The first thing most people do when starting a new game is to understand the rules and game mechanics. Sometimes there are just a few rules and the mechanics are straightforward. At times, the game becomes more dynamic, with more intricate rules and mechanisms. Certain games even feature distinct rule sets for each participant. As the game proceeds, the rules may alter. In other words, if you are unaware of the game's rules and mechanics, it is practically difficult to anticipate a favorable conclusion.

Financial markets are nothing more than one of the most competitive games in existence, with the world's brightest and best-capitalized players taking part. However, a study of the crypto markets over the previous year reveals that the most well-capitalized participants are seldom the wisest.

There are several sorts of financial markets, none of which are identical. External factors control (have rulesets) each one. These regulations differ across marketplaces (think equities, bonds, crypto, etc.). There are many distinct sorts of participants in each market (think "retail/uninformed" individuals or "professional/sophisticated" players like money managers, banks, hedge funds, market makers, pension funds, and so on). Central banks, a relatively recent active-market phenomenon, are perhaps the most important actors of all. These participants have their own set of rules that govern how and when they may participate in the market (for example, investment/trading mandates, rebalancing needs, size constraints, compliance & regulatory procedures, and so on).

Unsurprisingly, each sort of market participant has its own set of regulations (think about how the parameters that govern retail and institutional players differ). Regardless of the participants involved, the manner in which prices vary within a financial market has its own set of regulations (consider a prevailing theory like the efficient market hypothesis, or an alternative view in the inelastic market hypothesis).

When striving to survive and grow in markets, having a conceptual framework and knowledge of the financial market game, the many players and rulesets involved, and a manner of putting these moving parts together is critical. This article attempts to provide readers with knowledge of how to start translating these principles into actual financial market applications.

Order flow and Footprint charts

If you want to get a competitive advantage in the market, you must either be faster (doubt), smarter (doubt), or utilize the knowledge that others may not be utilizing and compete in places and ways that others cannot (bingo). Another way to look at it is that you should attempt to see things that others do not, and you should probably avoid doing things that the majority of others do.

For the sake of argument, assuming we accept the conclusions of each of the prior studies, the following question is simple. What are the practical implications of these ideas and discoveries? For example, how many players profit from an inelastic market perspective and events such as liquidity cascades, which seem to be recurrent aspects of contemporary financial markets?

If markets are reflexive and inelastic in nature, and order flow mechanics are the driving element in what drives price changes from instant to moment, it stands to reason that the order flow data itself is the most valuable data.

The goal is to present a different method of interpreting market data that is compatible with the inelastic market perspective (order flow) in order to construct a robust framework for market activity. This involves the use of a new sort of chart called a footprint chart.

Footprint charts were developed to assist traders to comprehend what is going on in the market by offering context. Footprint charts are NOT techniques, but rather different methods of viewing volume and price (order flow) data. If you are unfamiliar with these ideas and charts, they may seem a little esoteric at first. If it seems overwhelming, consider it another form of a chart, akin to a candlestick chart, but with more fine data. Understanding and interpreting these sorts of charts and data will take some effort, as with everything, but those that continue will likely learn how superior footprints are for visualizing market action.

A footprint chart, like a typical candlestick chart, displays a price range with certain regularity. A footprint chart splits up a bar by each price inside the range with an extra measure, unlike a typical candlestick chart provides four price points, referred to as OHLC (open, high, low, close) over some time period (minutes, days, weeks, etc.). This measure changes depending on the kind of footprint chart used. This is generally volume or a volume derivative such as delta.

Why should a footprint chart be used instead of typical OHLC candlesticks? Footprints allow you to study price, volume, and order flow data all at once, giving you context for what's going on INSIDE each bar or candlestick.

Periodicity - Periodicity is the method by which we measure and determine the generation of new bars and candles. As shown above, each bar is made up of a price range and numerous price levels through which the price moves. Traditional candlestick charts use time-based periodicity, in which a new bar is formed after a certain amount of time has elapsed (1m, 5m, 1h, 4h, 1d, etc.). However, there are additional forms of periodicities, such as volume-based (volume, delta) and volatility-based periodicities (range, tick).

Volume-Depending Periodicity - Bars are generated based on the amount of money exchanged or the delta.

