + σ_bar info
Mi blocks (Offset, Length, Mid, Levels)
S/R Detection (Nearest Above/Below)
CVCA Contact Analysis (3-row layout)
Volume Engine (Buy/Sell/Delta/FP Status)
Settings Guide
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Core Settings
σ_bar Lookback Period: Rolling window for the
Yang-Zhang volatility estimator. Controls how many
bars are used to compute σ_bar — the bridge
between time and price axes. Larger values produce
more robust geometric calibration but respond
slower to regime changes. Default: 20.
Range: 1–2500.
Cycloid Display
Show Outer/Upper/Lower Traces: Toggle
visibility of each of the three concentric cycloid
curves. The Outer (H−L) is the primary rolling
wheel — the strongest geometric curve. Upper and
Lower Pin curves trace the wick circles and show
internal candle structure.
Show Period Largest Candle: Enables the
period-based maxima scanner (M2). Scans the last N
bars for the single biggest candle. If it already
matches M0 or M1, no duplicate is drawn.
Period Lookback Length: Number of bars to scan
for the period-based largest candle. Default: 20.
Range: 5–200.
Show Reference Lines: Draws horizontal dashed
lines at cycloid apex and trough levels — the
geometric S/R framework. Six individual toggles
control which levels are drawn: Outer Apex (2R),
Outer Trough (0), Upper Pin Apex/Trough, Lower
Pin Apex/Trough.
Curve Color — Above/Below Price: When the
Outer Apex level is above current close, all
curves for that maxima use the "Above" color
(default: orange). When below, they use the
"Below" color (default: cyan). This gives an
instant visual read of the curve's S/R context.
Volume Engine
Calculation Method: Two engines — Geometric
(estimates buy/sell from OHLC price action) and
Intrabar (uses lower timeframe tick data via
PulseWire's ta library for precise
decomposition).
Intrabar Timeframe: Lower timeframe for
precise volume calculation. Only active in Intrabar
mode. 15S (15-second) recommended for most
instruments.
Calculation Basis: Current Candle uses live bar
data. Closed Candle uses only the last confirmed
bar — more stable, avoids intrabar noise.
Footprint & Contact Analysis
Show Contact Analysis (CVCA): Enables the
7-axis prediction engine in the dashboard. Detects
cycloid curve intersections and outputs directional
probability, conviction score, and behavior
classification. Requires PulseWire
Premium or Ultimate for full footprint data; falls
back to Volume Engine data when footprint is
unavailable.
Dashboard Settings
Show Dashboard: Projects the full data
dashboard onto the main price chart. Shows σ_bar
info, all Mi blocks with reference levels, S/R
detection, CVCA contact analysis, and volume
metrics.
Dashboard Position: Four corners: Top Right
(default), Top Left, Bottom Right, Bottom Left.
Dashboard Language: English, Türkçe, or
العربية. Full localization of all labels,
tooltips, and natural-language sentences.
Show Mi Reference Prices: Expands each Mi
block in the dashboard to show all 6 reference
price levels (3 apex + 3 trough). Default: OFF to
keep the dashboard compact.
A Theory, Not a System — An Invitation to Explore
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
This indicator is a theoretical exploration ,
not a proven trading system. The idea that
Aristotle's Wheel geometry maps meaningfully onto
price structure is a hypothesis — one that I
find compelling enough to build, share, and test
publicly, but one that requires far more data,
analysis, and community scrutiny to validate or
refute.
I chose to publish it on PulseWire precisely
because this platform is a living laboratory —
constantly moderated, reviewed, and challenged by
a global community of traders, developers, and
analysts. If the cycloid geometry holds predictive
value, this community will find it. If it doesn't,
this community will expose it.
Use this indicator as a research tool, not as a
signal generator. Combine it with your own
analysis. Question its assumptions. Test it across
instruments and timeframes. And if you discover
something — share it.
The mathematics is beautiful. Whether the market
agrees is an open question.
Indicator
Absorption BubblesSUMMARY
This indicator visualizes absorption events by plotting bubbles on candle wicks where volume activity suggests one side of the market is absorbing the other’s pressure. Instead of raw volume, the script normalizes activity against a rolling standard deviation defined by the Lookback Period. Bubbles appear on upper or lower wicks depending on whether buyers or sellers are absorbing pressure. The goal is to highlight whether aggressive orders are being accepted or absorbed at key price points.
METHODOLOGY
Absorption occurs when one side of the market absorbs aggressive orders from the other, preventing continuation. The script measures normalized volume against a user‑defined threshold to filter out weaker signals.
Green bubbles on upper wicks → Selling absorption (buyers push price up, sellers absorb the buying).
Red bubbles on lower wicks → Buying absorption (sellers push price down, buyers absorb the selling).
Red‑colored bars highlight candles where large volume is concentrated inside the body, signifying aggressive selling activity.
