Smart money concepts explained: Market makers, liquidity & order flow

Does smart money really control the market, or is price action driven by liquidity and order flow? This deep dive explains how institutional traders, market makers, accumulation, and failed breakouts shape market behavior beyond common trading myths.

The concept of “smart money” and its variations are becoming increasingly popular, as traders try to understand and explain how big institutional order flow works. In the retail trading industry, however, there are many myths around how institutional money usually works. 

In this article, we will go through major concepts that intersect with reading the “big order flow” and try to reflect on what actually works, what is the collective belief (not necessarily backed by evidence), and how to get maximum value from understanding the institutional order flow.

Disclaimer: There are no right or wrong answers in trading; every technique has its place in trading if executed correctly. The information in this article is provided for informational purposes only and should not be used as trading or investment advice.

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Does smart money always move the market?

Before diving into this topic, let’s think: Does big necessarily mean smart?

There’s a myth circulating in the trading community that big market participants rule price action and guide price movements in whatever direction they need.

The reality, however, is a bit more complex. Many big market participants interact with each other in the markets; some of them benefit from their operation, others suffer in the same way as any random “small trader.”

However, more often than not, big institutional flow is synchronized with major current market trends. This can amplify major market moves or cause intermediate to long-term reversals. That’s why studying how institutional order flow works can be seen as beneficial for understanding the market in general and generating precise entry points.

Who are the smart money market participants?

To better understand what institutional traders really do and avoid simplifications like “banks, hedge-funds, market makers”, let’s distinguish “buy side” and “sell side” liquidity traders.

Historically, before the electronic era of trading, traders were divided into two major groups: “floor traders” who were essentially individual market makers or floor brokers, and “upstairs traders”, who received phone calls from large institutional investors and brought those orders to floor brokers to execute in the trading pit.

Institutional trading floor activity illustrates how large market participants interact across futures and derivatives markets.

Both groups of traders had completely different goals. The goal of floor traders was to generate profits within a single day, so their goal was to buy at the lower side of the supposed range, and sell at local peaks, capturing short-term shifts in the “flow”. They were providing liquidity and getting paid for that. Today, we call them “scalpers” or “market makers”.

Bigger traders, on the other hand, might have been taking small losses, giving margin for floor traders for profitability. However, their perspective might have been much broader—aiming for bigger trends and operating larger portfolios. Both groups of traders have been considered as professionals, but they had different timeframes, risk management, and objectives.

That’s why, to understand the logic behind “big market participants”, we need to first determine which timeframe we are operating within and who is in control of the price at that specific moment.

Let’s start from the bottom up, debunking some myths, distinguishing the categories of institutional traders, and trying to understand their actions.

Market makers and their role in institutional order flow

Let’s start with the core liquidity providers or market makers (MM). When one trades CFDs on the MT4 or MT5 trading terminal, a CFD broker might serve as a market maker for a trader, i.e., providing liquidity both on the bid and ask side of a trade. 

While CFD brokers provide guaranteed liquidity to the trader, the process might be a bit different for centralized stock or futures exchanges, ECNs, or interbank FX markets.

The goal of a market maker is to establish buy limit orders below the current market price and sell limit orders above it to earn small profits from the bid-ask spread difference.

The eager buyer needs to hit the ask price with a market order to execute a trade, and the aggressive seller needs to hit the bid.

Hypothetical XAUUSD order book showing sell-side liquidity above price and buy-side liquidity below price. Source: AI-generated image by author.

Markets are auctions: to balance demand from buyers and supply from sellers, the price needs to move within a certain trading range.

How do market makers provide liquidity?

The principle behind providing liquidity usually works in such a way that a market maker holds larger amounts of resting orders at some distance from the last price. The market maker doesn’t want to burn all liquidity near the current price, as any rapid price movement may “squeeze the book,” leaving the market maker with the uncovered one-sided position that it later will need to close with a loss.

So, a market maker usually tries to distribute resting limit orders around the current price in a certain range around the “mid-price”, creating the so-called “market maker cloud”—essentially a short-term trading range, preventing quick one-sided price movements, smoothing out “wicks,” and enabling it to move in a range-bound environment.

This liquidity structure gives a mean-reversion skew to price movements.

