$ Pine Script Volume Profile

What is Volume Profile?

• ▸ Point of Control (POC): The price level with the highest traded volume for the specified period. It represents the price where the most trading activity occurred and is considered a fair value area.
• ▸ Value Area (VA): The price range where a significant percentage of the total volume (typically 70% or 68%) was traded. It signifies where the majority of participants found value.
• ▸ High Volume Nodes (HVN): Price levels where a large amount of volume was traded, indicating areas of agreement or consolidation. These often act as strong support or resistance.
• ▸ Low Volume Nodes (LVN): Price levels where very little volume was traded, indicating areas of disagreement or rapid price movement. These often act as weak support/resistance and tend to be easily broken through.

Components and Calculation (Conceptual)

1. Define the Analysis Period: This can be a specific session (e.g., daily, weekly) or a fixed number of bars (e.g., last 100 bars).
2. Determine Price Range: Identify the high and low prices within the analysis period.
3. Define Bins: Divide the price range into a specified number of equal price "bins." For example, if the range is $10 and you want 10 bins, each bin would be $1 wide.
4. Distribute Volume: For each bar within the analysis period, distribute its volume across the price bins that its `high`-`low` range covers. If a bar's `high` is in one bin and its `low` in another, its volume is proportionally distributed.
5. Aggregate Volume per Bin: Sum up the volume for each price bin.
6. Identify POC, VA, HVN, LVN: Once the volume distribution is complete, the POC is the bin with the highest volume. The Value Area is found by accumulating volume from the POC outwards until the specified percentage (e.g., 70%) of total volume is reached.

Basic Volume Profile Implementation in Pine Script

//@version=5
indicator("My Volume Profile", overlay=true, max_bars_back=500)

// --- User Inputs ---
profileType = input.string("Fixed Range", title="Profile Type", options=["Fixed Range", "Session Profile"])
fixedRangeBars = input.int(100, title="Fixed Range Bars (for Fixed Range Profile)", minval=10, maxval=500)
numberOfRows = input.int(20, title="Number of Rows (Bins)", minval=5, maxval=100)
valueAreaPercentage = input.int(70, title="Value Area (%)", minval=50, maxval=99)

// --- Plotting Colors ---
upVolumeColor = input.color(color.new(color.lime, 40), title="Up Volume Color")
downVolumeColor = input.color(color.new(color.red, 40), title="Down Volume Color")
pocColor = input.color(color.new(color.purple, 0), title="POC Color")
vaColor = input.color(color.new(color.yellow, 60), title="Value Area Color")

// --- Implement Volume Profile Logic ---
if profileType == "Fixed Range"
    profile = volume.profile_fixed(fixedRangeBars, numberOfRows, valueAreaPercentage)
    if barstate.islast and not na(profile)
        profile.plot(upVolumeColor, downVolumeColor, pocColor, vaColor)
else if profileType == "Session Profile"
    profile = volume.profile_session(numberOfRows, valueAreaPercentage)
    if not na(profile)
        profile.plot(upVolumeColor, downVolumeColor, pocColor, vaColor)

// Note: Pine Script's built-in `volume` module handles the complex drawing
// of the histogram, POC line, and Value Area shading automatically.

Supply & Demand Hotspots

Practical Volume Profile Trading Strategies

//@version=5
strategy("VP: HVN/LVN Strategy", overlay=true)

numberOfRows = input.int(30, title="Number of Rows (Bins)", minval=5, maxval=100)
valueAreaPercentage = input.int(70, title="Value Area (%)", minval=50, maxval=99)

profile = volume.profile_session(numberOfRows, valueAreaPercentage)

if not na(profile)
    profile.plot(
        color.new(color.lime, 40),
        color.new(color.red, 40),
        color.new(color.purple, 0),
        color.new(color.yellow, 60)
    )

if not na(profile) and barstate.isconfirmed
    pocPrice = profile.poc_price
    longCondition = ta.crossover(close, pocPrice)
    shortCondition = ta.crossunder(close, pocPrice)
    if longCondition
        strategy.entry("Long POC Break", strategy.long)
    if shortCondition
        strategy.entry("Short POC Break", strategy.short)
    strategy.close("Long POC Break", when=shortCondition)
    strategy.close("Short POC Break", when=longCondition)

