Volume Trend Lines
Introduction
Volume is one of the essential elements of financial market analysis. While price shows how the market moves, volume adds another dimension by revealing the level and concentration of trading activity.
Volume Trend Lines (VTL) takes a volume-centered approach to trend analysis. Rather than relying solely on price movements, the indicator uses volume data as the foundation for constructing trend lines, taking into account how Buy, Sell, and Total volume are distributed across different price levels.
By bringing volume-based analysis directly onto the price chart, VTL offers traders an additional perspective on market structure that complements traditional price analysis.
The Challenge of Measuring Buy and Sell Volume
One of the central challenges in volume analysis is determining how much of the trading activity within a candle was initiated by buyers and how much by sellers. Every transaction has both a buyer and a seller; the Buy/Sell distinction describes which side initiated the trade, not two separate quantities of shares or contracts.
Total candle volume is usually available, but identifying trade direction requires finer transaction data. When such data are limited, statistical and geometric techniques provide estimates rather than direct measurements.
1. TradingView Intrabar Volume Classification
Intrabar analysis examines the smaller observations that make up a chart candle. TradingView introduced tick-based charts in August 2024, including the 1T interval. Availability depends on the user's plan, the symbol, and historical data coverage.
The official TradingView ta library provides requestUpAndDownVolume(), which aggregates lower-timeframe volume into Up and Down components. For supported 1T requests, the library can compare tick prices with Bid and Ask information when available. Otherwise, its directional classification falls back to price-based rules: the intrabar Close relative to its Open, with the previous Close used when the Close equals the Open. Later versions of the library, including version 14 used by VTL, also map tick observations to chart candles more consistently.
For intrabar observations indexed by i, the aggregation can be written as:
V_up = Σᵢ Vᵢ × I(dᵢ = +1)
V_down = Σᵢ Vᵢ × I(dᵢ = −1)
ΔV = V_up − V_down
Here Vᵢ is the volume of observation i, dᵢ is its assigned direction, and I is an indicator function equal to 1 when its condition holds and 0 otherwise. Finer observations can improve directional resolution, but the classification still depends on the available data and should not be regarded as an infallible identification of trade initiators.
Figure 1: Intrabar volume classification and aggregation.
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2. Statistical, Mathematical, and Geometric Estimation
When transaction-level classification is unavailable, or when a complementary estimate is useful, candle volume can be apportioned using price changes, volatility, or candle geometry. Each of the following seven approaches produces a Buy-volume share p between 0 and 1.
Let O, H, L, C, and V denote a candle's Open, High, Low, Close, and total volume, and let C_prev denote the preceding Close. For any single method considered on its own:
V_buy = V × p
V_sell = V × (1 − p)
Within a single method, these two estimates are complementary. When an application evaluates its Buy and Sell estimates independently, however, the resulting displayed values need not add up to the original candle volume.
2.1. Bulk Volume Classification (BVC)
Origin. David Easley, Marcos López de Prado, and Maureen O'Hara developed BVC in their 2012 Review of Financial Studies paper on order-flow toxicity and examined it further in a 2016 Journal of Financial Economics study. Instead of assigning all volume to a single direction, BVC estimates a Buy fraction from the price change relative to recent volatility.
Calculation.
ΔC = C − C_prev
μ_ΔC = (1/n) Σⱼ ΔCⱼ
σ_ΔC = √[(1/n) Σⱼ (ΔCⱼ − μ_ΔC)²]
z = ΔC / σ_ΔC
p = Φ(z)
Φ(z) = (1/√(2π)) ∫₋∞ᶻ exp(−u²/2) du
The standard normal cumulative distribution function Φ converts a positive standardized change into a Buy share above 50% and a negative one into a Buy share below 50%. σ_ΔC is the population standard deviation of the latest n = 20 close-to-close changes, the current one included. If volatility is zero or unavailable, z is set to zero and p = 0.5. Φ is evaluated with the Abramowitz–Stegun approximation 26.2.17, whose absolute error is below 7.5 × 10⁻⁸.
Figure 2: BVC and the standard normal cumulative distribution.
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2.2. Geometry Bulk
Origin. This volume-classification formulation adapts established ideas from the Rogers–Satchell volatility estimator (1991), the Yang–Zhang estimator (2000), and the geometry of an OHLC candle. "Geometry Bulk" is the name of this adaptation, not a separately established academic estimator attributed to a named inventor.
Calculation. The logarithmic center of the candle is the logarithm of its geometric mean, measured relative to the previous Close:
G = (O × H × L × C)^(1/4)
r_G = ln(G / C_prev)
The overnight return r_O, the open-to-close return r_C, and the Rogers–Satchell term RS are defined as:
r_O = ln(O / C_prev)
r_C = ln(C / O)
RS = ln(H/O) × ln(H/C) + ln(L/O) × ln(L/C)
The move of the logarithmic center is standardized by a volatility σ_G and mapped through the standard normal cumulative distribution function:
p = Φ(r_G / σ_G)
σ_G combines the variance of the overnight return r_O with an intrabar variance built from r_C and the Rogers–Satchell term, in the spirit of the Yang–Zhang estimator:
σ_G² = σ_O² + c × max[k × σ_C² + (1 − k) × mean(RS), 0]
k = 0.34 / [1.34 + (n + 1) / (n − 1)]
c = (7 − 4 ln 2) / 16 ≈ 0.2642
Here σ_O² and σ_C² are the sample variances of r_O and r_C, and mean(RS) is the average Rogers–Satchell term, all taken over the latest n = 23 candles with the current one included. The weight k follows Yang and Zhang. The factor c is the variance of the logarithmic OHLC center, measured from the Open, for a candle whose log price follows a driftless Brownian motion with unit variance; it scales the intrabar component to the center and is not part of the original Yang–Zhang estimator. No estimate is returned when σ_G² is unavailable or not positive.
Figure 3: OHLC geometric center and volatility-adjusted classification.
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2.3. Geometry: Close Location Value (CLV)
Origin. Close Location Value is associated with volume-based accumulation and distribution analysis, particularly Marc Chaikin's Accumulation/Distribution Line. It expresses where the candle closes within its full trading range.
Calculation.
CLV = [(C − L) − (H − C)] / (H − L)
p = (CLV + 1)/2 = (C − L)/(H − L)
A Close at the High gives p = 1, a Close at the Low gives p = 0, and a Close at the midpoint gives p = 0.5. When H = L, the method assigns p = 0.5. Close location is a geometric proxy for directional pressure, not a direct trade-by-trade classification.
Figure 4: Close location and the resulting Buy-volume share.
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2.4. Tick Rule
Origin. The Tick Rule is a long-established trade-classification technique in market microstructure research and was also evaluated in the 1991 work of Charles Lee and Mark Ready. In its candle-based form, consecutive candle closing prices take the place of consecutive transaction prices.
Calculation.
ΔC = C − C_prev
p = 1 if ΔC > 0
p = 0 if ΔC < 0
If ΔC = 0, the last nonzero closing-price direction determines p; if no earlier nonzero direction exists, p = 0.5. Unlike proportional estimators, this rule normally allocates the entire candle volume to a single side, and a net candle direction cannot reveal the actual initiator of every transaction.
Figure 5: Tick Rule, including the zero-change fallback.
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2.5. Lee–Ready
Origin. Charles M. C. Lee and Mark J. Ready described their widely used trade-classification procedure in 1991. The original method compares trade prices with the prevailing Bid–Ask midpoint and applies the Tick Rule when the comparison is inconclusive. Because historical trade reports often lagged the quote revisions they triggered, a quote could appear in the data ahead of the trade that caused it. Lee and Ready therefore compared each trade with an earlier quote: five seconds before the reported trade time for their 1988 data and two seconds for 1987 data, noting that other periods may require a different delay.
Original quote-based rule.
M_quote = (Bid + Ask)/2
A trade above M_quote is classified as buyer-initiated, and a trade below it as seller-initiated. A trade at the midpoint is resolved using the Tick Rule.
Candle-based approximation. Because the method operates on chart candles, which carry no Bid and Ask quotes, VTL always uses the preceding candle's High–Low midpoint as its price reference:
M = (H_prev + L_prev)/2
p = 1 if C > M
p = 0 if C < M
For C = M, the Tick Rule determines p, or p = 0.5 if no previous nonzero direction exists. Using the previous candle is conceptually consistent with the concern about reference timing, but an OHLC midpoint is not a delayed quote, and this approximation must not be described as the original Lee–Ready algorithm.
Figure 6: Original quote-midpoint classification versus the candle-based approximation.
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2.6. Wick Imbalance
Origin. This geometric approximation is based on the proportions of a candle's shadows. Although candlestick analysis has historical roots in Japanese markets, this particular volume-allocation formula is not attributed to any uniquely established academic inventor.
Calculation.
W_upper = H − max(O, C)
W_lower = min(O, C) − L
p = W_lower / (W_lower + W_upper)
1 − p = W_upper / (W_lower + W_upper)
A longer lower shadow raises the estimated Buy proportion, while a longer upper shadow raises the estimated Sell proportion. If both shadows are zero, p = 0.5.
Figure 7: Upper and lower shadows as geometric volume-allocation weights.
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2.7. ML-Logit
Origin. This approach uses the logistic function, whose mathematical origins go back to Pierre-François Verhulst in the nineteenth century. Here it is applied as a fixed-coefficient probability model; it is not a separately trained machine-learning classifier.
Calculation.
r = (C − C_prev) / σ_ΔC
q = (V − μ_V) / σ_V
z = r × g(q)
p = 1 / [1 + exp(−z)]
Here σ_ΔC is the population standard deviation of the latest 50 close-to-close changes, and μ_V and σ_V are the mean and population standard deviation of the latest 50 volumes, each window including the current candle. Any normalization with a zero or unavailable standard deviation contributes zero instead. The volume factor is:
g(q) = 1 + 0.5 × tanh(q)
It lies between 0.5 and 1.5 and increases with relative volume q, so it changes the strength, but not the sign, of the price-change signal.
Figure 8: Logistic Buy-share curves at different relative-volume levels.
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Interpretation and Limitations
These methods estimate directional volume under different assumptions. Some allocate volume wholly to one side; others assign a fractional share. They should not be interpreted as direct observations of buyer- and seller-initiated transactions, nor as guarantees of future price direction. Their usefulness depends on market conditions, data quality, and the timeframe under study.
3. From Volume Analysis to Volume-Based Trend Lines
Having explored different approaches to estimating Buy and Sell volume, two important questions arise: how can this information be used to construct volume-based trend lines, and which of the seven estimation methods should be chosen?
Rather than requiring traders to make that choice manually, Volume Trend Lines (VTL) introduces Smart Volume, an adaptive approach designed to evaluate these methods against TradingView's intrabar volume data.
3.1. Volume Data
The first section of the VTL settings is ① Volume data, where users select the Volume engine used for the indicator's calculations. Two engines are available: Smart Volume, the default, and Footprint (Premium/Ultimate). Only the selected engine runs.
Smart Volume
Smart Volume is the default engine in VTL. With the default one-minute reference, it does not require a higher-tier TradingView subscription, making it accessible across TradingView plans to users who have been granted access to VTL.
It evaluates all seven estimation methods against the directional volume data obtained through TradingView's official ta library using requestUpAndDownVolume().
Instead of assuming that a single mathematical or statistical method performs best under all market conditions, VTL re-evaluates the methods' estimates against the available intrabar reference data as each candle closes.
Based on this comparison, Smart Volume selects one method for the Buy side and one for the Sell side, each under its own side-specific criterion, without requiring users to choose an estimation method manually. The selected Buy and Sell methods may therefore differ.
The resulting volume estimates form the basis for VTL's subsequent volume analysis, including the construction of its volume-based trend lines.
Smart Volume Resolution
The Smart Volume resolution setting determines the lower timeframe used as the reference for evaluating the seven estimation methods.
The default resolution is 1 minute, so Smart Volume can be used across TradingView plans without tick-data access.
At this resolution, the intrabar reference remains an approximation based on the price movements of individual one-minute candles.
VTL applies a minimum sampling guideline for the number of reference intervals per chart candle. When a time-based resolution provides too few reference intervals per chart candle, the indicator displays a warning on the chart but does not prevent the calculations.
Therefore, a 15-minute chart is the minimum recommended timeframe when using a one-minute reference.
For more informative sampling, a chart timeframe of 1 hour or higher is recommended with the default one-minute resolution. A one-hour candle can contain up to 60 one-minute observations, depending on the available market data.
How far back one-minute reference data reaches depends on the symbol and on the user's TradingView plan. On higher chart timeframes, fewer candles than the selected period may therefore be evaluated; the Evaluated row of the Status panel and the on-chart notice show the actual count.
If the selected Smart Volume resolution is higher than the chart timeframe, VTL automatically falls back to the chart's own timeframe.
Using Tick Data for Greater Granularity
TradingView users with Expert or Ultimate subscriptions can access 1T data for supported symbols.