Green‑colored bars highlight candles where large volume is concentrated inside the body, signifying aggressive buying activity.
The Lookback Period controls how many bars are used to calculate the rolling standard deviation of volume, letting traders adjust sensitivity to recent vs. longer‑term activity. Optional significant volume lines extend forward, marking areas where absorption was strongest.
FUNCTIONS
Normalized volume detection using rolling standard deviation
Adjustable Lookback Period for volume normalization
Dynamic bubble plotting on candle wicks (size scales with absorption strength)
Separate visualization for buying vs. selling absorption
Alerts for buying absorption, selling absorption, or any absorption event (only at bar close)
Bar coloring when large absorption occurs inside candle bodies
APPLICATION
Setup: Add the script to any chart and timeframe. Adjust the Absorption Threshold to filter out weaker bubbles and the Lookback Period to control how volume normalization is calculated. Red bubbles highlight buying absorption, often signalling potential price pivots - price can often go upwards from this. Green bubbles mark selling absorption, reflecting resistance to upward moves - price may go downwards from this.
Interpretation:
Green bubbles on upper wicks = sellers absorbing buying pressure.
Red bubbles on lower wicks = buyers absorbing selling pressure.
Larger bubbles = stronger absorption relative to recent volume.
Settings & Use:
Raising the Absorption Threshold filters out smaller bubbles, leaving only significant absorption events.
Changing the Lookback Period alters how “normal” volume is defined — shorter periods make the script more sensitive, longer periods smooth out noise.
Alerts can be set for buying absorption, selling absorption, or any absorption event, and they only trigger at bar close to avoid noise. Indicator
Orderblock Footprints [AlgoAlpha]🟠 OVERVIEW
This script highlights orderblocks and then drills into what actually trades inside them. Zones are created only after an abnormal directional impulse, measured with a z-score on consecutive candle bodies, so the orderblocks are tied to real expansion rather than simple pivots. Once a zone exists, the script overlays lower-timeframe volume footprints inside the candle when price trades back into that zone. The goal is to show not just where an orderblock sits, but whether price is being accepted or absorbed when it is revisited.
🟠 CONCEPTS
Orderblocks are detected after extreme bullish or bearish impulses. The script tracks consecutive body movement up or down, normalizes that distance with a rolling z-score, and only triggers when the move is statistically large. The last opposite candle before that impulse defines the orderblock range. These zones then extend forward until they are either mitigated by price closing through them or they expire by age.
Inside an active zone, the script switches to a lower timeframe and builds a footprint-style profile for each bar. Each candle is split into price rows, counting time-at-price and volume delta. Positive and negative delta are colored separately. Absorption is flagged when opposing delta prints appear in the wick that rejects the zone. In practice: the impulse defines context ; the footprint shows interaction .
🟠 FEATURES
Separate bullish and bearish zones with automatic extension
Volume split inside each zone candle (up vs down volume)
Lower-timeframe footprint with TPO-style rows and delta gradient
Absorption detection using opposing delta in rejection wicks
Alerts for zone creation and absorption events
🟠 USAGE
Setup : Add the script to your chart. It works on any market and timeframe. The lower timeframe for footprints is fixed at 5 minutes, so higher chart timeframes show clearer structure. Use the Z-Score Window to control how strict impulse detection is and Max Box Age to limit how long old zones stay on the chart.
Read the chart : Bullish orderblocks are created after strong upward impulses and are invalidated when price closes below them. Bearish orderblocks are created after strong downward impulses and are invalidated when price closes above them. When price trades inside a zone, footprint rows appear. Green-tinted rows show positive delta; red-tinted rows show negative delta. Absorption labels appear when opposing delta prints into a rejecting wick.
Settings that matter : Increasing the Z-Score Window makes orderblocks rarer but more significant. Disabling Prevent Overlap allows stacked zones if you want to study clustering. Adjusting Rows per bar changes footprint resolution—lower values are cleaner, higher values show more detail but use more objects.
Indicator
Indicator
Open Interest Footprint IQ [TradingIQ]Hello Traders!
Th e Open Interest Footprint IQ indicator is an advanced visualization tool designed for cryptocurrency markets. It provides a granular, real-time breakdown of open interest changes across different price levels, allowing traders to see how aggressive market participation is distributed within each bar.
Unlike standard footprint charts that rely solely on volume, this indicator offers unique insights by focusing on the interaction between price action and changes in open interest (OI) — a leading metric often used to infer trader intent and positioning.
How it works
The Open Interest Footprint IQ processes lower timeframe price and open interest data to build a footprint-style chart that shows how traders are positioning themselves within each candle.
Here’s a breakdown of the process:
1. Granular OI & Price Sampling
The script retrieves lower-timeframe data (1-minute, 1-second, or 1-tick, based on your setting).