Volume-driven bars are built using a user-specified minimum amount of volume transacted before a new bar is formed. For example, a user may enter "1,000" to indicate a frequency of 1,000 contracts exchanged. This may also be configured using the notional volume exchanged. In the above example, we can see that each new bar is formed only when a minimum of 2,500 contracts have been exchanged and that all volume bars at the bottom of the chart are similar. At the very bottom of the figure, we can also see the time elapsed for reference.

Delta-driven bars are built using a user-specified minimum delta transacted before a new bar is formed. Delta is the net purchasing or selling based on how volume was traded. If 25 contracts trade at the bid, for example, the delta is -25 because the seller is crossing the spread to the best available bid. If 25 contracts are traded at the ask price, the inverse is true, and the delta is +25. Delta tracks how much volume is traded while smoothing out price movements. It also gives traders greater context for price movement, possible reversals, and underlying market strength/weakness. In the above example, we can see that each new bar is formed only once the minimum delta criterion of 750 contracts is met. With the delta bar indicator, we can see this at the bottom of the chart. At the very bottom of the figure, we can also see the time elapsed for reference.

Volatility-Based Periodicity – Bars are created based on the actual movement of price.

Range-driven volatility-based bars are built based on the smallest price range traveled, as specified by the user before a new bar is formed. In the above example, the range periodicity is set to $150. We can see that each new bar is only formed once the price has crossed a $150 price range inside the previous bar. Within these charts, there are a few intriguing things to notice. First, observe how each bar begins at a price that is outside of the prior bar's range. Take note of how each bar closes at either its greatest or lowest price. This makes natural sense when we consider what a range periodicity of $150 signifies. At the very bottom of the figure, we can also see the time elapsed for reference.

Tick-based volatility bars are built in the same way as volume bars are, using a user-specified number of ticks. A tick is a single transaction. Many alternative tick chart settings have become popular throughout the years. This style of graphic has greater detail than traditional time-based charts. In the preceding example, we can see that a new bar is only produced once 20k transactions have occurred, as shown by the indication at the bottom of the chart. Again, at the very bottom of the chart, we can see the time elapsed for reference.

Color Shading - Each footprint type will be colored by the user's choice of two colors. These are usually red/green or red/blue. Red denotes more aggressive selling at a set price (more transactions at the bid than the ask).

footprint cluster chart

Source: Bybit

At the chosen price, blue indicates more aggressive purchasing. The hues are also colored according to how powerful the purchasing or selling was. The volume determines the strength. In other words, the amount of volume exchanged on the bid against the ask.

Footprint Type - Different kinds of footprint charts exist, such as bid/ask footprints or footprint features, delta footprints, and volume footprints.

Type 1: Footprint Bid/Ask & Footprint Profile - A bid/ask footprint shows the number of contracts transacted in real-time at the bid against the ask with a user-defined interval. Because these displays are real-time, the bid/ask footprint will vary as additional deals are conducted in the market.

Each price level will be represented by the total number of contracts traded at the bid minus the total number of contracts traded at the ask (for example, 100 x 400). The footprint chart provides participants with a straightforward method to see bid/ask order flow information, emphasizing the critical locations inside each price range without losing context regarding previous price behavior. Color shading (particularly consecutive colors) aids in providing early signals of the dominating side of the market. The stacking of blue footprints, for example, is an early indication that buyers are in command.

A footprint profile shows a vertical histogram of volume at various price levels over a user-specified period of time. The color inside the footprint profile, like other footprint types, is dependent on the delta, or the net buying/selling at each price level. Blue denotes a positive delta (buying pressure), while red denotes a negative delta (selling pressure).

Footprint profiles make it simple to see how much volume is exchanged at every price level. Combining footprint profiles with other contextual data (previous market-structure key levels, open interest, value areas with respect to current price, and existing market imbalances in relation to price) might enable high-precision decision-making during significant market changes. High-volume nodes inside footprint profiles may be used in the same way as composite volume profiles but on shorter timescales.

Type 2: Delta Footprint Profile - Unlike the bid/ask profile, the delta footprint shows a single number indicating either a positive or negative value. Again, delta is the net difference between the amount traded at the bid and the quantity exchanged at the ask. Delta displays how many more contracts were sold at the bid price vs the ask price. Remember, for the price to change, one of these factors must occur! Delta footprints are great for displaying the buying and selling pressure at each price level in real-time, as well as which side of the market is the aggressor.