When 1T data are available, selecting 1T as the Smart Volume resolution is recommended for a more granular evaluation of the seven estimation methods.
Unlike one-minute candles, which summarize price movements over a fixed time interval, 1T data provide individual tick observations. TradingView's volume-classification library can also use Bid/Ask information when available, offering a more detailed directional reference.
However, greater granularity does not guarantee perfectly accurate trade classification. Tick-data availability and historical coverage depend on the symbol, the data provider, and the TradingView subscription.
When the reference data do not cover the entire evaluation window, which is more likely with 1T data, VTL evaluates the methods using the available valid reference candles. With the Status panel enabled, the number of evaluated candles appears in its Evaluated row, marked with ⓘ; with the panel disabled, VTL displays a notice on the chart indicating how many candles were evaluated relative to the period set by the Period (candles) input.
Smart Volume is therefore designed to work with both accessible one-minute references and more granular tick-based data, allowing users to choose the evaluation resolution best suited to their available market data.
Footprint (Premium/Ultimate)
The Footprint engine does not estimate. It reads TradingView's own volume footprint data through request.footprint(), with one tick per row, so the Buy and Sell volume of each candle's price rows come directly from that data and the Distribution model setting does not apply. Footprint data require a Premium or Ultimate plan.
A candle without footprint data, taller than VTL's row limit, with rows that are missing or not one tick tall, or whose rows do not add up to the candle's Buy and Sell totals is left out of the analysis, and a note on the chart counts such candles by reason.
3.2. Status Panel
To provide greater transparency into the Smart Volume evaluation process, VTL includes an optional Status panel that displays the current analysis settings, the selected estimation methods, and their accuracy relative to the available reference data.
The panel is disabled by default. To enable it, open the VTL settings and, on the Inputs tab, go to the ⑨ Display section near the bottom, tick Status panel, and click Ok to apply the setting.
Once enabled, the panel appears at the bottom center of the chart and provides a compact summary of Smart Volume's adaptive evaluation. Data-related notes and warnings remain visible even when the Status panel is disabled.
Figure 9: The Status panel option in the Display section of the VTL settings, with an enlarged view.
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3.3. Understanding the Status Panel
The Status panel provides a concise overview of the current volume analysis, including the reference data, the selected estimation methods, and their measured agreement with the reference.
When Smart Volume is active, the panel displays the six fields shown in Figure 10. When Footprint (Premium/Ultimate) is selected, it displays the engine name and TradingView Footprint data as its source.
1. Reference
Displays the lower timeframe used to obtain the intrabar volume reference against which the seven estimation methods are evaluated.
2. Distribution
Identifies the volume distribution model selected in the Distribution model setting, which distributes the estimated volume across price levels. This setting is independent of the seven methods used to estimate Buy and Sell volume. The available distribution models are described in detail in a later section.
3. Evaluated
Shows the number of candles with valid reference data included in the evaluation, relative to the total number of candles in the selected analysis period.
For example, "50 of 50 candles" indicates that valid reference data were available for all 50 candles in the evaluation period. When fewer candles than the period length could be evaluated, the count is marked with ⓘ and a note at the bottom of the panel explains that the reference data do not reach further back.
4. Buy side
Displays the selected Buy-volume estimation method and its accuracy percentage, which expresses how closely the method's estimates agree with the intrabar reference over the evaluated candles. A higher percentage indicates closer agreement.
5. Sell side
Displays the selected Sell-volume estimation method and its accuracy percentage, expressed in the same way.
The Sell-side method is selected independently of the Buy side, so the two selected methods may differ, as in Figure 10, where Geometry (CLV) is selected for Buy volume and ML-Logit for Sell volume.
Each percentage is measured over all evaluated candles, whereas each side's method is selected under its own side-specific criterion. The method selected for one side therefore need not show the higher percentage, as Figure 10 illustrates.
6. Overall
Displays the arithmetic average of the Buy-side and Sell-side accuracy percentages. In Figure 10, (75.7% + 81.8%) / 2 ≈ 78.8%.
These accuracy values measure agreement with the available intrabar reference data. They do not represent the probability of correctly predicting future price movements.
Figure 10: The Smart Volume Status panel at the bottom center of the chart, with an enlarged view.
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The Status panel enables traders to examine reference-data coverage, identify the currently selected estimation methods, and assess how closely their estimates correspond to the intrabar reference.
The panel is refreshed when a new candle closes, while the method evaluations are updated as new valid reference data become available.
3.4. The Footprint Engine
While Smart Volume estimates Buy and Sell volume using statistical and mathematical methods, the Footprint engine takes a different approach. It uses TradingView's own Footprint data, which provides Buy and Sell volume at individual price levels within each candle.
This distinction is fundamental. Rather than estimating how candle volume is distributed across prices, VTL works directly with the price-level volume information supplied by TradingView. This allows the indicator to examine where trading activity is concentrated, how Buy and Sell volume differ across price levels, and how these concentrations contribute to volume-based trend lines, volume profiles, and delta analysis.
The Footprint engine operates independently of Smart Volume. Its data are not modified by the seven estimation methods, and no method-selection accuracy percentages are calculated. When Footprint is selected, the Smart Volume resolution and Distribution model settings become inactive.
Footprint values are retained once a candle closes, providing a consistent historical basis for the selected analysis period. If a candle's Footprint data are unavailable or fail the required validity checks, VTL excludes that candle rather than replacing its values with estimates. An on-chart notice shows how many candles were excluded and why.
Data Interpretation and Limitations
Although Footprint provides more detailed price-level information than candle-wide volume estimates, its Buy and Sell classifications still depend on TradingView's underlying methodology and the available market data. They should not be interpreted as infallible identification of the initiating side of every transaction.
The value of Footprint within VTL lies in using this price-level information as the foundation for a consistent analysis of volume concentration, directional imbalance, and volume-based market structure.
3.5. Volume Distribution Models
Estimating Buy and Sell volume is the first step in volume-based analysis. The next challenge is determining how that volume should be distributed across the price levels within each candle.
Smart Volume addresses this through three mathematical distribution models: Galton, Gaussian, and Kumaraswamy. Each represents a different assumption about where trading volume is concentrated within a candle's High–Low range.
These models do not determine the total amount of Buy or Sell volume. Instead, they distribute the estimated volume of each side across price levels, forming the basis for subsequent analysis, including volume profiles, delta distributions, and volume-based trend lines.
The Distribution model setting is available only when Smart Volume is selected. Galton is the default model.
3.5.1. Galton Distribution
Statistical basis. The Galton model draws on the binomial distribution, a fundamental concept in probability theory illustrated by the Galton board. This distribution produces a concentration around a central point, with progressively smaller weights toward the extremes.
For a symmetric binomial distribution, the probability of obtaining k successes in n independent trials is:
P(K = k) = C(n, k) × (1/2)ⁿ
Here C(n, k) is the binomial coefficient. This equation describes the underlying statistical principle; applying it to volume distribution requires a separate interpretation of price levels.
Volume distribution. In VTL, the Galton model places the greatest volume concentration at the candle's Close, with weights decreasing toward the High and Low. Each side of the distribution follows the distance from the Close to its respective price boundary.
Buy and Sell volume share the same normalized distribution across price levels, although their estimated quantities may differ.
An important consequence is that the Buy/Sell proportion remains constant across the price levels of an individual candle. Therefore, this model cannot represent Buy volume dominating at one price level and Sell volume dominating at another within the same candle.
Galton provides a unified, closing-price-centered distribution in which Buy and Sell volume concentrations follow an identical price pattern.
Figure 11: Galton distribution showing the common price-level weighting of Buy and Sell volume, with the highest concentration at the Close and declining weights toward the High and Low.
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3.5.2. Gaussian Distribution
Statistical basis. The Gaussian, or normal, distribution is one of the most widely used probability models in statistics. Its characteristic bell-shaped curve represents values concentrated around a central point, with progressively lower density farther from that center.
The Gaussian probability density function is:
f(x) = [1 / (σ√(2π))] × exp[−(x − μ)² / (2σ²)]
Here μ represents the center of the distribution, while σ controls its spread.
Volume distribution. Unlike Galton, the Gaussian model allows Buy and Sell volume to follow different distributions within the same candle.
In VTL, Buy volume is centered halfway between the Low and Close, while Sell volume is centered halfway between the Close and High.
Both distributions are confined to the candle's High–Low range, with their volume weights normalized within those boundaries.
As a result, the Buy/Sell proportion can vary across price levels. Buy volume may dominate one part of the candle's range while Sell volume dominates another.
These concentrations represent statistical allocations rather than direct observations of where individual Buy- or Sell-initiated transactions occurred.
The Gaussian model therefore provides a differentiated representation of directional volume concentration while retaining the familiar structure of a bell-shaped distribution.
Figure 12: Gaussian distribution showing separate Buy and Sell concentration centers within the candle's High–Low range and their overlapping volume distributions.
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3.5.3. Kumaraswamy Distribution
Statistical basis. The Kumaraswamy distribution, introduced by P. Kumaraswamy in 1980, is a continuous probability distribution defined over a bounded interval. Its two shape parameters allow it to represent a variety of distribution patterns, including asymmetric and skewed forms.
For a normalized variable x between 0 and 1, its probability density function is:
f(x; a, b) = ab × x^(a−1) × (1−x^a)^(b−1)
Here a and b are positive shape parameters that determine the distribution's form.
Unlike the conventional Gaussian distribution, Kumaraswamy is naturally defined within finite boundaries, making it suitable for modeling quantities over a specified interval.
Volume distribution. VTL applies the Kumaraswamy model within each candle's High–Low range, using separate distributions for Buy and Sell volume.
Buy volume is concentrated around the midpoint between the Low and Close, while Sell volume is concentrated around the midpoint between the Close and High.
Its distinguishing characteristic is the flexibility of its shape. The distribution adapts to the candle's relative height within the analysis period, allowing its curvature and concentration pattern to change with candle characteristics.
As with Gaussian, the different Buy and Sell distributions allow their relative proportions to vary across price levels. However, Kumaraswamy is not restricted to the conventional bell-shaped form.
This provides an alternative mathematical representation of directional volume concentration that accommodates varying distribution shapes within the candle's price boundaries.
Figure 13: Kumaraswamy distribution illustrating separate Buy and Sell concentration regions and changes in distribution shape for candles with different relative price ranges.
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Choosing and Interpreting a Distribution Model
The three models represent different mathematical assumptions about how volume is distributed within a candle.
Galton concentrates volume around the Close and applies identical price-level weights to Buy and Sell volume, preserving their relative proportion throughout the candle.
Gaussian uses separate bell-shaped distributions, allowing Buy and Sell concentrations to differ across price levels.
Kumaraswamy also separates Buy and Sell concentrations but introduces greater flexibility in distribution shape, responding to variations in candle characteristics.
The selected model directly influences the resulting price-level volume distribution and, consequently, the volume concentrations, delta patterns, and price levels used in VTL's subsequent analysis.
Interpretation and Limitations
These distributions are mathematical estimates, not direct measurements of executed volume at individual prices. Their purpose is to provide structured representations of estimated Buy and Sell volume under different statistical assumptions.
No single distribution model can be assumed to reproduce the actual intrabar trading activity under all market conditions.
When Footprint is selected, these models are disabled. VTL instead uses the price-level Buy and Sell volume data provided by TradingView.
3.6. Period and Blocks
Volume analysis depends not only on how trading activity is measured, but also on the time interval over which it is examined. A short observation period emphasizes recent activity, while a longer period provides a broader view of volume concentration and its development over time.
VTL organizes this analysis through the ② Period and blocks section of its settings. These controls define the number of candles included in the analysis, how they are grouped into smaller intervals, the percentage used for volume value areas, and how far selected analytical lines extend beyond the latest candle.
The settings apply to both Smart Volume and Footprint, providing a consistent analytical structure regardless of the selected volume engine.
3.6.1. Period (candles)
The Period setting defines the number of closed chart candles included in VTL's analysis.
The default period is 50 candles, with an adjustable range from 2 to 150.
For example, on a one-hour chart, a period of 50 represents the latest 50 completed hourly candles. On a daily chart, the same setting represents 50 completed daily candles.
The period establishes the common observation window for the indicator's volume-based calculations. Within this window, VTL examines the distribution and concentration of Buy, Sell, and Total volume across price levels.
A shorter period focuses the analysis on more recent market activity, while a longer period incorporates a wider history of trading behavior.
As each new candle closes, the analysis period moves forward to include the latest completed candle.
In Smart Volume, the selected period also determines the evaluation window used to compare volume estimation methods against the available intrabar reference data.
The completeness of the resulting analysis depends on data availability. When valid reference or Footprint data are insufficient, VTL provides on-chart information about the relevant limitations.
3.6.2. Blocks
Examining volume over an entire period reveals its overall distribution, but it does not necessarily show how that distribution has developed from one part of the period to another.
VTL addresses this by dividing the selected period into smaller chronological sections called Blocks.
The default setting is 4 blocks, with a configurable range from 2 to 50.