For each candle, it captures:
High and low prices
Price change direction
Change in open interest (OI)
2. Classifying Trader Behavior
For each lower-timeframe segment, the indicator determines the type of positioning occurring based on price movement and OI change:
If price is moving up and open interest is increasing, it suggests that long positions are being opened. This is considered a "Longs Opening" event, labeled as UU (Up/Up).
If price is moving up but open interest is decreasing, it indicates that short positions are being closed. This is referred to as UD (Up/Down), or "Shorts Closing."
If price is moving down and open interest is increasing, it signals that short positions are being opened. This is known as DU (Down/Up), or "Shorts Opening."
If price is moving down while open interest is also decreasing, it means that long positions are being closed. This is labeled as DD (Down/Down), or "Longs Closing."
These are stored in separate arrays and displayed at specific price levels.
It is particularly useful for identifying:
Where longs or shorts are opening/closing positions
Stacked imbalances (indicative of potential absorption or exhaustion)
Value area zones and POC (Point of Control) based on OI, not volume
This footprint runs on your choice of sub-bar granularity and is ideal for high-frequency trading, scalping, and entries based on order flow dynamics.
Key Features
Footprint Visualization
At each price level within a candle:
Long/short opening and closing behavior is broken down.
Delta (net open interest change) is displayed both numerically and color-coded.
Optional gradient coloring shows intensity and type of flow (longs/shorts opened/closed).
Cumulative or per-bar reset modes allow you to track OI evolution over time.
The image above explains the information that each Footprint box shows across a candlestick!
Each footprint box shows:
OI Delta
OI Delta %
Longs Opened (LO)
Longs Closed (LC)
Shorts Opened (SO)
Shorts Closed (SC)
The image above explains the color-coding feature of the indicator.
Boxes are color coded to show which position action
dominated at the price area.
For this example:
Green boxes = Long positions being opened dominated
Purple boxes = Long positions being closed dominated
Red boxes = Short positions being opened dominated
Yellow boxes = Short positions being closed dominated
All colors are customizable.
Additionally, for traders who are only interested in whether OI increased/decreased, a "two-color" option is available in the settings.
For the two-color option, footprint boxes can be one of two colors. Showing whether OI increased or decreased at the level.
Cumulative Levels
Open Interest Footprint IQ contains a "Cumulative Levels" feature that tracks/stores open interest change at tick levels over time, rather than resetting per bar.
With the "Cumulative Levels" feature enabled, traders can see open interest changes persist across all candlesticks. This feature is useful for determining whether longs opening, longs closing, shorts opening, or shorts closing are dominating at particular price areas over time rather than on a single bar.
A useful feature to see if shorts/longs are favoring certain price throughout the day, week, month, etc.
Input Settings Explained
Granularity (Dropdown: Granularity)
Options: 1-Minute, 1-Second, 1-Tick
Determines how finely the script samples the lower timeframe data to construct the footprint.
For precision:
1-Tick = Highest accuracy, but more resource-intensive.
1-Second/1-Minute = Suitable for broader or more zoomed-out analysis.
Tick Level Distance (Tick Level Distance (0 = Auto))
Defines the vertical spacing between levels in the footprint chart.
If 0, the script uses an automatic calculation based on ATR to adapt to volatility.
Set a manual value (e.g., 5) to control the height granularity of each level in ticks.
Cumulative Levels (Toggle)
If enabled, the footprint builds cumulatively over time, rather than resetting per candle.
Use case: Visualize ongoing buildup of OI activity across a session or day.
Cumulative Levels Reset TF (Timeframe)
Sets the reset interval for the cumulative view (e.g., reset daily, hourly, etc.)
Works only when Cumulative Levels is enabled.
Delta Box Display Settings
Show Delta Percentage
Toggles the display of the percentage change in OI across the footprint level.
Helpful to gauge how aggressive positioning is relative to total OI at that level.
Show Longs/Shorts (Opened/Closed)
Show Longs Opened: Displays OI increase in up candles (price ↑, OI ↑).
Show Longs Closed: Displays OI decrease in down candles (price ↓, OI ↓).
Show Shorts Opened: OI increase in down candles (price ↓, OI ↑).
Show Shorts Closed: OI decrease in up candles (price ↑, OI ↓).
These behaviors are color-coded to give traders instant context:
Blue-green for longs opening.
Purple for longs closing.
Red for shorts opening.
Yellow for shorts closing.
Value Area & POC
Value Area % (Value Area %)
Controls how much cumulative open interest is used to define the value area.
Example: 70% means the smallest range of prices that contains 70% of total OI in that bar will be marked.
Helps identify zones of interest, support/resistance, and institutional levels.
The image above explains how to identify the VAH/VAL/POC shown by Open Interest Footprint IQ.
VAH = Upper 🞂
POC = ●
VAL = Lower 🞂
Imbalances
Imbalance Percentage
Defines the minimum delta % required at a level to be marked as an imbalance.
