Origin
The story starts on the trading floor of the Chicago Board of Trade in the 1980s. Trader J. Peter Steidlmayer felt that the standard tools of the time — candlestick charts and simple volume histograms — couldn’t tell him what was actually happening in the market. His answer was to treat price as an auction, and to visualize which price levels attracted the most trading activity over time. The result was Market Profile, and two of its core concepts — the Point of Control (POC, the single most-traded price) and the Value Area (the price range covering the bulk of trading) — became the foundation for everything that followed in order flow analysis.
The limitation was that Steidlmayer’s approach still summarized an entire session after the fact. That changed once electronic trading replaced open-outcry pits in the early 2000s and every single execution began being logged in real time. In 2003, a company called MarketDelta, founded by Trevor Harnett, launched the first software to break this execution data down inside a single bar — showing, price level by price level, how much volume traded on the buy side versus the sell side. MarketDelta trademarked the chart as “Footprint,” which is why different platforms now use different names for the same underlying idea: Sierra Chart calls it “Numbers Bars,” NinjaTrader calls it “Volumetric Bars,” MotiveWave calls it “Volume Imprint.” MarketDelta itself moved onto a CQG-based platform after 2016, and in 2024 TradingView added native footprint charting, turning what had been an institutional-only tool into something any retail trader can open.
Why It Was Needed
A standard candlestick tells you the open, high, low, and close, plus one number for total volume. It says nothing about who was more aggressive inside that candle — buyers or sellers — or which specific price level actually saw the fight. Classic oscillators like RSI or MACD don’t fix this either; they’re derivatives of price, reprocessing what already happened rather than showing who is actually doing the trading.
Volume Footprint targets exactly this gap: showing not just how far price moved, but how much buying and selling pressure sat behind that move. If price barely moves while a huge volume prints at one level, that’s absorption — someone is quietly absorbing everything thrown at that price. If price blows through a level on comparatively thin volume, that’s imbalance — one side is overwhelming the other. Neither candlesticks, moving averages, nor RSI can make this distinction.
How It Works
A footprint chart splits each bar into rows, one per price level, with the buy-side and sell-side executed volume shown side by side (the left/right convention varies slightly by platform, but the underlying idea is identical everywhere). Three metrics come out of this structure:
- Delta: the net difference between buy-side and sell-side volume within a bar or price level. A strongly positive delta means buyers were in control; a strongly negative one means sellers were.
- Point of Control (POC): the single price level with the most volume in a given period — read as the price the market currently agrees is “fair,” and a common point of support or resistance when price revisits it.
- Cumulative Volume Delta (CVD): delta accumulated across many bars. When price keeps rising but CVD starts rolling over, that divergence is an early warning that the buying actually pushing price up is losing strength.
On top of this, an “imbalance” overlay flags price levels where the buy/sell ratio crosses a threshold (commonly 3:1), making it easy to spot exactly where one side overwhelmed the other. Reading delta, POC, and imbalance together — bar by bar — is the essence of order flow trading: figuring out, in real time, which side is actually winning at a given price.
Sell volume (bid hit)
Point of Control (POC)
Proof It Works, the Tools, and How to Start
The clearest evidence this isn’t just theory comes from Fabio Valentini, an Italian futures trader based in Dubai (UAE) who scalps Nasdaq futures (NQ) almost exclusively during the New York session. He has finished in the top three of the futures scalping division of the Robbins World Cup Trading Championship for three consecutive years, with multiple sources consistently citing an audited return of more than 500% in a single year, and quarterly returns of 69%, 90%, 218%, and 160% across separate competitions. Multiple sources also confirm he executed over 2,000 trades in a 12-month span.
He describes his own framework as three steps — Direction, Location, and Aggression: establish the broader directional bias from price structure, locate where price currently sits within the Value Area, and finally confirm actual aggressive buying or selling using footprint and CVD before entering. His toolset — Volume Profile, VWAP, footprint charts, and CVD — maps directly onto the concepts above.
Two caveats matter here for accuracy. First, “audited” refers to the trading contest’s own internal verification process, not an independent third-party auditor, and the contest itself carries an official disclaimer that results may not represent a participant’s overall trading performance. Second, Valentini isn’t the field’s only verified performer — the same championship’s 2023 futures record was Ivan Scherman’s 491.4%, from Argentina — which suggests order flow and futures scalping as a discipline has produced a broad pool of verifiably strong traders, not just one standout name.
Tools available today: NinjaTrader’s “Order Flow+” suite (Volumetric Bars, CVD, Volume Profile together), Sierra Chart’s “Numbers Bars,” and — since 2024 — native footprint charting on TradingView. Open-source TradingView scripts inspired by Valentini’s public methodology (combining delta, imbalance, and low-volume-node detection) are also available, letting traders learn the concepts before paying for a dedicated data feed.
Getting started: (1) pick a platform that supports footprint charting — TradingView, NinjaTrader, or Sierra Chart; (2) restrict yourself to genuinely liquid instruments such as futures or major cryptocurrencies, since volume fragmented across multiple venues distorts the delta reading; (3) spend time simply watching how POC, delta, and imbalance line up with actual price behavior before placing any trades; (4) practice distinguishing absorption from imbalance on a small account or simulator before trading live size.
Limitations: order flow reading leans heavily on discretion and is hard to reduce to a fully mechanical rule set. It’s also expensive and difficult to backtest in the traditional win-rate/drawdown sense, since it requires tick-level execution data. In thin or fragmented markets, delta itself becomes unreliable. This is less a signal that hands you an answer and more a lens for reading who is winning the fight at this exact moment.
Where It Fits
Volume Footprint earns its keep in short-term and intraday scalping on liquid futures and major assets. It’s an information layer supporting discretionary judgment rather than a standalone mechanical system, which makes it a poor fit for traders who can’t watch the screen closely, or for longer-horizon swing and position strategies.
UQ’s 6-Layer engine reads market participant strength through multi-timeframe (1h/4h/1d) candles and volume-based analysis (MTF_ORDERFLOW, AI_VWAP) in a directionally similar spirit, but it doesn’t interpret tick-by-tick executions the way a footprint chart does. The two are best understood as tools built for different jobs — a discretionary scalping instrument versus a swing-timeframe automated engine — rather than one being a smaller version of the other.