Each block represents a consecutive group of candles within the same analysis period. The blocks are numbered from the oldest to the newest, allowing the trader to examine changes in volume concentration as the market develops.
For example, a 50-candle period divided into four blocks produces four consecutive observation intervals. When the period cannot be divided evenly, the oldest block contains the remaining candles.
Each block contains at least two candles. If the requested number of blocks exceeds what the selected period can accommodate, VTL automatically uses fewer blocks and displays an informational notice.
Figure 14: A 50-candle analysis period divided into four chronological blocks, illustrating the relationship between the full observation period and its individual volume-analysis intervals.
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Why Blocks Matter
The distinction between the whole period and its individual blocks is central to VTL's approach.
The full period provides an aggregated view of volume concentration across the selected candles. Each block provides a more localized view of that concentration during a particular part of the period.
This makes it possible to examine whether areas of concentrated trading activity remain at similar price levels or shift as the observation period progresses.
These changes form the basis for VTL's volume-based trend lines, which relate the development of volume concentration to price over time.
Blocks also support individual volume profiles and distribution curves, allowing traders to compare shorter intervals within the broader analysis period.
3.6.3. Value Area (%)
In volume profile analysis, the Value Area identifies a price region containing a specified share of the observed trading volume.
The concept is commonly used to distinguish areas of greater volume concentration from prices where comparatively less activity occurred.
VTL uses three principal volume-profile levels:
Point of Control (POC): The price level with the highest volume concentration within the selected observation interval.
Value Area High (VAH): The upper boundary of the calculated Value Area.
Value Area Low (VAL): The lower boundary of the calculated Value Area.
The Value area (%) setting specifies the target percentage of volume to be included within these boundaries.
The default is 70%, consistent with the conventional setting used in TradingView's Volume Profile tools. The percentage can be adjusted from 1% to 100%.
For example, with a 70% setting, the analysis seeks to identify a price region around the POC representing approximately 70% of the selected volume. Because volume is organized into discrete price levels, the resulting area does not necessarily contain exactly the target percentage.
The same Value Area setting applies to profiles calculated for the whole period and for individual blocks.
Figure 15: A conceptual volume profile illustrating the Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL), with a 70% target Value Area highlighted.
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Interpreting the Value Area
The POC identifies the strongest concentration of volume in the selected profile, while VAH and VAL describe the boundaries of its principal volume region.
Comparing these levels across different blocks can help traders observe changes in the location and distribution of trading activity.
A shift in the POC, for example, indicates that the price level of maximum volume concentration has changed between observation intervals.
These levels describe historical volume distribution. They do not, by themselves, establish guaranteed support, resistance, or future price direction.
3.6.4. Offset (bars)
The Offset setting controls how far VTL's volume-based trend lines and whole-period POC, VAH, and VAL levels extend to the right of the latest candle.
The default is 19 bars, with an adjustable range from 0 to 200.
Increasing the Offset provides additional chart space for viewing extended trend lines and volume-profile levels, while also positioning their labels away from the most recent price action.
The Offset changes only the visual extension of these analytical elements. It does not change the selected period, the underlying volume data, or the calculated volume-profile levels.
Extended trend lines follow their existing direction beyond the observation period and should not be interpreted as guaranteed forecasts of future prices.
How Period and Blocks Work Together
These settings establish the time-based framework for VTL's analysis.
The Period determines how much completed price history is examined. Blocks divide that history into successive observation intervals, making changes in volume concentration easier to identify. Value Area defines the target volume coverage of the profile boundaries, while Offset controls how selected analytical levels are displayed beyond the latest candle.
Together, they allow traders to examine both the overall distribution of volume and its development across smaller intervals, creating the foundation for the volume-based trend lines and other analytical features described in the following sections.
3.7. Volume-Based Trend Lines
Traditional trend lines are generally constructed from price movements, often connecting successive highs, lows, or other significant points on a chart. While these methods describe the direction of price action, they do not directly account for where trading volume is concentrated.
Volume Trend Lines (VTL) approaches trend analysis from a different perspective. Instead of using price extremes as the primary reference, it examines how the price levels associated with concentrated trading volume change over time.
By combining volume profile analysis with statistical regression, VTL constructs trend lines that reflect the direction of volume concentration across the selected analysis period.
The ③ Trend lines section of the settings provides three independently configurable lines: Buy, Sell, and Total.
3.7.1. From Volume Concentration to Trend Lines
As described in the previous section, VTL divides the analysis period into consecutive blocks. Each block represents a separate interval in which Buy, Sell, and Total volume can be examined across price levels.
A central concept in this process is the Point of Control (POC), the price level with the greatest volume concentration within a given block.
Because Buy, Sell, and Total volume can have different distributions, each may produce a different POC.
VTL uses these block-level volume concentrations and their associated positions in time to establish the reference points for its trend lines.
Rather than simply connecting consecutive POC levels with straight segments, VTL applies statistical regression to identify the overall direction represented by these reference points.
This distinction is important. A fitted trend line summarizes the movement of volume concentration across the observation period; it does not necessarily pass through every individual reference point.
Figure 16: Conceptual illustration of volume-based trend line construction, showing POC-related reference points across successive blocks and a fitted trend line representing their overall direction, rather than connecting them individually.
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3.7.2. Buy, Sell, and Total Trend Lines
VTL provides three independent trend lines, each based on a different category of trading volume.
Buy Trend Line
The Buy Trend Line follows the development of price levels associated with the greatest concentration of Buy volume across the analysis blocks.
An upward-sloping Buy line indicates that these concentrations have generally shifted toward higher prices, while a downward-sloping line indicates a movement toward lower prices.
This describes the location of Buy-volume concentration, not necessarily an increase or decrease in the total quantity of buying activity.
The Buy line is disabled by default and is displayed in blue when enabled.
Sell Trend Line
The Sell Trend Line applies the same analytical principle to Sell-volume concentrations.
Its direction reflects how the price levels associated with concentrated Sell volume have developed throughout the selected period.
A rising Sell line does not necessarily indicate increasing selling pressure. It indicates that the fitted price location of Sell-volume concentration is moving higher.
The Sell line is disabled by default and is displayed in pink when enabled.
Total Trend Line
The Total Trend Line represents the combined distribution of Buy and Sell volume.
It identifies the overall direction of volume concentration without separating the two sides.
Importantly, the Total line is calculated from the combined volume distribution. It is not the arithmetic average of the Buy and Sell trend lines.
The Total line is enabled by default and is displayed in white.
Comparing the Three Lines
When displayed together, the three lines provide complementary views of how volume concentration develops over time.
Differences in their slopes or relative positions indicate that Buy, Sell, and Total volume concentrations are not necessarily evolving in the same way.
For example, Buy-volume concentrations may shift toward higher prices while Sell-volume concentrations remain relatively stable or move in another direction.
Such differences provide additional information about the structure of trading activity. However, the relative position or intersection of these lines should not, by itself, be interpreted as confirmation of buying pressure, selling pressure, or a future price reversal.
Figure 17: Buy, Sell, and Total volume-based trend lines displayed together, illustrating how the direction and price location of their volume concentrations can differ over the same analysis period.
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3.7.3. Linear Regression and Standard Error
Statistical basis. Linear regression is a widely used statistical method for identifying the linear relationship between observations.
The ordinary least-squares method determines the straight line that minimizes the sum of squared vertical differences between the observed values and the fitted line.
Its general equation is:
ŷ = a + bx
Here x represents the observation's position along the chart's candle sequence, ŷ is the fitted price, a is the intercept, and b is the slope.
A positive slope indicates an upward tendency in the reference prices, a negative slope indicates a downward tendency, and a slope near zero indicates relatively little overall directional change.
In VTL, this statistical principle is applied separately to the volume-concentration reference points associated with Buy, Sell, and Total volume.
Standard Error
A regression line describes the overall linear tendency of its observations, but it does not show how closely those observations follow that direction.
VTL therefore includes two additional dashed lines positioned above and below each fitted trend line.
Their distance from the central line is determined by the residual standard error of the regression, a statistical measure of the dispersion of observed values around their fitted line.
For N observations, the residual standard error is:
SE = √[Σᵢ(yᵢ − ŷᵢ)² / (N − 2)]
Here yᵢ represents an observed reference price, ŷᵢ is the corresponding fitted price, and N is the number of regression observations.
The two dashed lines are positioned at:
Upper = ŷ + SE
Lower = ŷ − SE
A smaller standard error indicates that the reference points are more closely aligned with the fitted line in price terms. A larger standard error indicates greater dispersion around that direction.
These boundaries are parallel to the central regression line and maintain a constant vertical distance from it.
Important distinction. The dashed lines represent one residual standard error above and below the fitted line. They are not statistical confidence intervals, prediction intervals, or probability-based boundaries for future prices.
At least two reference observations on different candles are required to establish a fitted line, while the standard-error boundaries require at least three reference points.
When sufficient observations are unavailable, VTL omits the affected line or its standard-error boundaries and provides an informational notice on the chart.
Figure 18: A conceptual least-squares regression line with observed reference points and parallel dashed boundaries positioned one residual standard error above and below the fitted line.
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3.7.4. Interpreting Volume-Based Trend Lines
The principal purpose of these lines is to identify the direction in which concentrated trading activity is located across successive observation intervals.
Three general interpretations are possible:
Rising trend line: The fitted price location of the selected volume concentration is moving toward higher levels.
Falling trend line: The fitted price location of the selected volume concentration is moving toward lower levels.
Relatively flat trend line: The selected volume concentrations show limited overall directional movement during the observation period.
These interpretations apply separately to Buy, Sell, and Total volume.
An important distinction is that the slope of a volume-based trend line describes the movement of volume concentration in price, not the rate of change in trading volume itself.
Likewise, a steep line does not necessarily indicate stronger trading activity than a flatter line. Its slope is influenced by the price movement of the reference levels, the chart timeframe, and the characteristics of the instrument.
The standard-error boundaries add another dimension by showing how closely the underlying volume-concentration observations follow the fitted direction.
Together, these elements can help traders examine whether the locations of concentrated trading activity exhibit a consistent directional tendency or a more dispersed pattern.
However, a well-aligned historical regression does not guarantee that the same tendency will continue.
3.7.5. Trend Line Appearance and Settings
Each of the three trend lines has its own display controls, allowing traders to examine individual volume categories or compare them on the same chart.
Visibility: Buy, Sell, and Total lines can be enabled or disabled independently. By default, only the Total line is visible.
Color: Each line has an independently adjustable color. The default colors are blue for Buy, pink for Sell, and white for Total.
Width: Line thickness can be adjusted from 1 to 5. The defaults are 3 for Buy and 2 for both Sell and Total.
Line Style: Solid, Dashed, and Dotted styles are available for the central trend line. The standard-error boundaries remain dashed regardless of the selected center-line style.
Neon Glow
The Neon glow option adds a soft visual halo around enabled trend lines on dark chart backgrounds.
It is enabled by default and is intended to improve the visual distinction of the central lines without changing their analytical values.
VTL also adjusts line colors when necessary to maintain readability against the chart background, whether the chart uses a light or dark theme.
These visual settings affect presentation only. They do not change the calculated trend lines or their standard-error values.
Line Extension
The Offset (bars) setting, introduced in Section 3.6.4, also controls the extension of the volume-based trend lines beyond the latest completed candle.
The central regression line continues along its fitted slope, while its standard-error boundaries extend in parallel.
This extension provides a visual continuation of the existing statistical relationship. It does not represent a new observation or an independently calculated forecast.
3.7.6. Data Requirements and Limitations
Volume-based trend lines depend on the quality and availability of the underlying volume information.
With Smart Volume, the analysis is based on estimated Buy and Sell volume and the selected mathematical distribution model. With Footprint, it uses the price-level volume information supplied by TradingView.
Consequently, differences in the volume engine, distribution model, analysis period, or number of blocks can affect the resulting trend lines.
The Volume engine and the selected distribution model influence the underlying volume concentrations, while the Period and Blocks settings determine the observation structure used to examine their development.
The Value area (%) setting determines the target coverage of VAH and VAL, but it does not determine the POC levels from which the trend-line analysis is derived.
Each analysis block requires at least two candles, and at least two usable blocks are needed for trend-line analysis. Missing or unusable volume information can also prevent sufficient reference points from being established.
VTL updates its analysis as new candles close. Because the observation period moves forward and its underlying volume estimates or concentrations may change, previously displayed regression lines can also change as the analysis is refreshed.
These lines should therefore be understood as dynamic descriptions of the selected volume history, rather than fixed historical boundaries or guaranteed forecasts.
Analytical Perspective
The distinguishing feature of VTL's trend lines is the information used to establish their direction.
Traditional price-based trend lines describe relationships between selected price observations. Volume-based trend lines instead describe the directional development of price levels associated with concentrated trading activity.
By examining Buy, Sell, and Total volume separately, VTL provides different perspectives on how these concentrations evolve throughout the analysis period.
The regression lines summarize their direction, while the standard-error boundaries describe the dispersion of the underlying reference observations.