If the net open interest change at a level exceeds this threshold, a visual marker appears.
Stacked Imbalance Count
If the number of consecutive imbalance levels meets this count, a “Stacked Imbalance” alert will trigger.
This can signal aggressive buying or selling pressure, potential breakout zones, or institutional absorption.
Color Settings
Longs Opened / Closed, Shorts Opened / Closed
Customize the color palette for each order flow behavior.
These colors appear in the background gradient of the footprint boxes.
Up/Down Only Mode
Toggle to override all behavior-based colors with a single Up Color and Down Color.
Useful if you prefer a simple bull/bear view.
Up Color / Down Color
If "Up/Down Only" is enabled, these two colors are used to represent all net positive or negative deltas.
Special Notes
Crypto only: This script works only with crypto tickers on PulseWire.
For other assets (stocks, futures), a warning message will appear instead.
OI data must be available from the exchange (many perpetual pairs support this).
If the footprint is too small or invisible, increase your tick level spacing in the settings.
Alerts
When a stacked imbalance is detected, an alert is fired ("Stacked Imbalance").
This feature is useful for automated systems, bots, or simply staying informed of potential trade setups.
And that's all for now!
If you have any questions or features you'd like to see feel free to share them in the comments below!
Thank you traders!
Indicator
Footprint IQ Pro [TradingIQ]Hello Traders!
Introducing "Footprint IQ Pro"!
Footprint IQ Pro is an all-in-one Footprint indicator with several unique features.
Features
Calculated delta at tick level
Calculated delta ratio at tick level
Calculated buy volume at tick level
Calculated sell volume at tick level
Imbalance detection
Stacked imbalance detection
Stacked imbalance alerts
Value area and POC detection
Highest +net delta levels detection
Lowest -net delta levels detection
CVD by tick levels
Customizable values area percentage
The image above thoroughly outlines what each metric in the delta boxes shows!
Metrics In Delta Boxes
"δ:", " δ%:", " ⧎: ", " ◭: ", " ⧩: "
δ Delta (Difference between buy and sell volume)
δ% Delta Ratio (Delta as a percentage of total volume)
⧎ Total Volume At Level (Total volume at the price area)
◭ Total Buy Volume At Level (Total buy volume at the price area)
⧩ Total Sell Volume At Level (total sell volume at the price area)
Each metric comes with a corresponding symbol.
That said, until you become comfortable with the symbol, you can also turn on the descriptive labels setting!
The image above exemplifies the feature.
The image above shows Footprint IQ's full power!
Additionally, traders with an upgraded PulseWire plan can make use of the "1-Second" feature Footprint IQ offers!
The image above shows each footprint generated using 1-second volume data. 1-second data is highly granular compared to 1-minute data and, consequently, each footprint is exceptionally more accurate!
Imbalance Detection
Footprint IQ pro is capable of detecting user-defined delta imbalances.
The image above further explains how Footprint IQ detects imbalances!
The imbalance percentage is customizable in the settings, and is set to 70% by default.
Therefore,
When net delta is positive, and the positive net delta constitutes >=70% of the total volume, a buying imbalance will be detected (upwards triangle).
When net delta is negative, and the negative net delta constitutes >=70% of the total volume, a buying imbalance will be detected (downwards triangle).
Stacked Imbalance Detection
In addition to imbalance detection, Footprint IQ Pro can also detect stacked imbalances!
The image above shows Footprint IQ Pro detecting stacked imbalances!
Stacked imbalances occur when consecutive imbalances at sequential price areas occur. Stacked imbalances are generally interpreted as significant price moves that are supported by volume, rather than a significant result with disproportionate effort.
The criteria for stacked imbalance detection (how many imbalances must occur at sequential price areas) is customizable in the settings.
The default value is three. Therefore, when three imbalances occur at sequential price areas, golden triangles will begin to print to show a stacked imbalance.
Additionally, traders can set alerts for when stacked imbalances occur!
Highest +Delta and Highest -Delta Levels
In addition to being a fully-fledged Footprint indicator, Footprint IQ Pro goes one step further by detecting price areas where the greater +Delta and -Delta are!
The image above shows price behavior near highest +Delta price areas detected by Footprint IQ!
These +Delta levels are considered important as there has been strong interest from buyers at these price areas when they are traded at.
It's expected that these levels can function as support points that are supported by volume.
The image above shows a similar function for resistance points!
Blue lines = High +Delta Detected Price Areas
Red lines = High -Delta Detected Price Areas
Value Area Detection
Similar to traditional volume profile, Footprint IQ Pro displays the value area per bar.
Green lines next to each footprint show the value area for the bar. The value area % is customizable in the settings.
CVD Levels
Footprint IQ Pro is capable of storing historical volume delta information to provide CVD measurements at each price area!
The image above exemplifies this feature!
When this feature is enabled, you will see the CVD of each price area, rather than the net delta!
And that's it!