Simply said, it’s easier for the price to return to the body of a short-term trading range (at least temporarily) than to break and trend. That doesn’t automatically mean that trends don’t happen. In fact, it’s quite the opposite, trends happen quite frequently but over very short time periods, the mean-reversion component dominates as the flow usually isn’t strong enough to break the “floor” or  “ceiling” of a market maker cloud.

The movie Cast Away comes to mind as a metaphor. In the film, the hero, played by Tom Hanks, tries to sail beyond the large tidal wave and fails.

The mechanism of building a “market maker cloud” makes the market more efficient and smooths out the action to the benefit of most market participants: nobody wants to have a noisy market with huge wicks in both directions.

Of course, this works only if the price flow is not overly aggressive: in the latter case, we observe quick and furious breakouts.

How volume distribution reveals trading ranges

The best way to visualize the “market marker cloud” is to watch the shape of the so-called market profile (and volume profile), which indicates the trading range within which the business is being conducted.

The picture below references the 30-minute XAUUSD timeframe, and indicates the approximate trading range for the majority of trading activity for the given day.

The corresponding range is the area between VAH (value area high) and VAL (value area low), which is known as a value area. This area aggregates most of the trading activity within the range.

That is clearly visible in hindsight, while in real time, there’s much uncertainty around the day’s actual trading range. But I want to focus on the main principle—the prevalent market behavior is to lock within a trading range for some period of time because the order flow doesn’t have enough power to break the ceiling or the floor of a “market maker cloud”.

XAUUSD TPO market profile showing VAH, VAL, and point of control within a short-term trading range.

That principle leads to the most common outcome: most “breakouts” tend to fail, and volatility tends to decrease rather than to escalate as resting liquidity on both sides of the range keeps the price auction from escalating further, cutting off the action. Of course, that doesn’t automatically mean breakouts and trends don’t happen; it simply highlights the short-term domination of resting liquidity makers (market makers) versus aggressive traders (liquidity takers).

Another representation of this principle is visible using a basic Bollinger Bands indicator, which visualizes two standard deviations from the simple moving average indicator.

Green and red areas represent borders of the “liquidity cloud,” and in most cases, the price pulls back to the range, aiming to test the indicator’s middle line. Don’t treat it as a trading strategy; it’s just a basic mean-reversion model. To turn it into a trading system, a trader would need more risk and trade management amongst other things.

XAUUSD 30min chart with Bollinger Bands and pivot zones illustrating mean-reversion behavior near liquidity boundaries.

How institutional traders accumulate and distribute positions

Prices don’t always remain within their range: trends would occur more often than they should if price action were random. In this paragraph, we will discuss the accumulation and distribution process carried out by big investment funds and institutions.

The keyword for understanding this process is size. The size of the trades executed by "whales" are often so big that they need to be split into smaller fractions.

From the information above, you should understand that if somebody drops a huge market order, the order book will be “squeezed” immediately, leading to a big price spike and eventually, a wick.

That’s why, if you were to place yourself behind the trading desk of a big investment bank, you would understand that if you have a big order to execute, you’d need to accumulate it slowly and consistently. Buying small amounts of an asset at the beginning of the day, adding to your position during the European session, adding a little more during the US session, using pullbacks, etc. 

That’s why the digital trace of a big buyer is consistency.

Let’s take a look at the May 2026 Nasdaq (USTECH100) rally. The buying flow is distributed evenly across multiple sequences of days, and is represented in either directional price action during the US session or the consistent support of the market during pullbacks.

USTECH100 H1 chart showing consistent directional buying flow and gradual institutional accumulation.

The rapid and furious price action rarely corresponds with the behavior of institutional buyers (or sellers); they usually occur as a result of long liquidations, short squeezes, interventions from central banks (rare occasions), or reactions to the news. In short, many occur as either the emotional reaction to changing market conditions, earnings reports publications (for stocks), margin calls, and other similar effects. The continuation of the trend after rapid liquidation breaks (quick and volatile decline) or profit-taking rallies, is a less likely scenario.

Another good example is the accumulation visible on the chart of NVDA stock. Here, we observe continuous repetitive volume inflow at the beginning of each session.

NVDA intraday chart highlighting repeated accumulation zones and recurring volume inflows.