Together, these features offer a statistical framework for examining volume-based market structure alongside conventional price analysis, without implying certainty about future market behavior.
3.8. Block Curves
The ④ Block curves section provides a visual representation of how trading volume is distributed across price levels within individual analysis blocks.
While volume-based trend lines describe the direction of volume concentration over time, Block Curves illustrate the distribution itself, allowing traders to examine where volume is concentrated and how Buy and Sell activity differs within each block.
VTL represents these distributions through smooth, shaded curves drawn directly on the price chart.
3.8.1. Volume Curves
Four independently configurable curve types are available:
Buy: Represents the distribution of estimated or measured Buy volume across the price levels of each block.
Sell: Represents the corresponding Sell-volume distribution.
Total: Represents the combined Buy and Sell volume distribution.
Delta: Represents the difference between Buy and Sell volume concentrations at individual price levels.
The Buy, Sell, and Total curves provide complementary views of volume concentration.
When Buy and Sell curves are displayed together, they appear as stacked distributions, with Sell volume extending beyond the Buy region. When Total is enabled alongside them, its outer boundary represents their combined distribution.
If Total is displayed on its own, it appears as a filled curve.
The width of a curve represents the relative concentration of volume at a particular price. Wider regions indicate greater concentration, while narrower regions indicate less.
Color intensity provides an additional visual reference: stronger shading corresponds to higher relative volume concentration.
3.8.2. Delta Curve
The Delta curve highlights the difference between Buy and Sell volume distributions.
At a given price level:
Delta = Buy Volume − Sell Volume
Positive Delta indicates that Buy volume exceeds Sell volume, while negative Delta indicates the opposite.
VTL uses separate colors to distinguish these conditions, making it possible to identify price regions where one side has greater volume concentration.
The Delta curve has its own display scale. Its width represents the relative magnitude of the imbalance within that block, rather than the absolute volume of either side.
3.8.3. Curve Settings
Each curve can be enabled independently, with individually adjustable colors and transparency.
The Width (%) setting controls how far the curves extend horizontally across their block. Its default is 100%, with an adjustable range from 10% to 100%.
Each block's curves are scaled to its available display width. Consequently, two equally wide curves in different blocks do not necessarily represent equal absolute trading volumes.
The High / low option displays dashed horizontal lines marking the upper and lower price rows covered by each block's volume distribution.
The Borders option adds dotted vertical lines separating consecutive blocks, making their chronological boundaries easier to identify.
All Block Curves are disabled by default.
When multiple curves are enabled simultaneously, VTL may simplify their shading or display curves for fewer blocks to remain within TradingView's graphical limits.
Figure 19: Block volume distributions illustrating Buy, Sell, Total, and Delta curves, with relative volume concentrations represented by curve width and color intensity.
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3.9. Block Profile
The ⑤ Block profile section identifies significant volume-profile levels within each analysis block.
While Block Curves describe the shape of volume distribution, Block Profile provides specific price references derived from that distribution.
Three levels are available:
POC (Point of Control): The price level with the highest volume concentration in the block.
VAH (Value Area High): The upper boundary of the calculated Value Area.
VAL (Value Area Low): The lower boundary of the calculated Value Area.
Volume Source
The Volume setting determines which volume category is used to calculate these levels:
Buy, Sell, or Total.
Total is selected by default.
Selecting Buy or Sell allows traders to examine the corresponding volume concentration and Value Area independently, rather than relying exclusively on combined volume.
The Value Area percentage follows the setting described in Section 3.6.3.
Display and Labels
POC, VAH, and VAL can be enabled separately. Each has independent color, line-width, and line-style controls.
The default POC color is orange, while VAH and VAL use blue. All three levels are disabled by default.
The Labels setting provides three display modes:
Off: Hides the labels.
Minimal: Displays a short label identifying the level, with additional information available when hovering over it.
Full: Displays detailed information directly on the chart.
Detailed labels include the block number, level price, and Buy and Sell volume associated with that price row. VAH and VAL labels also provide volume information for the relevant portions of the Value Area between those levels and the POC.
These levels allow traders to compare the locations of significant volume concentrations across successive blocks and observe how those locations change over time.
They represent the selected block's volume profile and should not automatically be interpreted as guaranteed support or resistance levels.
3.10. Period Curves
The ⑥ Period curves section extends volume-distribution analysis from individual blocks to the entire selected period.
Instead of examining each block separately, Period Curves combine the available volume information across the full observation window into a single set of distributions.
The same four curve types are available: Buy, Sell, Total, and Delta.
Buy, Sell, and Total
The Buy and Sell curves represent their respective volume concentrations across the entire period.
When both are enabled, their distributions appear stacked. The Total curve represents their combined distribution and is displayed as the outer boundary when Buy or Sell curves are also visible.
Examining the full-period distribution alongside individual blocks allows traders to distinguish broader concentrations of trading activity from those associated with shorter intervals.
Period Delta
The Delta curve represents the difference between Buy and Sell volume distributions across the full period.
Positive and negative Delta regions are shown in separate colors, indicating which side has greater volume concentration at different price levels.
The Period Delta uses its own display scale and is enabled by default.
Its shape can help identify where directional volume imbalance is concentrated across the selected observation window.
However, the Period Delta is an aggregated representation of the full period. It does not establish when the underlying trading activity occurred or whether a particular imbalance remains active in the latest candle.
Display Settings
All four curves have independently adjustable colors and transparency.
The Width (%) setting controls their horizontal display extent, from 10% to 100%, with 100% selected by default.
The High / low option, also enabled by default, displays dashed lines at the highest and lowest price rows of the period's volume distribution.
Because Block Curves and Period Curves use their own display scales, their widths should not be interpreted as directly comparable absolute volume measurements.
Figure 20: Comparison of individual Block Curves and the full-period volume distribution, illustrating localized volume concentrations alongside the aggregated Period Delta.
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3.11. Period Profile
The ⑦ Period profile section identifies the principal volume-profile levels across the entire selected period.
As with Block Profile, the three available levels are POC, VAH, and VAL.
The difference is the observation interval: Block Profile calculates these levels for individual blocks, while Period Profile calculates them for the entire period.
Volume Source
The Volume setting offers Buy, Sell, and Total as independent profile sources, with Total selected by default.
This allows the whole-period POC and Value Area to be examined using either directional volume category or their combined distribution.
Profile Levels and Appearance
POC, VAH, and VAL are all enabled by default.
Their default color is purple, with a solid POC line and dotted VAH and VAL lines.
Each level has independently adjustable color, line width, and line style.
Unlike block-profile levels, which remain within their respective blocks, the whole-period levels extend to the right according to the Offset (bars) setting introduced in Section 3.6.4.
Labels
The Labels setting offers Off, Minimal, and Full modes.
Minimal is selected by default.
In Minimal mode, the level name is displayed on the chart and additional data can be viewed by hovering over the label.
Full mode displays the level price, Buy and Sell volume at the corresponding price row, and, for VAH and VAL, volume information for the relevant portions of the Value Area.
Interpreting Block and Period Profiles Together
The whole-period profile provides a broader reference for the distribution of trading volume, while individual block profiles reveal how that distribution develops across smaller observation intervals.
Comparing them can help traders identify whether recent volume concentrations are located near the broader period's principal volume region or have shifted toward different price levels.
These levels describe historical trading-volume distribution rather than independently confirmed future price behavior.
3.12. Delta Peaks
The ⑧ Delta peaks section identifies the most pronounced positive and negative Buy–Sell volume imbalances within the selected analysis period.
Unlike Delta curves, which describe the distribution of imbalance across price levels, Delta Peaks identify specific candle and price-level locations where the greatest directional differences occur.
Peak Buy
Peak Buy marks the candle and price level where Buy volume exceeds Sell volume by the greatest amount.
Peak Sell
Peak Sell marks the candle and price level where Sell volume exceeds Buy volume by the greatest amount.
These measurements are based on the difference between Buy and Sell volume within an individual candle's price row, not simply on the candle's total Buy or Sell volume.
Consequently, a Delta Peak does not necessarily identify the candle with the highest overall trading volume.
Visual Representation
Each peak is identified by a small cross at its corresponding candle and price level.
A horizontal line extends from that location toward the right side of the chart, making the identified price easier to reference.
The associated label can display the peak price, Delta value, and Buy and Sell volumes at the identified location.
Peak Buy and Peak Sell are both enabled by default.
The default colors are blue for Peak Buy and pink for Peak Sell. Each line has adjustable color, width, and style settings.
The Labels setting offers Off, Minimal, and Full modes, with Minimal selected by default. Additional peak information remains available by hovering over the cross.
The independent Offset (bars) setting controls the extension of the peak lines. Its default is 3 bars, with an adjustable range from 0 to 200.
When no qualifying positive or negative imbalance exists, the corresponding peak is not displayed.
Interpretation
Delta Peaks highlight locations where directional volume imbalance was greatest within the selected period.
These locations may be useful when examining historical price reactions, areas of concentrated trading activity, or changes in volume-based market structure.
However, a strong historical Buy or Sell imbalance does not necessarily imply that the same side will dominate future trading at that price.
The identified peaks may also change as the analysis period advances or its underlying volume information is updated.
Figure 21: Peak Buy and Peak Sell markers identifying the strongest positive and negative candle-level volume imbalances within an analysis period, with horizontal reference lines extending from their corresponding price levels.
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3.13. Display Settings
The final section of the VTL settings, ⑨ Display, provides controls for the readability of information presented on the chart.
Text Size
The Text size setting adjusts the size of on-chart text, including informational labels and the Status panel.
The default is 15, with an adjustable range from 1 to 100.
Status Panel
The Status panel option controls the display of the indicator's volume-data information and evaluation summary.
It is disabled by default. Its contents and interpretation are explained in Sections 3.2 and 3.3.
Important data-availability notices and informational warnings remain visible when the Status panel is disabled.
Chart Appearance
VTL's adjustable colors, line styles, transparency, and curve shading allow traders to organize the display according to their chart preferences.
Selected visual colors are also adapted where appropriate to improve readability on different chart backgrounds.
These presentation settings do not change the underlying volume calculations.
3.14. Alerts and Data Window
VTL provides eight reference series for user-defined TradingView alerts: Total Line, Buy Line, Sell Line, Period POC, Period VAH, Period VAL, Peak Buy, and Peak Sell. The first three follow their respective volume-based trend lines; the next three identify the whole-period volume-profile levels; and the last two mark the prices of the strongest positive and negative Delta peaks.
These values are available when sufficient data exist, even if the corresponding chart drawings are hidden. Period POC, VAH, and VAL follow the Volume source selected in the Period profile settings.
Creating Alerts
Open TradingView's Create Alert dialog, choose the relevant VTL series under Condition, and configure an available comparison, such as price crossing a reference level. Set the notification method and frequency through TradingView. For conditions requiring a completed candle, use an appropriate bar-close frequency.
Reference levels can change as the observation period advances or the underlying volume estimates are updated. TradingView alerts use the indicator configuration saved when the alert is created, so review or recreate alerts after changing relevant settings. VTL supplies reference levels, not predefined Buy/Sell signals or entry and exit recommendations.
Data Window
TradingView's Data Window provides additional numerical outputs, including volume data, Smart Volume method evaluations, regression statistics, profile references, Delta Peaks, and configuration values. Available values depend on the active engine and data coverage. Applicable plotted values can also be examined through TradingView's chart-data export.
4. Purpose, Limitations, and Disclaimer
Volume Trend Lines (VTL) is designed for educational, informational, and independent market analysis. It helps users study where Buy, Sell, and Total volume are concentrated, how those concentrations change over time, and how directional imbalances appear across price levels.
Data and Interpretation
Smart Volume uses statistical estimates evaluated against available intrabar reference data; Footprint relies on TradingView's price-level volume data. Both are subject to data availability and classification limitations. Volume profiles, Delta Peaks, regression lines, and their extensions describe the selected observations, not guaranteed future outcomes. Values can change as new candles close, settings change, or the analysis window moves forward.
Not Financial Advice
VTL does not provide investment, financial, or trading advice, personalized recommendations, or guaranteed Buy/Sell signals. Its alerts and analytical levels are informational references, not trading instructions. Users remain responsible for independently assessing market conditions and the risks of any decisions they make.
Volume is one of the essential elements of financial market analysis. While price shows how the market moves, volume adds another dimension by revealing the level and concentration of trading activity.
Volume Trend Lines (VTL) takes a volume-centered approach to trend analysis. Rather than relying solely on price movements, the indicator uses volume data as the foundation for constructing trend lines, taking into account how Buy, Sell, and Total volume are distributed across different price levels.
By bringing volume-based analysis directly onto the price chart, VTL offers traders an additional perspective on market structure that complements traditional price analysis.
The Challenge of Measuring Buy and Sell Volume
One of the central challenges in volume analysis is determining how much of the trading activity within a candle was initiated by buyers and how much by sellers. Every transaction has both a buyer and a seller; the Buy/Sell distinction describes which side initiated the trade, not two separate quantities of shares or contracts.