Thank you so much to PulseWire for offering the greatest charting platform for everyone to create on!
If you have any feature requests you'd like to see for Footprint IQ, please feel free to share them with us!
Thank you!
Indicator
Indicator
Real-Time HTF Volume Footprint [BigBeluga]Real-time HTF Volume Footprint Profile is designed to provide a comprehensive view of higher timeframe volume profiles on your current chart. It overlays critical volume information from larger timeframes (like daily, weekly, or monthly) onto lower timeframe charts, helping you spot significant levels where volume is concentrated, acting as potential support or resistance.
🔵 Key Features:
HTF High and Low Zones: The indicator highlights the high and low of the chosen higher timeframe with clear zones, marking them with boxes. These zones help you see the broader market structure at a glance.
Volume Profile within HTF Range: Each higher timeframe range displays a volume profile, showing the distribution of volume at each price level. The most-traded price is highlighted in blue, known as the Point of Control (POC), indicating the price level with the highest activity.
Dynamic POC Option: Activate Dynamic POC to observe how the Point of Control shifts over time, giving insight into changing market interests and potential price direction.
Timeframe Flexibility: Select from daily, weekly, and monthly ranges (and more) to overlay their footprint profiles on your lower timeframe chart. This helps you tailor the indicator to the trading horizon that suits your strategy.
Info Table: Table shows a traders which timeframe is selected with last high and low of the selected timeframe
Visual Clarity with Custom Colors: The indicator uses subtle fills and distinct colors to ensure volume profile data integrates seamlessly into your chart without overwhelming other indicators or price data.
🔵 When to Use:
The HTF Volume Footprint Profile is essential for traders who want to bridge the gap between high-timeframe and intraday analysis. By visualizing HTF volume distribution on lower timeframes, this tool helps you:
Spot potential liquidity zones where price might react.
Identify support and resistance levels within HTF ranges.
Monitor PoC shifts that indicate changes in market behavior.
Track how current price aligns with significant volume clusters, providing a clear edge for volume-based strategies.
This indicator empowers traders to analyze lower timeframes with the context of higher timeframe volume profiles, providing a solid basis for identifying critical support and resistance levels shaped by large volume clusters. Whether you’re looking to spot liquidity zones or align your trades with broader market trends, HTF Volume Footprint Profile equips you with a strategic view. Indicator
Volume Delta Candles HTF [TradingFinder] LTF Volume Candles 🔵 Introduction
In financial markets, understanding the concepts of supply and demand and their impact on price movements is of paramount importance. Supply and demand, as fundamental pillars of economics, reflect the interaction between buyers and sellers.
When buyers' strength surpasses that of sellers, demand increases, and prices tend to rise. Conversely, when sellers dominate buyers, supply overtakes demand, causing prices to drop. These interactions play a crucial role in determining market trends, price reversal points, and trading decisions.
Volume Delta Candles offer traders a practical way to visualize trading activity within each candlestick. By integrating data from lower timeframes or live market feeds, these candles eliminate the need for standalone volume indicators.
They present the proportions of buying and selling volume as intuitive colored bars, making it easier to interpret market dynamics at a glance. Additionally, they encapsulate critical metrics like peak delta, lowest delta, and net delta, allowing traders to grasp the market's internal order flow with greater precision.
In financial markets, grasping the interplay between supply and demand and its influence on price movements is crucial for successful trading. These fundamental economic forces reflect the ongoing balance between buyers and sellers in the market.
When buyers exert greater strength than sellers, demand dominates, driving prices upward. Conversely, when sellers take control, supply surpasses demand, and prices decline. Understanding these dynamics is essential for identifying market trends, pinpointing reversal points, and making informed trading decisions.
Volume Delta Candles provide an innovative method for evaluating trading activity within individual candlesticks, offering a simplified view without relying on separate volume indicators. By leveraging lower timeframe or real-time data, this tool visualizes the distribution of buying and selling volumes within a candle through color-coded bars.
This visual representation enables traders to quickly assess market sentiment and understand the forces driving price action. Buyer and seller strength is a critical concept that focuses on the ratio of buying to selling volumes. This ratio not only provides insights into the market's current state but also serves as a leading indicator for detecting potential shifts in trends.
Traders often rely on volume analysis to identify significant supply and demand zones, guiding their entry and exit strategies. Delta Candles translate these complex metrics, such as Maximum Delta, Minimum Delta, and Final Delta, into an easy-to-read visual format using Japanese candlestick structures, making them an invaluable resource for analyzing order flows and market momentum.
By merging the principles of supply and demand with comprehensive volume analysis, tools like the indicator introduced here offer unparalleled clarity into market behavior. This indicator calculates the relative strength of supply and demand for each candlestick by analyzing the ratio of buyers to sellers.
🔵 How to Use
The presented indicator is a powerful tool for analyzing supply and demand strength in financial markets. It helps traders identify the strengths and weaknesses of buyers and sellers and utilize this information for better decision-making.