Delta footprints are often used to detect possible intra-bar support or resistance relative to the current price (similar to bid/ask footprint profiles). This form of usage is restricted to extended time periods. Another possible use for delta footprints is to track market strength relative to volume as each bar is formed. For example, if the price starts to rise, we would expect to observe positive delta values, suggesting that purchasers are the aggressors. Monitoring the delta values as the market moves is crucial because we can see the buying and selling pouring in at each price level, confirming the strength of the move. The market cannot continue to advance in one way indefinitely and will ultimately reverse. Sometimes you'll witness an extreme delta value or sellers finally returning to the market (red delta coloring), signaling a possible reversal.

Type 3: Volume Footprint - Like the delta footprint, the volume footprint displays the entire volume (independent of the bid/ask) traded at each price level vs the delta. Volume footprints are useful for locating high-volume clusters/nodes. The volume footprint would be 500 if the figures from the preceding bid/ask footprint (100 x 400) were used. The deeper the hue, the more volume traded, offering traders a simple method to measure market activity throughout any time, similar to the color shading of earlier footprints.

Over time, traders who prefer to use footprint charts have been shown to trade less volatile, momentum-driven securities, such as those in fixed-income markets. Knowing how much of an item is traded at each price level is useful information for determining where the markets have the greatest liquidity. It may also assist asset managers in determining the best regions to transact in terms of opening or closing positions.

The most practical and consistent application of principles learned from the inelastic market hypothesis seems to be using real-time footprint plots based on numerous variables and varied periodicities. It is also an example of leveraging knowledge and data that most participants are unlikely to be aware of in order to compete for perfect possibilities. Next-level analysis and new market tactics become conceivable when traders learn to use these technologies.

How can we apply the technique?

How can we discover opportunities now that we have the instruments to enable us to make high-precision judgments based on inelastic market concepts? To put it another way, if footprints help us decide when to trade, how do we know where to trade?

Where do we stand in terms of market structure, and what kind of market are we in?

Some readers will be acquainted with auction market theory, a market idea (AMT). AMT, in a nutshell, is a framework for watching and trading financial markets. It attempts to identify the market's primary purpose and how market players interact with one another to achieve that goal.

A market accomplishes two major goals:

It permits two-way commerce (auction, buy/sell, etc.).
It seeks the asset's fair value over time. In other words, the volume should be dispersed somewhat uniformly throughout time. Remember this while looking at the profile/distribution-based charts presented above and throughout this article.

AMT examines market phenomena such as supply and demand, price discovery, and the auction process. A fundamental tenet of AMT is that VALUE and PRICE are separate concepts. Market or volume profiles are tools used to depict these notions.

The usage of composite profiles is an example of how we may apply the key concepts of AMT to assist us to decide where opportunities may emerge. A composite profile is just a profile view that has been blended (or aggregated) throughout many time periods. Instead of examining seven separate daily profiles, consider integrating these daily profiles into a single weekly composite profile.

We discovered that utilizing high-timeframe composite profiles may be really beneficial for spotting important opportunity zones. The accompanying chart depicts the behavior of the BTCUSD price since 2020, with a composite volume profile on the y-axis adjacent to the price level. AMT principles provide context for expected pricing action consequences based on where it occurs in relation to value regions. When looking at price action on any timescale, we may maintain the bigger significant levels in perspective by using the composite profile to indicate critical regions (such as value area highs/lows, points of control for high-volume nodes, volume gaps, or market inefficiencies).

Is it better to be balanced or unbalanced?

When markets are "in-balance" (inside a high-volume node value region), we may anticipate the price to behave quite differently from when the price is out of balance, indicating a market inefficiency or volume gap between two high-volume nodes. An old financial market heuristic holds that markets are normally rangebound, or in a position of relative equilibrium, around 80% of the time. This indicates that markets are only going in one direction, a condition known as imbalance, around 20% of the time. One of the most crucial components of trading is determining which condition the market is now in while maintaining a broader market structure in context with current price movement.

There are certain important observations to make while utilizing the above-mentioned footprint notions. Bullish patterns in trending markets will be verified by dark blue footprints, whereas bearish trends will be confirmed by dark red footprints. The related color footprints should dominate directional trending markets (the majority blue for bullish trends and red for bearish trends). Strong trends are frequently accompanied by dark bars at the top and bottom of each bar. This is great for identifying the beginning of a new trend since we know that late aggressive positions (often "FOMO" trades) are frequently penalized. When we witness lighter color shading, it indicates that a trend is losing traction.