Total candle volume is usually available, but identifying trade direction requires finer transaction data. When such data are limited, statistical and geometric techniques provide estimates rather than direct measurements.
1. TradingView Intrabar Volume Classification
Intrabar analysis examines the smaller observations that make up a chart candle. TradingView introduced tick-based charts in August 2024, including the 1T interval. Availability depends on the user's plan, the symbol, and historical data coverage.
The official TradingView ta library provides requestUpAndDownVolume(), which aggregates lower-timeframe volume into Up and Down components. For supported 1T requests, the library can compare tick prices with Bid and Ask information when available. Otherwise, its directional classification falls back to price-based rules: the intrabar Close relative to its Open, with the previous Close used when the Close equals the Open. Later versions of the library, including version 14 used by VTL, also map tick observations to chart candles more consistently.
For intrabar observations indexed by i, the aggregation can be written as:
V_up = Σᵢ Vᵢ × I(dᵢ = +1)
V_down = Σᵢ Vᵢ × I(dᵢ = −1)
ΔV = V_up − V_down
Here Vᵢ is the volume of observation i, dᵢ is its assigned direction, and I is an indicator function equal to 1 when its condition holds and 0 otherwise. Finer observations can improve directional resolution, but the classification still depends on the available data and should not be regarded as an infallible identification of trade initiators.
Figure 1: Intrabar volume classification and aggregation.
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2. Statistical, Mathematical, and Geometric Estimation
When transaction-level classification is unavailable, or when a complementary estimate is useful, candle volume can be apportioned using price changes, volatility, or candle geometry. Each of the following seven approaches produces a Buy-volume share p between 0 and 1.
Let O, H, L, C, and V denote a candle's Open, High, Low, Close, and total volume, and let C_prev denote the preceding Close. For any single method considered on its own:
V_buy = V × p
V_sell = V × (1 − p)
Within a single method, these two estimates are complementary. When an application evaluates its Buy and Sell estimates independently, however, the resulting displayed values need not add up to the original candle volume.
2.1. Bulk Volume Classification (BVC)
Origin. David Easley, Marcos López de Prado, and Maureen O'Hara developed BVC in their 2012 Review of Financial Studies paper on order-flow toxicity and examined it further in a 2016 Journal of Financial Economics study. Instead of assigning all volume to a single direction, BVC estimates a Buy fraction from the price change relative to recent volatility.
Calculation.
ΔC = C − C_prev
μ_ΔC = (1/n) Σⱼ ΔCⱼ
σ_ΔC = √[(1/n) Σⱼ (ΔCⱼ − μ_ΔC)²]
z = ΔC / σ_ΔC
p = Φ(z)
Φ(z) = (1/√(2π)) ∫₋∞ᶻ exp(−u²/2) du
The standard normal cumulative distribution function Φ converts a positive standardized change into a Buy share above 50% and a negative one into a Buy share below 50%. σ_ΔC is the population standard deviation of the latest n = 20 close-to-close changes, the current one included. If volatility is zero or unavailable, z is set to zero and p = 0.5. Φ is evaluated with the Abramowitz–Stegun approximation 26.2.17, whose absolute error is below 7.5 × 10⁻⁸.
Figure 2: BVC and the standard normal cumulative distribution.
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2.2. Geometry Bulk
Origin. This volume-classification formulation adapts established ideas from the Rogers–Satchell volatility estimator (1991), the Yang–Zhang estimator (2000), and the geometry of an OHLC candle. "Geometry Bulk" is the name of this adaptation, not a separately established academic estimator attributed to a named inventor.
Calculation. The logarithmic center of the candle is the logarithm of its geometric mean, measured relative to the previous Close:
G = (O × H × L × C)^(1/4)
r_G = ln(G / C_prev)
The overnight return r_O, the open-to-close return r_C, and the Rogers–Satchell term RS are defined as:
r_O = ln(O / C_prev)
r_C = ln(C / O)
RS = ln(H/O) × ln(H/C) + ln(L/O) × ln(L/C)
The move of the logarithmic center is standardized by a volatility σ_G and mapped through the standard normal cumulative distribution function:
p = Φ(r_G / σ_G)
σ_G combines the variance of the overnight return r_O with an intrabar variance built from r_C and the Rogers–Satchell term, in the spirit of the Yang–Zhang estimator:
σ_G² = σ_O² + c × max[k × σ_C² + (1 − k) × mean(RS), 0]
k = 0.34 / [1.34 + (n + 1) / (n − 1)]
c = (7 − 4 ln 2) / 16 ≈ 0.2642
Here σ_O² and σ_C² are the sample variances of r_O and r_C, and mean(RS) is the average Rogers–Satchell term, all taken over the latest n = 23 candles with the current one included. The weight k follows Yang and Zhang. The factor c is the variance of the logarithmic OHLC center, measured from the Open, for a candle whose log price follows a driftless Brownian motion with unit variance; it scales the intrabar component to the center and is not part of the original Yang–Zhang estimator. No estimate is returned when σ_G² is unavailable or not positive.
Figure 3: OHLC geometric center and volatility-adjusted classification.
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2.3. Geometry: Close Location Value (CLV)
Origin. Close Location Value is associated with volume-based accumulation and distribution analysis, particularly Marc Chaikin's Accumulation/Distribution Line. It expresses where the candle closes within its full trading range.
Calculation.
CLV = [(C − L) − (H − C)] / (H − L)
p = (CLV + 1)/2 = (C − L)/(H − L)
A Close at the High gives p = 1, a Close at the Low gives p = 0, and a Close at the midpoint gives p = 0.5. When H = L, the method assigns p = 0.5. Close location is a geometric proxy for directional pressure, not a direct trade-by-trade classification.
Figure 4: Close location and the resulting Buy-volume share.
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2.4. Tick Rule
Origin. The Tick Rule is a long-established trade-classification technique in market microstructure research and was also evaluated in the 1991 work of Charles Lee and Mark Ready. In its candle-based form, consecutive candle closing prices take the place of consecutive transaction prices.
Calculation.
ΔC = C − C_prev
p = 1 if ΔC > 0
p = 0 if ΔC < 0
If ΔC = 0, the last nonzero closing-price direction determines p; if no earlier nonzero direction exists, p = 0.5. Unlike proportional estimators, this rule normally allocates the entire candle volume to a single side, and a net candle direction cannot reveal the actual initiator of every transaction.
Figure 5: Tick Rule, including the zero-change fallback.
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2.5. Lee–Ready
Origin. Charles M. C. Lee and Mark J. Ready described their widely used trade-classification procedure in 1991. The original method compares trade prices with the prevailing Bid–Ask midpoint and applies the Tick Rule when the comparison is inconclusive. Because historical trade reports often lagged the quote revisions they triggered, a quote could appear in the data ahead of the trade that caused it. Lee and Ready therefore compared each trade with an earlier quote: five seconds before the reported trade time for their 1988 data and two seconds for 1987 data, noting that other periods may require a different delay.
Original quote-based rule.
M_quote = (Bid + Ask)/2
A trade above M_quote is classified as buyer-initiated, and a trade below it as seller-initiated. A trade at the midpoint is resolved using the Tick Rule.
Candle-based approximation. Because the method operates on chart candles, which carry no Bid and Ask quotes, VTL always uses the preceding candle's High–Low midpoint as its price reference:
M = (H_prev + L_prev)/2
p = 1 if C > M
p = 0 if C < M
For C = M, the Tick Rule determines p, or p = 0.5 if no previous nonzero direction exists. Using the previous candle is conceptually consistent with the concern about reference timing, but an OHLC midpoint is not a delayed quote, and this approximation must not be described as the original Lee–Ready algorithm.
Figure 6: Original quote-midpoint classification versus the candle-based approximation.
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2.6. Wick Imbalance
Origin. This geometric approximation is based on the proportions of a candle's shadows. Although candlestick analysis has historical roots in Japanese markets, this particular volume-allocation formula is not attributed to any uniquely established academic inventor.
Calculation.
W_upper = H − max(O, C)
W_lower = min(O, C) − L
p = W_lower / (W_lower + W_upper)
1 − p = W_upper / (W_lower + W_upper)
A longer lower shadow raises the estimated Buy proportion, while a longer upper shadow raises the estimated Sell proportion. If both shadows are zero, p = 0.5.
Figure 7: Upper and lower shadows as geometric volume-allocation weights.
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2.7. ML-Logit
Origin. This approach uses the logistic function, whose mathematical origins go back to Pierre-François Verhulst in the nineteenth century. Here it is applied as a fixed-coefficient probability model; it is not a separately trained machine-learning classifier.
Calculation.
r = (C − C_prev) / σ_ΔC
q = (V − μ_V) / σ_V
z = r × g(q)
p = 1 / [1 + exp(−z)]
Here σ_ΔC is the population standard deviation of the latest 50 close-to-close changes, and μ_V and σ_V are the mean and population standard deviation of the latest 50 volumes, each window including the current candle. Any normalization with a zero or unavailable standard deviation contributes zero instead. The volume factor is:
g(q) = 1 + 0.5 × tanh(q)
It lies between 0.5 and 1.5 and increases with relative volume q, so it changes the strength, but not the sign, of the price-change signal.
Figure 8: Logistic Buy-share curves at different relative-volume levels.
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Interpretation and Limitations
These methods estimate directional volume under different assumptions. Some allocate volume wholly to one side; others assign a fractional share. They should not be interpreted as direct observations of buyer- and seller-initiated transactions, nor as guarantees of future price direction. Their usefulness depends on market conditions, data quality, and the timeframe under study.
3. From Volume Analysis to Volume-Based Trend Lines
Having explored different approaches to estimating Buy and Sell volume, two important questions arise: how can this information be used to construct volume-based trend lines, and which of the seven estimation methods should be chosen?
Rather than requiring traders to make that choice manually, Volume Trend Lines (VTL) introduces Smart Volume, an adaptive approach designed to evaluate these methods against TradingView's intrabar volume data.
3.1. Volume Data
The first section of the VTL settings is ① Volume data, where users select the Volume engine used for the indicator's calculations. Two engines are available: Smart Volume, the default, and Footprint (Premium/Ultimate). Only the selected engine runs.
Smart Volume
Smart Volume is the default engine in VTL. With the default one-minute reference, it does not require a higher-tier TradingView subscription, making it accessible across TradingView plans to users who have been granted access to VTL.
It evaluates all seven estimation methods against the directional volume data obtained through TradingView's official ta library using requestUpAndDownVolume().
Instead of assuming that a single mathematical or statistical method performs best under all market conditions, VTL re-evaluates the methods' estimates against the available intrabar reference data as each candle closes.
Based on this comparison, Smart Volume selects one method for the Buy side and one for the Sell side, each under its own side-specific criterion, without requiring users to choose an estimation method manually. The selected Buy and Sell methods may therefore differ.
The resulting volume estimates form the basis for VTL's subsequent volume analysis, including the construction of its volume-based trend lines.
Smart Volume Resolution
The Smart Volume resolution setting determines the lower timeframe used as the reference for evaluating the seven estimation methods.
The default resolution is 1 minute, so Smart Volume can be used across TradingView plans without tick-data access.
At this resolution, the intrabar reference remains an approximation based on the price movements of individual one-minute candles.
VTL applies a minimum sampling guideline for the number of reference intervals per chart candle. When a time-based resolution provides too few reference intervals per chart candle, the indicator displays a warning on the chart but does not prevent the calculations.
Therefore, a 15-minute chart is the minimum recommended timeframe when using a one-minute reference.
For more informative sampling, a chart timeframe of 1 hour or higher is recommended with the default one-minute resolution. A one-hour candle can contain up to 60 one-minute observations, depending on the available market data.
How far back one-minute reference data reaches depends on the symbol and on the user's TradingView plan. On higher chart timeframes, fewer candles than the selected period may therefore be evaluated; the Evaluated row of the Status panel and the on-chart notice show the actual count.
If the selected Smart Volume resolution is higher than the chart timeframe, VTL automatically falls back to the chart's own timeframe.
Using Tick Data for Greater Granularity
TradingView users with Expert or Ultimate subscriptions can access 1T data for supported symbols.
When 1T data are available, selecting 1T as the Smart Volume resolution is recommended for a more granular evaluation of the seven estimation methods.
Unlike one-minute candles, which summarize price movements over a fixed time interval, 1T data provide individual tick observations. TradingView's volume-classification library can also use Bid/Ask information when available, offering a more detailed directional reference.
However, greater granularity does not guarantee perfectly accurate trade classification. Tick-data availability and historical coverage depend on the symbol, the data provider, and the TradingView subscription.
When the reference data do not cover the entire evaluation window, which is more likely with 1T data, VTL evaluates the methods using the available valid reference candles. With the Status panel enabled, the number of evaluated candles appears in its Evaluated row, marked with ⓘ; with the panel disabled, VTL displays a notice on the chart indicating how many candles were evaluated relative to the period set by the Period (candles) input.