🟣 Analyzing the Highest Volume Trades on Candles
A unique feature of this indicator is the visualization of price levels with the highest trade volume for each candlestick. These levels are marked as black lines on the candles, indicating prices where most trades occurred. This information is invaluable for identifying key supply and demand zones, which often act as support or resistance levels.
🟣 Trend Confirmation
The indicator enables traders to confirm bullish or bearish trends by observing changes in buyer and seller strength. When buyer strength increases and demand surpasses supply, the likelihood of a bullish trend continuation grows. Conversely, decreasing buyer strength and increasing seller strength may signal a potential bearish trend reversal.
🟣 Adjusting Timeframes and Calculation Methods
Users can customize the indicator's candlestick timeframe to align with their trading strategy. Additionally, they can switch between moving average and current candle modes to achieve more precise market analysis.
This indicator, with its accurate and visual data display, is a practical and reliable tool for market analysts and traders. Using it can help traders make better decisions and identify optimal entry and exit points.
🔵 Settings
Lower Time Frame Volume : This setting determines which timeframe the indicator should use to identify the price levels with the highest trade volume. These levels, displayed as black lines on the candlesticks, indicate prices where the most trades occurred.
It is recommended that users align this timeframe with their primary chart’s timeframe.
As a general rule :
If the main chart’s timeframe is low (e.g., 1-minute or 5-minute), it is better to keep this setting at a similarly low timeframe.
As the main chart’s timeframe increases (e.g., daily or weekly), it is advisable to set this parameter to a higher timeframe for more aligned data analysis.
Cumulative Mode :
Current Candle : Strength is calculated only for the current candlestick.
EMA (Exponential Moving Average) : The strength is calculated using an exponential moving average, suitable for identifying longer-term trends.
Calculation Period : The default period for the exponential moving average (EMA) is set to 21. Users can modify this value for more precise analysis based on their specific requirements.
Ultra Data : This option enables users to view more detailed data from various market sources, such as Forex, Crypto, or Stocks. When activated, the indicator aggregates and displays volume data from multiple sources.
🟣 Table Settings
Show Info Table : This option determines whether the information table is displayed on the chart. When enabled, the table appears in a corner of the chart and provides details about the strength of buyers and sellers.
Table Size : Users can adjust the size of the text within the table to improve readability.
Table Position : This setting defines the table’s placement on the chart.
🔵 Conclusion
The indicator introduced in this article is designed as an advanced tool for analyzing supply and demand dynamics in financial markets. By leveraging buyer and seller strength ratios and visually highlighting price levels with the highest trade volume, it aids traders in identifying key market zones.
Key features, such as adjustable analysis timeframes, customizable calculation methods, and precise volume data display, allow users to tailor their analyses to market conditions.
This indicator is invaluable for analyzing support and resistance levels derived from trade volumes, enabling traders to make more accurate decisions about entering or exiting trades.
By utilizing real market data and displaying the highest trade volume lines directly on the chart, it provides a precise perspective on market behavior. These features make it suitable for both novice and professional traders aiming to enhance their analysis and trading strategies.
With this indicator, traders can gain a better understanding of supply and demand dynamics and operate more intelligently in financial markets. By combining volume data with visual analysis, this tool provides a solid foundation for effective decision-making and improved trading performance. Choosing this indicator is a significant step toward refining analysis and achieving success in complex financial markets.
Indicator
Volume / Open Interest "Footprint" - By LeviathanThis script generates a footprint-style bar (profile) based on the aggregated volume or open interest data within your chart's visible range. You can choose from three different heatmap visualizations: Volume Delta/OI Delta, Total Volume/Total OI, and Buy vs. Sell Volume/OI Increase vs. Decrease.
How to use the indicator:
1. Add it to your chart.
2. The script will use your chart's visible range and generate a footprint bar on the right side of the screen. You can move left/right, zoom in/zoom out, and the bar's data will be updated automatically.
Settings:
- Source: This input lets you choose the data that will be displayed in the footprint bar.
- Resolution: Resolution is the number of rows displayed in a bar. Increasing it will provide more granular data, and vice versa. You might need to decrease the resolution when viewing larger ranges.
- Type: Choose between 3 types of visualization: Total (Total Volume or Total Open Interest increase), UP/DOWN (Buy Volume vs Sell Volume or OI Increase vs OI Decrease), and Delta (Buy Volume - Sell Volume or OI Increase - OI Decrease).
- Positive Delta Levels: This function will draw boxes (levels) where Delta is positive. These levels can serve as significant points of interest, S/R, targets, etc., because they mark the zones where there was an increase in buy pressure/position opening.
- Volume Aggregation: You can aggregate volume data from 8 different sources. Make sure to check if volume data is reported in base or quote currency and turn on the RQC (Reported in Quote Currency) function accordingly.