Non-directional/rangebound markets will have different footprint colors within each bar. As a general rule, rangebound market bars will contain around 50% blue and 50% red bars, but not entirely one hue. This color fluctuation is known as candy striping, and it happens when a market returns to equilibrium or fair value over a period of time. As we know, rangebound markets often test the upper and lower bounds (highs and lows in the value region) before failing and reverting to the range. When the market approaches one of these limits, a cluster of black footprints may join the market, signaling that they are betting on a breakout from the range. We realize that the odds are stacked against these situations (all else equal). If these positions are incorrect, they will become price-insensitive players as their positions deteriorate and force them to close. Identifying opportunities like these are highly beneficial.

Integrating Market Profile (TPO) Charts

These might be the value area extremes, control points, initial balance regions, or single prints. The combination of market profile TPO charts and footprint charts may be a very strong tool for determining where perfect opportunities may emerge and when it is best to take advantage of them.

TPO stands for time price opportunity and presents a histogram similar to a volume histogram using 30-minute time rotations as input. This makes it simple to identify where the price spent the most time and where the most money was traded. These profiles are often extremely similar, however, there may be dislocations. Dislocations result in inefficiencies, while inefficiencies result in opportunities. When considering any commodity in any market, the greatest pricing prospects are frequently dictated by time. In other words, the finest buying/selling chances are often available for the shortest period of time.

If you want to extract some type of advantage from the market, you either have to be quicker, smarter, or utilize the knowledge that others may not be utilizing and try to compete in places and ways where others cannot. Another way to look at it: you should attempt to see things that others do not, and you should probably avoid doing things that the majority of others do. The concept of recognizing opportunities should become evident with this in mind.

We want to compete in markets where most others are not, and where others are price averse. The combination of market profiles and footprint maps is deadly for detecting these zones. Where have we learned about market segments where other players are compelled to transact?

Cascades of Liquidation

Liquidation cascades are huge, abrupt drops in financial markets caused by declining liquidity, overloaded financial assets, and leverage. Liquidation cascades are market occurrences in which numerous people behave in price-insensitive ways/are compelled to act against their wishes. The most typical example is the forced closing of leveraged positions amid sharp market declines, regardless of position profit or loss, as a consequence of risk criteria being exceeded or position collateral being liquidated. Because of these considerations, liquidation events are a great place to seek chances in the market.

Examples of Order Flow Application in Financial Markets

In this part, we will look at these principles in several markets, including equities futures, commodities (including cryptocurrency), fixed income, and even currency futures. Finding appropriate order-flow principles and patterns across several marketplaces validates the theories we've utilized to get here. Furthermore, all of these notions may be used across a variety of times. These tools may be used by scalpers on lower periods and by long-term traders on larger timeframes.

Example of Equity Futures - SPX

Because of their high liquidity and volatility, SPX futures are one of the most popular securities traded in financial markets. Volatility (the amount the price wiggles) is vital since there isn't much potential without it. Volatility is often followed by spikes in volume, and since footprint charts track these parameters in real-time, we may deduce potential market routes.

spx delta footprint cluster

Source: Exocharts

The chart above shows ES mini futures contracts moving sideways or rangebound over a several-day timeframe. We're using a delta periodicity of 2,500, which means that a new bar is formed when the delta hits +2,500 or -2,500.

The idea here is that with delta periodicity, new bars are formed only when buying and selling become sufficiently unbalanced. Remember this for future instances. In the above example, we can see the constant dark blue delta imprints as price breaks out of the rangebound region, suggesting that buyers are in charge and that the ongoing move may have some fuel. We can also notice that volume is rather low throughout the price surge. This verifies an imbalance, with buyers outnumbering sellers and achieving the +2,500 delta criterion despite a low overall amount of transactions.

We know that markets do not continue to trend continuously; the market spends the bulk of its time in relative equilibrium. Tops and bottoms, although perilous, are also the most profitable possibilities. Delta at extreme price levels (HOD or LOD) may provide an excellent opportunity to identify future reversals.

This is referred to as delta divergence. When a new high of day (HOD) or low of day (LOD) occurs, a delta in the opposite direction ensues. A HOD with a negative bar delta, for example, maybe a sell indication. The SPX futures markets are used in the example above, but the same ideas may be extended to other equity futures markets such as the Russell 2000, Nasdaq, Eurostoxx 50, Dow Jones, and so on.