Smart Volume is therefore designed to work with both accessible one-minute references and more granular tick-based data, allowing users to choose the evaluation resolution best suited to their available market data.
Footprint (Premium/Ultimate)
The Footprint engine does not estimate. It reads TradingView's own volume footprint data through request.footprint(), with one tick per row, so the Buy and Sell volume of each candle's price rows come directly from that data and the Distribution model setting does not apply. Footprint data require a Premium or Ultimate plan.
A candle without footprint data, taller than VTL's row limit, with rows that are missing or not one tick tall, or whose rows do not add up to the candle's Buy and Sell totals is left out of the analysis, and a note on the chart counts such candles by reason.
3.2. Status Panel
To provide greater transparency into the Smart Volume evaluation process, VTL includes an optional Status panel that displays the current analysis settings, the selected estimation methods, and their accuracy relative to the available reference data.
The panel is disabled by default. To enable it, open the VTL settings and, on the Inputs tab, go to the ⑨ Display section near the bottom, tick Status panel, and click Ok to apply the setting.
Once enabled, the panel appears at the bottom center of the chart and provides a compact summary of Smart Volume's adaptive evaluation. Data-related notes and warnings remain visible even when the Status panel is disabled.
Figure 9: The Status panel option in the Display section of the VTL settings, with an enlarged view.
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3.3. Understanding the Status Panel
The Status panel provides a concise overview of the current volume analysis, including the reference data, the selected estimation methods, and their measured agreement with the reference.
When Smart Volume is active, the panel displays the six fields shown in Figure 10. When Footprint (Premium/Ultimate) is selected, it displays the engine name and TradingView Footprint data as its source.
1. Reference
Displays the lower timeframe used to obtain the intrabar volume reference against which the seven estimation methods are evaluated.
2. Distribution
Identifies the volume distribution model selected in the Distribution model setting, which distributes the estimated volume across price levels. This setting is independent of the seven methods used to estimate Buy and Sell volume. The available distribution models are described in detail in a later section.
3. Evaluated
Shows the number of candles with valid reference data included in the evaluation, relative to the total number of candles in the selected analysis period.
For example, "50 of 50 candles" indicates that valid reference data were available for all 50 candles in the evaluation period. When fewer candles than the period length could be evaluated, the count is marked with ⓘ and a note at the bottom of the panel explains that the reference data do not reach further back.
4. Buy side
Displays the selected Buy-volume estimation method and its accuracy percentage, which expresses how closely the method's estimates agree with the intrabar reference over the evaluated candles. A higher percentage indicates closer agreement.
5. Sell side
Displays the selected Sell-volume estimation method and its accuracy percentage, expressed in the same way.
The Sell-side method is selected independently of the Buy side, so the two selected methods may differ, as in Figure 10, where Geometry (CLV) is selected for Buy volume and ML-Logit for Sell volume.
Each percentage is measured over all evaluated candles, whereas each side's method is selected under its own side-specific criterion. The method selected for one side therefore need not show the higher percentage, as Figure 10 illustrates.
6. Overall
Displays the arithmetic average of the Buy-side and Sell-side accuracy percentages. In Figure 10, (75.7% + 81.8%) / 2 ≈ 78.8%.
These accuracy values measure agreement with the available intrabar reference data. They do not represent the probability of correctly predicting future price movements.
Figure 10: The Smart Volume Status panel at the bottom center of the chart, with an enlarged view.
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The Status panel enables traders to examine reference-data coverage, identify the currently selected estimation methods, and assess how closely their estimates correspond to the intrabar reference.
The panel is refreshed when a new candle closes, while the method evaluations are updated as new valid reference data become available.
3.4. The Footprint Engine
While Smart Volume estimates Buy and Sell volume using statistical and mathematical methods, the Footprint engine takes a different approach. It uses TradingView's own Footprint data, which provides Buy and Sell volume at individual price levels within each candle.
This distinction is fundamental. Rather than estimating how candle volume is distributed across prices, VTL works directly with the price-level volume information supplied by TradingView. This allows the indicator to examine where trading activity is concentrated, how Buy and Sell volume differ across price levels, and how these concentrations contribute to volume-based trend lines, volume profiles, and delta analysis.
The Footprint engine operates independently of Smart Volume. Its data are not modified by the seven estimation methods, and no method-selection accuracy percentages are calculated. When Footprint is selected, the Smart Volume resolution and Distribution model settings become inactive.
Footprint values are retained once a candle closes, providing a consistent historical basis for the selected analysis period. If a candle's Footprint data are unavailable or fail the required validity checks, VTL excludes that candle rather than replacing its values with estimates. An on-chart notice shows how many candles were excluded and why.
Data Interpretation and Limitations
Although Footprint provides more detailed price-level information than candle-wide volume estimates, its Buy and Sell classifications still depend on TradingView's underlying methodology and the available market data. They should not be interpreted as infallible identification of the initiating side of every transaction.
The value of Footprint within VTL lies in using this price-level information as the foundation for a consistent analysis of volume concentration, directional imbalance, and volume-based market structure.
3.5. Volume Distribution Models
Estimating Buy and Sell volume is the first step in volume-based analysis. The next challenge is determining how that volume should be distributed across the price levels within each candle.
Smart Volume addresses this through three mathematical distribution models: Galton, Gaussian, and Kumaraswamy. Each represents a different assumption about where trading volume is concentrated within a candle's High–Low range.
These models do not determine the total amount of Buy or Sell volume. Instead, they distribute the estimated volume of each side across price levels, forming the basis for subsequent analysis, including volume profiles, delta distributions, and volume-based trend lines.
The Distribution model setting is available only when Smart Volume is selected. Galton is the default model.
3.5.1. Galton Distribution
Statistical basis. The Galton model draws on the binomial distribution, a fundamental concept in probability theory illustrated by the Galton board. This distribution produces a concentration around a central point, with progressively smaller weights toward the extremes.
For a symmetric binomial distribution, the probability of obtaining k successes in n independent trials is:
P(K = k) = C(n, k) × (1/2)ⁿ
Here C(n, k) is the binomial coefficient. This equation describes the underlying statistical principle; applying it to volume distribution requires a separate interpretation of price levels.
Volume distribution. In VTL, the Galton model places the greatest volume concentration at the candle's Close, with weights decreasing toward the High and Low. Each side of the distribution follows the distance from the Close to its respective price boundary.
Buy and Sell volume share the same normalized distribution across price levels, although their estimated quantities may differ.
An important consequence is that the Buy/Sell proportion remains constant across the price levels of an individual candle. Therefore, this model cannot represent Buy volume dominating at one price level and Sell volume dominating at another within the same candle.
Galton provides a unified, closing-price-centered distribution in which Buy and Sell volume concentrations follow an identical price pattern.
Figure 11: Galton distribution showing the common price-level weighting of Buy and Sell volume, with the highest concentration at the Close and declining weights toward the High and Low.
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3.5.2. Gaussian Distribution
Statistical basis. The Gaussian, or normal, distribution is one of the most widely used probability models in statistics. Its characteristic bell-shaped curve represents values concentrated around a central point, with progressively lower density farther from that center.
The Gaussian probability density function is:
f(x) = [1 / (σ√(2π))] × exp[−(x − μ)² / (2σ²)]
Here μ represents the center of the distribution, while σ controls its spread.
Volume distribution. Unlike Galton, the Gaussian model allows Buy and Sell volume to follow different distributions within the same candle.
In VTL, Buy volume is centered halfway between the Low and Close, while Sell volume is centered halfway between the Close and High.
Both distributions are confined to the candle's High–Low range, with their volume weights normalized within those boundaries.
As a result, the Buy/Sell proportion can vary across price levels. Buy volume may dominate one part of the candle's range while Sell volume dominates another.
These concentrations represent statistical allocations rather than direct observations of where individual Buy- or Sell-initiated transactions occurred.
The Gaussian model therefore provides a differentiated representation of directional volume concentration while retaining the familiar structure of a bell-shaped distribution.
Figure 12: Gaussian distribution showing separate Buy and Sell concentration centers within the candle's High–Low range and their overlapping volume distributions.
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3.5.3. Kumaraswamy Distribution
Statistical basis. The Kumaraswamy distribution, introduced by P. Kumaraswamy in 1980, is a continuous probability distribution defined over a bounded interval. Its two shape parameters allow it to represent a variety of distribution patterns, including asymmetric and skewed forms.
For a normalized variable x between 0 and 1, its probability density function is:
f(x; a, b) = ab × x^(a−1) × (1−x^a)^(b−1)
Here a and b are positive shape parameters that determine the distribution's form.
Unlike the conventional Gaussian distribution, Kumaraswamy is naturally defined within finite boundaries, making it suitable for modeling quantities over a specified interval.
Volume distribution. VTL applies the Kumaraswamy model within each candle's High–Low range, using separate distributions for Buy and Sell volume.
Buy volume is concentrated around the midpoint between the Low and Close, while Sell volume is concentrated around the midpoint between the Close and High.
Its distinguishing characteristic is the flexibility of its shape. The distribution adapts to the candle's relative height within the analysis period, allowing its curvature and concentration pattern to change with candle characteristics.
As with Gaussian, the different Buy and Sell distributions allow their relative proportions to vary across price levels. However, Kumaraswamy is not restricted to the conventional bell-shaped form.
This provides an alternative mathematical representation of directional volume concentration that accommodates varying distribution shapes within the candle's price boundaries.
Figure 13: Kumaraswamy distribution illustrating separate Buy and Sell concentration regions and changes in distribution shape for candles with different relative price ranges.
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Choosing and Interpreting a Distribution Model
The three models represent different mathematical assumptions about how volume is distributed within a candle.
Galton concentrates volume around the Close and applies identical price-level weights to Buy and Sell volume, preserving their relative proportion throughout the candle.
Gaussian uses separate bell-shaped distributions, allowing Buy and Sell concentrations to differ across price levels.
Kumaraswamy also separates Buy and Sell concentrations but introduces greater flexibility in distribution shape, responding to variations in candle characteristics.
The selected model directly influences the resulting price-level volume distribution and, consequently, the volume concentrations, delta patterns, and price levels used in VTL's subsequent analysis.
Interpretation and Limitations
These distributions are mathematical estimates, not direct measurements of executed volume at individual prices. Their purpose is to provide structured representations of estimated Buy and Sell volume under different statistical assumptions.
No single distribution model can be assumed to reproduce the actual intrabar trading activity under all market conditions.
When Footprint is selected, these models are disabled. VTL instead uses the price-level Buy and Sell volume data provided by TradingView.
3.6. Period and Blocks
Volume analysis depends not only on how trading activity is measured, but also on the time interval over which it is examined. A short observation period emphasizes recent activity, while a longer period provides a broader view of volume concentration and its development over time.
VTL organizes this analysis through the ② Period and blocks section of its settings. These controls define the number of candles included in the analysis, how they are grouped into smaller intervals, the percentage used for volume value areas, and how far selected analytical lines extend beyond the latest candle.
The settings apply to both Smart Volume and Footprint, providing a consistent analytical structure regardless of the selected volume engine.
3.6.1. Period (candles)
The Period setting defines the number of closed chart candles included in VTL's analysis.
The default period is 50 candles, with an adjustable range from 2 to 150.
For example, on a one-hour chart, a period of 50 represents the latest 50 completed hourly candles. On a daily chart, the same setting represents 50 completed daily candles.
The period establishes the common observation window for the indicator's volume-based calculations. Within this window, VTL examines the distribution and concentration of Buy, Sell, and Total volume across price levels.
A shorter period focuses the analysis on more recent market activity, while a longer period incorporates a wider history of trading behavior.
As each new candle closes, the analysis period moves forward to include the latest completed candle.
In Smart Volume, the selected period also determines the evaluation window used to compare volume estimation methods against the available intrabar reference data.
The completeness of the resulting analysis depends on data availability. When valid reference or Footprint data are insufficient, VTL provides on-chart information about the relevant limitations.
3.6.2. Blocks
Examining volume over an entire period reveals its overall distribution, but it does not necessarily show how that distribution has developed from one part of the period to another.
VTL addresses this by dividing the selected period into smaller chronological sections called Blocks.
The default setting is 4 blocks, with a configurable range from 2 to 50.
Each block represents a consecutive group of candles within the same analysis period. The blocks are numbered from the oldest to the newest, allowing the trader to examine changes in volume concentration as the market develops.
For example, a 50-candle period divided into four blocks produces four consecutive observation intervals. When the period cannot be divided evenly, the oldest block contains the remaining candles.
Each block contains at least two candles. If the requested number of blocks exceeds what the selected period can accommodate, VTL automatically uses fewer blocks and displays an informational notice.
Figure 14: A 50-candle analysis period divided into four chronological blocks, illustrating the relationship between the full observation period and its individual volume-analysis intervals.
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Why Blocks Matter
The distinction between the whole period and its individual blocks is central to VTL's approach.
The full period provides an aggregated view of volume concentration across the selected candles. Each block provides a more localized view of that concentration during a particular part of the period.