- Other settings mostly include appearance inputs. Read the tooltips for more info. Indicator
Indicator
Indicator
Realtime FootprintThe purpose of this script is to gain a better understanding of the order flow by the footprint. To that end, i have added unusual features in addition to the standard features.
I use "Real Time 5D Profile by LucF" main engine to create basic footprint(profile type) and added some popular features and my favorites.
This script can only be used in realtime, because pulsewire doesn't provide historical Bid/Ask date.
Bid/Ask date used this script are up/down ticks.
This script can only be used by time based chart (1m, 5m , 60m and daily etc)
This script use many labels and these are limited max 500, so you can't display many bars.
If you want to display foot print bars longer, turn off the unused sub-display function.
Default setting is footprint is 25 labels, IB count is 1, COT high and Ratio high is 1, COT low and Ratio low is 1 and Delta Box Ratio Volume is 1 , total 29.
plus UA , IB stripes , ladder fading mark use several labels.
///////// General Setting ///////////
Resets on Volume / Range bar
: If you want to use simple time based Resets on, please set Total Volume is 0.
Your timeframe is always the first condition. So if you set Total Volume is 1000, both conditions(Volume >= 1000 and your timeframe start next bar) must be met. (that is, new footprint bar doesn't start at when total volume = exactly 1000).
Ticks per row and Maximum row of Bar
: 1 is minimum size(tick). "Maximum row of Bar" decide the number of rows used in one footprint. 1 row is created from 1 label, so you need to reduce this number to display many footprints (Max label is 500).
Volume Filter and For Calculation and Display
: "Volume Filter" decide minimum size of using volume for this script.
"For Calculation and Display" is used to convert volume to an integer.
This script only use integer to make profile look better (I contained Bid number and Ask number in one row( one label) to saving labels. This require to make no difference in width by the number of digits and this script corresponds integers from 0 to 3 digits).
ex) Symbol average volume size is from 0.0001 to 0.001. You decide only use Volume >= 0.0005 by "Volume Filter".
Next, you convert volume to integer, by setting "For Calculation and Display" is 1000 (0.0005 * 1000 = 5).
If 0.00052 → 5.2 → 5, 0.00058 → 5.8 → 6 (Decimal numbers are rounded off)
This integer is used to all calculation in this script.
//////// Main Display ///////
Footprint, Total, Row Delta, Diagonal Delta and Profile
: "Footprint" display Ask and Bid per row. "Total" display Ask + Bid per row.
"Row Delta" display Ask - Bid per row. "Diagonal Delta" display Ask(row N) - Bid(row N -1) per row.
Profile display Total Volume(Ask + Bid) per row by using Block. Profile Block coloring are decided by Row Delta value(default: positive Row Delta (Ask > Bid) is greenish colors and negative Row Delta (Ask < Bid) is reddish colors.)
Volume per Profile Block, Row Imbalance Ratio and Delta Bull/Bear/Neutral Colors
: "Volume per Profile Block" decide one block contain how many total volume.
ex) When you set 20, Total volume 70 display 3 block.
The maximum number of blocks that can be used per low is 20.
So if you set 20, Total volume 400 is 20 blocks. total volume 800 is 20 blocks too.
"Row Imbalance Ratio" decide block coloring. The row imbalance is that the difference between Ask and Bid (row delta) is large.
default is x3, x2 and x1. The larger the difference, the brighter the color.
ex) Ask 30 Bid 10 is light green. Ask 20 Bid 10 is green. Ask 11 Bid 10 is dark green.
Ask 0 Bid 1 is light red. Ask 1 Bid 2 is red. ask 30 Bid 59 is dark green.
Ask 10 Bid 10 is neutral color(gray)
profile coloring is reflected same row's other elements(Ask, Bid, Total and Delta) too.
It's because one label can only use one text color.
/////// Sub Display ///////
Delta, total and Commitment of Traders
: "Delta" is total Ask - total Bid in one footprint bar. Total is total Ask + total Bid in one footprint bar.
"Commitment of traders" is variation of "Delta". COT High is reset to 0 when current highest is touched. COT Low is opposite.
Basic concept of Delta is to compare price with Delta. Ordinary, when price move up, delta is positive. Price move down is negative delta.
This is because market orders move price and market orders are counted by Delta (although this description is not exactly correct).
But, sometimes prices do not move even though many market orders are putting pressure on price , or conversely, price move strongly without many market orders.
This is key point. Big player absorb market orders by iceberg order(Subdivide large orders and pretend to be small limit orders.
Small limit orders look weak in the order book, but they are added each time you fill, so they are more powerful than they look.), so price don't move.
On the other hand, when the price is moving easily, smart players may be aiming to attract and counterattack to a better price for them.