US 10-Year Treasury Notes

Those interested in fixed-income markets can benefit greatly from several of the methods discussed in this article. Typically, the most liquid markets are the US Treasury markets. The accompanying graphic depicts US 10Yr Treasury Note futures, however, bear in mind that the same themes apply to numerous fixed-income markets. These fixed-income markets vary significantly from risk assets in that Treasury assets have far lower price volatility.

Because Treasury markets lack volatility, successful trading tactics may vary from those found in risk-asset markets. Treasury markets, for example, have fewer and less forceful price rotations than their equity-market equivalents. This is due to the amount of volume traded at each price level, which is a result of the Treasury market being one of the deepest and most liquid markets in existence. Because of the unusually high number of trades at each price level, directional order flow measurements become less important.

People that use footprints in these marketplaces have often gravitated toward volume footprint profiles, which allow them to track supply and demand with more detail. The profile/distribution form, as we know, instantly shows regions of significant liquidity as well as liquidity pockets/imbalances. It also enables traders to swiftly assess the fair value/price extremes of the Treasury market. This is particularly relevant for asset managers with investment mandates who want to trade at the most liquid price levels or another criterion.

Gold

Commodities are also suitable for order-flow testing. Gold, the most recognizable commodities market, is an excellent testing ground for our products. There are other gold markets, therefore we will concentrate on one of the more liquid futures markets, GC, which is traded on the COMEX. A rather unusual aspect of gold markets is that a significant percentage of nighttime trade (in comparison to US trading sessions) happens when the London markets open. This has been a noticeable trend in other commodity markets, such as grains and even Bitcoin.

In the above example, we are looking at gold contracts, GC, on an intraday timeframe with a delta 500 frequency. The chart's right side displays the previous week's composite volume profile, with highlighted locations to be mindful of. A rather balanced weekly profile is shown, suggesting a time of stabilization throughout the previous week. Price is breaking out of the previous week's value area, and we are seeing strong selling below the value-area bottom. Price rapidly returns to the value zone, punishing late sellers, and continues towards the previous week's value-zone high.

Example of Currency Futures - British Pound Futures

It should come as no surprise that we can now apply the same principles and methods to currency markets (futures). Spot forex markets (cash) do not aggregate volume as exactly as futures markets do, which is critical for our tools and ideas to function properly. Currency markets run around the clock, making global timezones more important than, say, equities markets. Knowing when the key sessions (Asia, London, US/CME, after hours) are open is vital for trading in these markets, particularly when employing volume, liquidity, and order-flow concepts. The graphic below looks at British Pound futures, but the concepts may be extended to any currency futures contract.

british future chart

Source: Exocharts

In the preceding graphic, we use a delta footprint profile in combination with another composite volume profile with a delta 750 periodicity. On the left side of the chart, we can see the weekly volume composite, which includes all volume traded during the first week of 2023. Toward the conclusion of the week, the pound started to slip out of the value range established in previous trading sessions. We know that if a break from value is to be maintained, volume and delta should corroborate it.

Take note of the first blue box, which indicates a price/delta divergence. Prices recaptured the value region in the following trading sessions and proceeded to retest and finally break out from value to the upside. Later in the chart, we witness a similar dynamic as prices return to and retest the previous breakout zone. Volumes dried up during this drop and retest, and we witness another price/delta divergence. This might be an indication of a weaker selling rotation. This breakout zone held, and the price proceeded to rise, with corroborating volume and delta.

Conclusion

Confidence is often cited as one of the most essential characteristics influencing market success. In financial markets, benefits cannot be obtained without incurring risks. The capacity to take risks is critical for success, especially when things are going wrong. The framework through which we see and evaluate the market contributes significantly to our confidence and capacity to continuously take risks.

Take note of how we use principles from auction market theory/inelastic market hypothesis with the market profile and footprint tools in each market type. The fact that this is achievable, beneficial, and straightforward across all of these marketplaces validates the frameworks and tools that we have developed and tested so far.

Disclaimer:
This article is intended for and only to be used for reference purposes only. No such information provided constitutes advice or a recommendation that any investment or trading strategy is suitable for any specific name.

Order flow and how we apply it to the market