This makes it possible to examine whether areas of concentrated trading activity remain at similar price levels or shift as the observation period progresses.
These changes form the basis for VTL's volume-based trend lines, which relate the development of volume concentration to price over time.
Blocks also support individual volume profiles and distribution curves, allowing traders to compare shorter intervals within the broader analysis period.
3.6.3. Value Area (%)
In volume profile analysis, the Value Area identifies a price region containing a specified share of the observed trading volume.
The concept is commonly used to distinguish areas of greater volume concentration from prices where comparatively less activity occurred.
VTL uses three principal volume-profile levels:
Point of Control (POC): The price level with the highest volume concentration within the selected observation interval.
Value Area High (VAH): The upper boundary of the calculated Value Area.
Value Area Low (VAL): The lower boundary of the calculated Value Area.
The Value area (%) setting specifies the target percentage of volume to be included within these boundaries.
The default is 70%, consistent with the conventional setting used in TradingView's Volume Profile tools. The percentage can be adjusted from 1% to 100%.
For example, with a 70% setting, the analysis seeks to identify a price region around the POC representing approximately 70% of the selected volume. Because volume is organized into discrete price levels, the resulting area does not necessarily contain exactly the target percentage.
The same Value Area setting applies to profiles calculated for the whole period and for individual blocks.
Figure 15: A conceptual volume profile illustrating the Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL), with a 70% target Value Area highlighted.
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Interpreting the Value Area
The POC identifies the strongest concentration of volume in the selected profile, while VAH and VAL describe the boundaries of its principal volume region.
Comparing these levels across different blocks can help traders observe changes in the location and distribution of trading activity.
A shift in the POC, for example, indicates that the price level of maximum volume concentration has changed between observation intervals.
These levels describe historical volume distribution. They do not, by themselves, establish guaranteed support, resistance, or future price direction.
3.6.4. Offset (bars)
The Offset setting controls how far VTL's volume-based trend lines and whole-period POC, VAH, and VAL levels extend to the right of the latest candle.
The default is 19 bars, with an adjustable range from 0 to 200.
Increasing the Offset provides additional chart space for viewing extended trend lines and volume-profile levels, while also positioning their labels away from the most recent price action.
The Offset changes only the visual extension of these analytical elements. It does not change the selected period, the underlying volume data, or the calculated volume-profile levels.
Extended trend lines follow their existing direction beyond the observation period and should not be interpreted as guaranteed forecasts of future prices.
How Period and Blocks Work Together
These settings establish the time-based framework for VTL's analysis.
The Period determines how much completed price history is examined. Blocks divide that history into successive observation intervals, making changes in volume concentration easier to identify. Value Area defines the target volume coverage of the profile boundaries, while Offset controls how selected analytical levels are displayed beyond the latest candle.
Together, they allow traders to examine both the overall distribution of volume and its development across smaller intervals, creating the foundation for the volume-based trend lines and other analytical features described in the following sections.
3.7. Volume-Based Trend Lines
Traditional trend lines are generally constructed from price movements, often connecting successive highs, lows, or other significant points on a chart. While these methods describe the direction of price action, they do not directly account for where trading volume is concentrated.
Volume Trend Lines (VTL) approaches trend analysis from a different perspective. Instead of using price extremes as the primary reference, it examines how the price levels associated with concentrated trading volume change over time.
By combining volume profile analysis with statistical regression, VTL constructs trend lines that reflect the direction of volume concentration across the selected analysis period.
The ③ Trend lines section of the settings provides three independently configurable lines: Buy, Sell, and Total.
3.7.1. From Volume Concentration to Trend Lines
As described in the previous section, VTL divides the analysis period into consecutive blocks. Each block represents a separate interval in which Buy, Sell, and Total volume can be examined across price levels.
A central concept in this process is the Point of Control (POC), the price level with the greatest volume concentration within a given block.
Because Buy, Sell, and Total volume can have different distributions, each may produce a different POC.
VTL uses these block-level volume concentrations and their associated positions in time to establish the reference points for its trend lines.
Rather than simply connecting consecutive POC levels with straight segments, VTL applies statistical regression to identify the overall direction represented by these reference points.
This distinction is important. A fitted trend line summarizes the movement of volume concentration across the observation period; it does not necessarily pass through every individual reference point.
Figure 16: Conceptual illustration of volume-based trend line construction, showing POC-related reference points across successive blocks and a fitted trend line representing their overall direction, rather than connecting them individually.
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3.7.2. Buy, Sell, and Total Trend Lines
VTL provides three independent trend lines, each based on a different category of trading volume.
Buy Trend Line
The Buy Trend Line follows the development of price levels associated with the greatest concentration of Buy volume across the analysis blocks.
An upward-sloping Buy line indicates that these concentrations have generally shifted toward higher prices, while a downward-sloping line indicates a movement toward lower prices.
This describes the location of Buy-volume concentration, not necessarily an increase or decrease in the total quantity of buying activity.
The Buy line is disabled by default and is displayed in blue when enabled.
Sell Trend Line
The Sell Trend Line applies the same analytical principle to Sell-volume concentrations.
Its direction reflects how the price levels associated with concentrated Sell volume have developed throughout the selected period.
A rising Sell line does not necessarily indicate increasing selling pressure. It indicates that the fitted price location of Sell-volume concentration is moving higher.
The Sell line is disabled by default and is displayed in pink when enabled.
Total Trend Line
The Total Trend Line represents the combined distribution of Buy and Sell volume.
It identifies the overall direction of volume concentration without separating the two sides.
Importantly, the Total line is calculated from the combined volume distribution. It is not the arithmetic average of the Buy and Sell trend lines.
The Total line is enabled by default and is displayed in white.
Comparing the Three Lines
When displayed together, the three lines provide complementary views of how volume concentration develops over time.
Differences in their slopes or relative positions indicate that Buy, Sell, and Total volume concentrations are not necessarily evolving in the same way.
For example, Buy-volume concentrations may shift toward higher prices while Sell-volume concentrations remain relatively stable or move in another direction.
Such differences provide additional information about the structure of trading activity. However, the relative position or intersection of these lines should not, by itself, be interpreted as confirmation of buying pressure, selling pressure, or a future price reversal.
Figure 17: Buy, Sell, and Total volume-based trend lines displayed together, illustrating how the direction and price location of their volume concentrations can differ over the same analysis period.
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3.7.3. Linear Regression and Standard Error
Statistical basis. Linear regression is a widely used statistical method for identifying the linear relationship between observations.
The ordinary least-squares method determines the straight line that minimizes the sum of squared vertical differences between the observed values and the fitted line.
Its general equation is:
ŷ = a + bx
Here x represents the observation's position along the chart's candle sequence, ŷ is the fitted price, a is the intercept, and b is the slope.
A positive slope indicates an upward tendency in the reference prices, a negative slope indicates a downward tendency, and a slope near zero indicates relatively little overall directional change.
In VTL, this statistical principle is applied separately to the volume-concentration reference points associated with Buy, Sell, and Total volume.
Standard Error
A regression line describes the overall linear tendency of its observations, but it does not show how closely those observations follow that direction.
VTL therefore includes two additional dashed lines positioned above and below each fitted trend line.
Their distance from the central line is determined by the residual standard error of the regression, a statistical measure of the dispersion of observed values around their fitted line.
For N observations, the residual standard error is:
SE = √[Σᵢ(yᵢ − ŷᵢ)² / (N − 2)]
Here yᵢ represents an observed reference price, ŷᵢ is the corresponding fitted price, and N is the number of regression observations.
The two dashed lines are positioned at:
Upper = ŷ + SE
Lower = ŷ − SE
A smaller standard error indicates that the reference points are more closely aligned with the fitted line in price terms. A larger standard error indicates greater dispersion around that direction.
These boundaries are parallel to the central regression line and maintain a constant vertical distance from it.
Important distinction. The dashed lines represent one residual standard error above and below the fitted line. They are not statistical confidence intervals, prediction intervals, or probability-based boundaries for future prices.
At least two reference observations on different candles are required to establish a fitted line, while the standard-error boundaries require at least three reference points.
When sufficient observations are unavailable, VTL omits the affected line or its standard-error boundaries and provides an informational notice on the chart.
Figure 18: A conceptual least-squares regression line with observed reference points and parallel dashed boundaries positioned one residual standard error above and below the fitted line.
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3.7.4. Interpreting Volume-Based Trend Lines
The principal purpose of these lines is to identify the direction in which concentrated trading activity is located across successive observation intervals.
Three general interpretations are possible:
Rising trend line: The fitted price location of the selected volume concentration is moving toward higher levels.
Falling trend line: The fitted price location of the selected volume concentration is moving toward lower levels.
Relatively flat trend line: The selected volume concentrations show limited overall directional movement during the observation period.
These interpretations apply separately to Buy, Sell, and Total volume.
An important distinction is that the slope of a volume-based trend line describes the movement of volume concentration in price, not the rate of change in trading volume itself.
Likewise, a steep line does not necessarily indicate stronger trading activity than a flatter line. Its slope is influenced by the price movement of the reference levels, the chart timeframe, and the characteristics of the instrument.
The standard-error boundaries add another dimension by showing how closely the underlying volume-concentration observations follow the fitted direction.
Together, these elements can help traders examine whether the locations of concentrated trading activity exhibit a consistent directional tendency or a more dispersed pattern.
However, a well-aligned historical regression does not guarantee that the same tendency will continue.
3.7.5. Trend Line Appearance and Settings
Each of the three trend lines has its own display controls, allowing traders to examine individual volume categories or compare them on the same chart.
Visibility: Buy, Sell, and Total lines can be enabled or disabled independently. By default, only the Total line is visible.
Color: Each line has an independently adjustable color. The default colors are blue for Buy, pink for Sell, and white for Total.
Width: Line thickness can be adjusted from 1 to 5. The defaults are 3 for Buy and 2 for both Sell and Total.
Line Style: Solid, Dashed, and Dotted styles are available for the central trend line. The standard-error boundaries remain dashed regardless of the selected center-line style.
Neon Glow
The Neon glow option adds a soft visual halo around enabled trend lines on dark chart backgrounds.
It is enabled by default and is intended to improve the visual distinction of the central lines without changing their analytical values.
VTL also adjusts line colors when necessary to maintain readability against the chart background, whether the chart uses a light or dark theme.
These visual settings affect presentation only. They do not change the calculated trend lines or their standard-error values.
Line Extension
The Offset (bars) setting, introduced in Section 3.6.4, also controls the extension of the volume-based trend lines beyond the latest completed candle.
The central regression line continues along its fitted slope, while its standard-error boundaries extend in parallel.
This extension provides a visual continuation of the existing statistical relationship. It does not represent a new observation or an independently calculated forecast.
3.7.6. Data Requirements and Limitations
Volume-based trend lines depend on the quality and availability of the underlying volume information.
With Smart Volume, the analysis is based on estimated Buy and Sell volume and the selected mathematical distribution model. With Footprint, it uses the price-level volume information supplied by TradingView.
Consequently, differences in the volume engine, distribution model, analysis period, or number of blocks can affect the resulting trend lines.
The Volume engine and the selected distribution model influence the underlying volume concentrations, while the Period and Blocks settings determine the observation structure used to examine their development.
The Value area (%) setting determines the target coverage of VAH and VAL, but it does not determine the POC levels from which the trend-line analysis is derived.
Each analysis block requires at least two candles, and at least two usable blocks are needed for trend-line analysis. Missing or unusable volume information can also prevent sufficient reference points from being established.
VTL updates its analysis as new candles close. Because the observation period moves forward and its underlying volume estimates or concentrations may change, previously displayed regression lines can also change as the analysis is refreshed.
These lines should therefore be understood as dynamic descriptions of the selected volume history, rather than fixed historical boundaries or guaranteed forecasts.
Analytical Perspective
The distinguishing feature of VTL's trend lines is the information used to establish their direction.
Traditional price-based trend lines describe relationships between selected price observations. Volume-based trend lines instead describe the directional development of price levels associated with concentrated trading activity.
By examining Buy, Sell, and Total volume separately, VTL provides different perspectives on how these concentrations evolve throughout the analysis period.
The regression lines summarize their direction, while the standard-error boundaries describe the dispersion of the underlying reference observations.
Together, these features offer a statistical framework for examining volume-based market structure alongside conventional price analysis, without implying certainty about future market behavior.
3.8. Block Curves
The ④ Block curves section provides a visual representation of how trading volume is distributed across price levels within individual analysis blocks.
While volume-based trend lines describe the direction of volume concentration over time, Block Curves illustrate the distribution itself, allowing traders to examine where volume is concentrated and how Buy and Sell activity differs within each block.
VTL represents these distributions through smooth, shaded curves drawn directly on the price chart.
3.8.1. Volume Curves
Four independently configurable curve types are available:
Buy: Represents the distribution of estimated or measured Buy volume across the price levels of each block.
Sell: Represents the corresponding Sell-volume distribution.
Total: Represents the combined Buy and Sell volume distribution.