It's more of a sport than science, and there's always no right response. Pay attention to the relationship between price, volume and delta.
ex) If COT Low is large negative value, it means many sell market orders is coming, but iceberg order is absorbing their attack at limit order.
you should not do buy entry, only this clue. but this is one of the hints.
"Delta, Box Ratio and Total texts is contained same label and its color are "Delta" coloring. Positive Delta is Delta Bull color(green),Negative Delta is Delta Bear Color
and Delta = 0 is Neutral Color(gray). When Delta direction and price direction are opposite is Delta Divergence Color(yellow).
I didn't add the cumulative volume delta because I prefer to display the CVD line on the price chart rather than the number.
Box Ratio , Box Ratio Divisor and Heavy Box Ratio Ratio
: This is not ordinary footprint features, but I like this concept so I added.
Box Ratio by Richard W. Arms is simple but useful tool. calculation is "total volume (one bar) divided by Bar range (highest - lowest)."
When Bull and bear are fighting fiercely this number become large, and then important price move happen.
I made average BR from something like 5 SMA and if current BR exceeds average BR x (Heavy Box Ratio Ratio), BR box mark will be filled.
Box Ratio Divisor is used to good looking display(BR multiplied by Box Ratio Divisor is rounded off and displayed as an integer)
Diagonal Imbalance Count , D IB Mark and D IB Stripes
: Diagonal Imbalance is defined by "Diagonal Imbalance Ratio".
ex) You set 2. When Ask(row N) 30 Bid(row N -1)10, it's 30 > 10*2, so positive Diagonal Imbalance.
When Ask(row N) 4 Bid(row N -1)9, it's 4*2 < 9, so negative Diagonal Imbalance.
This calculation does not use equals to avoid Ask(row N) 0 Bid(row N -1)0 became Diagonal Imbalance.
Ask(row N) 0 Bid(row N -1)0, it's 0 = 0*2, not Diagonal Imbalance. Ask(row N) 10 Bid(row N -1)5, it's 10 = 5*2, not Diagonal Imbalance.
"D IB Mark" emphasize Ask or Bid number which is dominant side(Winner of Diagonal Imbalance calculation), by under line.
"Diagonal Imbalance Count" compare Ask side D IB Mark to Bid side D IB Mark in one footprint.
Coloring depend on which is more aggressive side (it has many IB Mark) and When Aggressive direction and price direction are opposite is Delta Divergence Color(yellow).
"D IB Stripes" is a function that further emphasizes with an arrow Mark, when a DIB mark is added on the same side for three consecutive row. Three consecutive arrow is added at third row.
Unfinished Auction, Ratio Bounds and Ladder fading Mark
: "Unfinished Auction" emphasize highest or lowest row which has both Ask and Bid, by Delta Divergence Color(yellow) XXXXXX mark.
Unfinished Auction sometimes has magnet effect, price may touch and breakout at UA side in the future.
This concept is famous as profit taking target than entry decision.
But, I'm interested in the case that Big player make fake breakout at UA side and trapped retail traders, and then do reversal with retail traders stop-loss hunt.
Anyway, it's not stand alone signal.
"Ratio Bounds" gauge decrease of pressure at extreme price. Ratio Bounds High is number which second highest ask is divided by highest ask.
Ratio Bounds Low is number which second lowest bid is divided by lowest bid. The larger the number, the less momentum the price has.
ex)first footprint bar has Ratio Bounds Low 2, second footprint bar has RBL 4, third footprint bar has RBL 20.
This indicates that the bear's power is gradually diminishing.
"Ladder fading mark" emphasizes the decrease of the value in 3 consecutive row at extreme price. I added two type Marks.
Ask/Bid type(triangle Mark) is Ask/Bid values are decreasing of three consecutive row at extreme price.
Row Imbalance type(Diamond Mark) are row Imbalance values are decreasing of three consecutive row at extreme price.
ex)Third lowest Bid 40, second lowest Bid 10 and lowest Bid 5 have triangle up Mark. That is bear's power is gradually diminishing.
(This Mark only check Bid value at lowest price and Ask value at highest price).
Third highest row delta + 60, second highest row delta + 5, highest delta - 20 have diamond Mark. That is Bull's power is gradually diminishing.
Sub display use Delta colors at bottom of Sub display section.
////// Candle & POC /////////
candle and POC
: Ordinary, "POC" Point of Control is row of largest total volume, but this script'POC is volume weighted average.
This is because the regular POC was visually displayed by the profile ,and I was influenced LucF's ideas.
POC coloring is decided in relation to the previous POC. When current POC is higher than previous POC, color is UP Bar Color(green).
In the opposite case, Down Bar color is used.
POC Divergence Color is used when Current POC is up but current bar close is lower than open (Down price Bar),or in the opposite case.
POC coloring has option also highlight background by Delta Divergence Color(yellow). but bg color is displayed at your time frame current price bar not current footprint bar.
The basic explanation is over.
I add some image to promote understanding basic ideas.
Indicator