If I observe the described action, I would definitely try to position within the same direction as the recognized order flow. This might not be as easy as it sounds because the institutional buyer is not rushing to get into the trade at any available price, preferring not to amplify breakouts. Thus, a strong flow in one direction might be a trader’s ally, but trade execution needs to align with the price action as well because the majority of it might be messy and noisy with occasional inflows of volume in the trend’s direction.

You can see different examples in the XAUUSD chart below. The big price squeeze on both sides occurs amid the absence of notable institutional activity.  A rapid decline to the left is replaced with a consolidation, after which the price moves rapidly to the upside, falling back into the range thereafter. 

That is a typical market reaction, but it is not a basis for a trading system yet. This is an observation to consider while preparing for the day and analysis.

XAUUSD intraday chart showing sharp liquidity-driven price spikes followed by failed follow-through and range reversion.

Shakeouts, liquidity squeezes, and failed breakouts

One of the most intriguing topics in a trading community is whether or not big market participants initiate “liquidity squeezes" and “shakeouts”?

"Fake breakouts" or when the borders of the trading ranges fail under testing are often observed on the charts of different financial assets. That’s why traders have been asking the same questions: Are those moves intentional? Do they aim to “squeeze” the stop losses of retail traders?

My personal opinion on the topic is that, in most cases, these moves have nothing to do with “stop runs”. The reason is quite simple: the area above the “market maker cloud” tends to be quite “thin,” which rarely corresponds with meaningful volume spikes of volume when the prices test the area. Given how thin the area is, it often leads to a rapid spike (wick), that doesn’t have enough volume to accumulate a position for any institutional buyer or seller.

For the sake of example, let’s take a couple of situations from the stock market (as it usually contains transparent information about volume, which might be easily validated)

AMD stock: 13 March 2026

The price tested the horizontal level after the price action, but the aggression comes from sellers, as the buying activity preceding the decline was quite modest. The seller has hit bids, initiating a massive price decline, but this probably wasn’t the result of any “shakeout,” as we’d see the green bar on the volume histogram in this case.

This can be seen as a normal or regular sell-off, not a “shakeout,” because the seller simply took advantage of the retest and has taken action.

AMD intraday chart showing a failed retest near resistance before the aggressive sell-side pressure triggered a sharp decline.

Of course, there are situations where volumes grow substantially at the moments of failed breakouts. This is usually associated with the fight between two (or more) behemoths—one big market participant against the other. The retail volume very rarely satisfies the needs of institutional traders for liquidity.

Interestingly, failed breakouts were described far before retail trading became popular.

In his 1930’s book titled, “The Richard D. Wyckoff Method of Trading and Investing in Stocks”, Wykoff described what he called “springs” (failed breakout to the downside) and “upthrusts” (failed breakout to the upside).

In the book, he speaks about the same phenomenon that we observe in the markets today—price retests of areas above and below important price levels or trading ranges before initiating the move. So there’s nothing particularly new in this type of action. The described events are typical of the market and usually represent a normal auction process, when the market “checks” certain levels or areas before moving in any direction.

Final thoughts on smart money trading

There are many myths surrounding "smart money", with a few of them creating actual trading opportunities.

If you look at the core, “big money” is not a monolithic entity executing coordinated stop runs against retail accounts. It is a fragmented ecosystem of institutional participants operating with vastly different objectives, timeframes, and execution techniques.

• The liquidity cloud vs trend inflow: Market makers naturally enforce a mean-reverting environment in the short term by distributing limit orders to smooth out volatility. Directional trends only develop when an aggressive buy- or sell-side flow is powerful enough to break through this baseline "cloud."
• Consistency over aggressiveness: True institutional positioning is defined by consistency, not speed. Because of their size, large funds must split orders into fractions and accumulate or distribute positions quietly and evenly across sessions. Conversely, furious intraday spikes and violent wicks are usually signs of thin localized liquidity , emotional news reactions, or liquidations, but rarely are they footprints of big market participants accumulating positions.
• Auctions, not conspiracies: Failed breakouts, Wyckoff springs, and structural retests are not intentional traps designed to hunt retail stops. They are the standard, centuries-old mechanics of the market auction process, checking for depth before moving to the next level of value.

Ultimately, institutional order flow shouldn't be treated as a conspiratorial cheat code. It is simply a framework for understanding who controls the market action, and for a savvy trader, it might offer valuable trading insights.