Delta: Represents the difference between Buy and Sell volume concentrations at individual price levels.
The Buy, Sell, and Total curves provide complementary views of volume concentration.
When Buy and Sell curves are displayed together, they appear as stacked distributions, with Sell volume extending beyond the Buy region. When Total is enabled alongside them, its outer boundary represents their combined distribution.
If Total is displayed on its own, it appears as a filled curve.
The width of a curve represents the relative concentration of volume at a particular price. Wider regions indicate greater concentration, while narrower regions indicate less.
Color intensity provides an additional visual reference: stronger shading corresponds to higher relative volume concentration.
3.8.2. Delta Curve
The Delta curve highlights the difference between Buy and Sell volume distributions.
At a given price level:
Delta = Buy Volume − Sell Volume
Positive Delta indicates that Buy volume exceeds Sell volume, while negative Delta indicates the opposite.
VTL uses separate colors to distinguish these conditions, making it possible to identify price regions where one side has greater volume concentration.
The Delta curve has its own display scale. Its width represents the relative magnitude of the imbalance within that block, rather than the absolute volume of either side.
3.8.3. Curve Settings
Each curve can be enabled independently, with individually adjustable colors and transparency.
The Width (%) setting controls how far the curves extend horizontally across their block. Its default is 100%, with an adjustable range from 10% to 100%.
Each block's curves are scaled to its available display width. Consequently, two equally wide curves in different blocks do not necessarily represent equal absolute trading volumes.
The High / low option displays dashed horizontal lines marking the upper and lower price rows covered by each block's volume distribution.
The Borders option adds dotted vertical lines separating consecutive blocks, making their chronological boundaries easier to identify.
All Block Curves are disabled by default.
When multiple curves are enabled simultaneously, VTL may simplify their shading or display curves for fewer blocks to remain within TradingView's graphical limits.
Figure 19: Block volume distributions illustrating Buy, Sell, Total, and Delta curves, with relative volume concentrations represented by curve width and color intensity.
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3.9. Block Profile
The ⑤ Block profile section identifies significant volume-profile levels within each analysis block.
While Block Curves describe the shape of volume distribution, Block Profile provides specific price references derived from that distribution.
Three levels are available:
POC (Point of Control): The price level with the highest volume concentration in the block.
VAH (Value Area High): The upper boundary of the calculated Value Area.
VAL (Value Area Low): The lower boundary of the calculated Value Area.
Volume Source
The Volume setting determines which volume category is used to calculate these levels:
Buy, Sell, or Total.
Total is selected by default.
Selecting Buy or Sell allows traders to examine the corresponding volume concentration and Value Area independently, rather than relying exclusively on combined volume.
The Value Area percentage follows the setting described in Section 3.6.3.
Display and Labels
POC, VAH, and VAL can be enabled separately. Each has independent color, line-width, and line-style controls.
The default POC color is orange, while VAH and VAL use blue. All three levels are disabled by default.
The Labels setting provides three display modes:
Off: Hides the labels.
Minimal: Displays a short label identifying the level, with additional information available when hovering over it.
Full: Displays detailed information directly on the chart.
Detailed labels include the block number, level price, and Buy and Sell volume associated with that price row. VAH and VAL labels also provide volume information for the relevant portions of the Value Area between those levels and the POC.
These levels allow traders to compare the locations of significant volume concentrations across successive blocks and observe how those locations change over time.
They represent the selected block's volume profile and should not automatically be interpreted as guaranteed support or resistance levels.
3.10. Period Curves
The ⑥ Period curves section extends volume-distribution analysis from individual blocks to the entire selected period.
Instead of examining each block separately, Period Curves combine the available volume information across the full observation window into a single set of distributions.
The same four curve types are available: Buy, Sell, Total, and Delta.
Buy, Sell, and Total
The Buy and Sell curves represent their respective volume concentrations across the entire period.
When both are enabled, their distributions appear stacked. The Total curve represents their combined distribution and is displayed as the outer boundary when Buy or Sell curves are also visible.
Examining the full-period distribution alongside individual blocks allows traders to distinguish broader concentrations of trading activity from those associated with shorter intervals.
Period Delta
The Delta curve represents the difference between Buy and Sell volume distributions across the full period.
Positive and negative Delta regions are shown in separate colors, indicating which side has greater volume concentration at different price levels.
The Period Delta uses its own display scale and is enabled by default.
Its shape can help identify where directional volume imbalance is concentrated across the selected observation window.
However, the Period Delta is an aggregated representation of the full period. It does not establish when the underlying trading activity occurred or whether a particular imbalance remains active in the latest candle.
Display Settings
All four curves have independently adjustable colors and transparency.
The Width (%) setting controls their horizontal display extent, from 10% to 100%, with 100% selected by default.
The High / low option, also enabled by default, displays dashed lines at the highest and lowest price rows of the period's volume distribution.
Because Block Curves and Period Curves use their own display scales, their widths should not be interpreted as directly comparable absolute volume measurements.
Figure 20: Comparison of individual Block Curves and the full-period volume distribution, illustrating localized volume concentrations alongside the aggregated Period Delta.
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3.11. Period Profile
The ⑦ Period profile section identifies the principal volume-profile levels across the entire selected period.
As with Block Profile, the three available levels are POC, VAH, and VAL.
The difference is the observation interval: Block Profile calculates these levels for individual blocks, while Period Profile calculates them for the entire period.
Volume Source
The Volume setting offers Buy, Sell, and Total as independent profile sources, with Total selected by default.
This allows the whole-period POC and Value Area to be examined using either directional volume category or their combined distribution.
Profile Levels and Appearance
POC, VAH, and VAL are all enabled by default.
Their default color is purple, with a solid POC line and dotted VAH and VAL lines.
Each level has independently adjustable color, line width, and line style.
Unlike block-profile levels, which remain within their respective blocks, the whole-period levels extend to the right according to the Offset (bars) setting introduced in Section 3.6.4.
Labels
The Labels setting offers Off, Minimal, and Full modes.
Minimal is selected by default.
In Minimal mode, the level name is displayed on the chart and additional data can be viewed by hovering over the label.
Full mode displays the level price, Buy and Sell volume at the corresponding price row, and, for VAH and VAL, volume information for the relevant portions of the Value Area.
Interpreting Block and Period Profiles Together
The whole-period profile provides a broader reference for the distribution of trading volume, while individual block profiles reveal how that distribution develops across smaller observation intervals.
Comparing them can help traders identify whether recent volume concentrations are located near the broader period's principal volume region or have shifted toward different price levels.
These levels describe historical trading-volume distribution rather than independently confirmed future price behavior.
3.12. Delta Peaks
The ⑧ Delta peaks section identifies the most pronounced positive and negative Buy–Sell volume imbalances within the selected analysis period.
Unlike Delta curves, which describe the distribution of imbalance across price levels, Delta Peaks identify specific candle and price-level locations where the greatest directional differences occur.
Peak Buy
Peak Buy marks the candle and price level where Buy volume exceeds Sell volume by the greatest amount.
Peak Sell
Peak Sell marks the candle and price level where Sell volume exceeds Buy volume by the greatest amount.
These measurements are based on the difference between Buy and Sell volume within an individual candle's price row, not simply on the candle's total Buy or Sell volume.
Consequently, a Delta Peak does not necessarily identify the candle with the highest overall trading volume.
Visual Representation
Each peak is identified by a small cross at its corresponding candle and price level.
A horizontal line extends from that location toward the right side of the chart, making the identified price easier to reference.
The associated label can display the peak price, Delta value, and Buy and Sell volumes at the identified location.
Peak Buy and Peak Sell are both enabled by default.
The default colors are blue for Peak Buy and pink for Peak Sell. Each line has adjustable color, width, and style settings.
The Labels setting offers Off, Minimal, and Full modes, with Minimal selected by default. Additional peak information remains available by hovering over the cross.
The independent Offset (bars) setting controls the extension of the peak lines. Its default is 3 bars, with an adjustable range from 0 to 200.
When no qualifying positive or negative imbalance exists, the corresponding peak is not displayed.
Interpretation
Delta Peaks highlight locations where directional volume imbalance was greatest within the selected period.
These locations may be useful when examining historical price reactions, areas of concentrated trading activity, or changes in volume-based market structure.
However, a strong historical Buy or Sell imbalance does not necessarily imply that the same side will dominate future trading at that price.
The identified peaks may also change as the analysis period advances or its underlying volume information is updated.
Figure 21: Peak Buy and Peak Sell markers identifying the strongest positive and negative candle-level volume imbalances within an analysis period, with horizontal reference lines extending from their corresponding price levels.
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3.13. Display Settings
The final section of the VTL settings, ⑨ Display, provides controls for the readability of information presented on the chart.
Text Size
The Text size setting adjusts the size of on-chart text, including informational labels and the Status panel.
The default is 15, with an adjustable range from 1 to 100.
Status Panel
The Status panel option controls the display of the indicator's volume-data information and evaluation summary.
It is disabled by default. Its contents and interpretation are explained in Sections 3.2 and 3.3.
Important data-availability notices and informational warnings remain visible when the Status panel is disabled.
Chart Appearance
VTL's adjustable colors, line styles, transparency, and curve shading allow traders to organize the display according to their chart preferences.
Selected visual colors are also adapted where appropriate to improve readability on different chart backgrounds.
These presentation settings do not change the underlying volume calculations.
3.14. Alerts and Data Window
VTL provides eight reference series for user-defined TradingView alerts: Total Line, Buy Line, Sell Line, Period POC, Period VAH, Period VAL, Peak Buy, and Peak Sell. The first three follow their respective volume-based trend lines; the next three identify the whole-period volume-profile levels; and the last two mark the prices of the strongest positive and negative Delta peaks.
These values are available when sufficient data exist, even if the corresponding chart drawings are hidden. Period POC, VAH, and VAL follow the Volume source selected in the Period profile settings.
Creating Alerts
Open TradingView's Create Alert dialog, choose the relevant VTL series under Condition, and configure an available comparison, such as price crossing a reference level. Set the notification method and frequency through TradingView. For conditions requiring a completed candle, use an appropriate bar-close frequency.
Reference levels can change as the observation period advances or the underlying volume estimates are updated. TradingView alerts use the indicator configuration saved when the alert is created, so review or recreate alerts after changing relevant settings. VTL supplies reference levels, not predefined Buy/Sell signals or entry and exit recommendations.
Data Window
TradingView's Data Window provides additional numerical outputs, including volume data, Smart Volume method evaluations, regression statistics, profile references, Delta Peaks, and configuration values. Available values depend on the active engine and data coverage. Applicable plotted values can also be examined through TradingView's chart-data export.
4. Purpose, Limitations, and Disclaimer
Volume Trend Lines (VTL) is designed for educational, informational, and independent market analysis. It helps users study where Buy, Sell, and Total volume are concentrated, how those concentrations change over time, and how directional imbalances appear across price levels.
Data and Interpretation
Smart Volume uses statistical estimates evaluated against available intrabar reference data; Footprint relies on TradingView's price-level volume data. Both are subject to data availability and classification limitations. Volume profiles, Delta Peaks, regression lines, and their extensions describe the selected observations, not guaranteed future outcomes. Values can change as new candles close, settings change, or the analysis window moves forward.
Not Financial Advice
VTL does not provide investment, financial, or trading advice, personalized recommendations, or guaranteed Buy/Sell signals. Its alerts and analytical levels are informational references, not trading instructions. Users remain responsible for independently assessing market conditions and the risks of any decisions they make.
Dostępne w Płatnej Przestrzeni
Ten wskaźnik jest dostępny wyłącznie dla subskrybentów SABANCI . Dołącz, aby uzyskać dostęp do tego oraz innych skryptów autorstwa ata_sabanci.
Measuring markets through Volume Dynamics & Geometric Frameworks.
For invite-only script access, DM on TradingView or via x.com/sabanci_ata
For invite-only script access, DM on TradingView or via x.com/sabanci_ata
Wyłączenie odpowiedzialności
Informacje i publikacje nie stanowią i nie powinny być traktowane jako porady finansowe, inwestycyjne, tradingowe ani jakiekolwiek inne rekomendacje dostarczane lub zatwierdzone przez TradingView. Więcej informacji znajduje się w Warunkach użytkowania.
Dostępne w Płatnej Przestrzeni
Ten wskaźnik jest dostępny wyłącznie dla subskrybentów SABANCI . Dołącz, aby uzyskać dostęp do tego oraz innych skryptów autorstwa ata_sabanci.
Measuring markets through Volume Dynamics & Geometric Frameworks.
For invite-only script access, DM on TradingView or via x.com/sabanci_ata
For invite-only script access, DM on TradingView or via x.com/sabanci_ata
Wyłączenie odpowiedzialności
Informacje i publikacje nie stanowią i nie powinny być traktowane jako porady finansowe, inwestycyjne, tradingowe ani jakiekolwiek inne rekomendacje dostarczane lub zatwierdzone przez TradingView. Więcej informacji znajduje się w Warunkach użytkowania.