//@version=5
strategy("VP: Value Area Strategy", overlay=true)

numberOfRows = input.int(30, title="Number of Rows (Bins)", minval=5, maxval=100)
valueAreaPercentage = input.int(70, title="Value Area (%)", minval=50, maxval=99)

profile = volume.profile_session(numberOfRows, valueAreaPercentage)

if not na(profile)
    profile.plot(
        color.new(color.lime, 40),
        color.new(color.red, 40),
        color.new(color.purple, 0),
        color.new(color.yellow, 60)
    )

var float prevVAH = na
var float prevVAL = na
isNewSession = ta.change(time("D"))

if isNewSession[1] and not na(profile[1])
    prevVAH := profile[1].value_area_high
    prevVAL := profile[1].value_area_low

prevVAH := nz(prevVAH[1], prevVAH)
prevVAL := nz(prevVAL[1], prevVAL)

if not na(prevVAH) and not na(prevVAL)
    longAbsorption = open < prevVAL and close > prevVAL
    shortAbsorption = open > prevVAH and close < prevVAH
    if (longAbsorption)
        strategy.entry("Long VA Absorb", strategy.long)
    if (shortAbsorption)
        strategy.entry("Short VA Absorb", strategy.short)

//@version=5
strategy("VP: POC Strategy", overlay=true)

numberOfRows = input.int(30, title="Number of Rows (Bins)", minval=5, maxval=100)
valueAreaPercentage = input.int(70, title="Value Area (%)", minval=50, maxval=99)

profile = volume.profile_session(numberOfRows, valueAreaPercentage)

if not na(profile)
    profile.plot(
        color.new(color.lime, 40),
        color.new(color.red, 40),
        color.new(color.purple, 0),
        color.new(color.yellow, 60)
    )

var float prevPOC = na
isNewSession = ta.change(time("D"))

if isNewSession[1] and not na(profile[1])
    prevPOC := profile[1].poc_price

prevPOC := nz(prevPOC[1], prevPOC)

if not na(prevPOC)
    longPOCBreakout = close > prevPOC and close[1] <= prevPOC[1] and volume > ta.sma(volume, 20) * 1.2
    shortPOCBreakout = close < prevPOC and close[1] >= prevPOC[1] and volume > ta.sma(volume, 20) * 1.2
    if (longPOCBreakout)
        strategy.entry("Long POC Breakout", strategy.long)
    if (shortPOCBreakout)
        strategy.entry("Short POC Breakout", strategy.short)

Optimizing Volume Profile Performance

• ▸ Contextual Analysis: Volume Profile is best used in conjunction with price action and overall market context.
• ▸ Timeframe Selection: The chosen `profileType` and the chart's timeframe greatly impact the profile's relevance.
• ▸ Number of Rows (Bins): Experiment with the `numberOfRows`. Start with 20-30 and adjust.
• ▸ Value Area Percentage: The default 70% is common, but some traders prefer 68%.
• ▸ Confluence with Other Indicators: Volume Profile levels gain significant strength when they align with Moving Averages, Fibonacci Retracements, Trendlines, and Psychological price levels.
• ▸ Volume Confirmation: Always seek confirmation from volume. A breakout with strong, increasing volume is more reliable.
• ▸ Market Open/Close Behavior: Pay attention to how price reacts to the previous session's POC and Value Area boundaries.
• ▸ Fixed vs. Session Profile: Understand when to use each. `volume.profile_session` is for recurring periods while `volume.profile_fixed` is for analyzing specific ranges.

Institutional Footprint

Common Volume Profile Pitfalls

• ▸ Lagging Nature: Volume Profile shows where volume *has been* traded, not where it *will* be traded.
• ▸ False Signals: Price can temporarily penetrate or "fake out" around key Volume Profile levels.
• ▸ Over-Reliance: Using Volume Profile as the sole decision-making tool without considering broader market context.
• ▸ Data Quality: The accuracy depends on the quality and granularity of volume data.
• ▸ Visual Clutter: With too many profiles or too many rows, the chart can become overly cluttered.
• ▸ Dynamic Nature in Strategies: Implementing strategies based on *previous* session's data can be tricky.

Conclusion