Coffee Price Dynamics – Part 2
- Igor Bragato
- 4 days ago
- 7 min read
Do you want to know how coffee prices really work? Are you prepared for the mental work it takes to really understand the answer?
In Part 1 of this series, we began answering the difficult question of how coffee prices work by breaking down trends and seasonality — the structural backbones of coffee price dynamics.
But on their own, they do not explain some of the extremes in coffee price action, for example, why markets overshoot. Nor do they explain false breakouts, or why being right about price direction and wrong on timing can still cost a lot of money.
To understand the answer to these questions, we will have to dive even deeper into coffee price dynamics.
In Part 2 of this article, we explore cycles and noise, the forces that dictate long-term price behavior and short-term chaos. So, if you're still with us and you want to know the truth, let’s finish what we started and enter the world of Coffee Price Dynamics.
Cycles: Beyond the Calendar
Cycles are long-term fluctuations that predict the general back and forth flow of price related to the broader Supply and Demand dynamics of surplus and deficit. Note this oversupply /undersupply fluctuation is not fixed to a certain timeline.
Commodity markets, such as coffee, are inherently cyclical: investment and disinvestment cycles, price-driven production responses, and multi-year weather patterns.
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The S&D cycle is a long-term feedback loop. Coffee and other planted agricultural commodities are relatively inelastic, so they respond slowly to price signals. If prices rally by, say, 100c, growers are clearly incentivized to increase production, but they can’t instantly “magic up” more trees or acreage.
As a result, supply adjustments take time; it’s a delayed feedback system that typically takes years to unfold. This means that increased production tends to lag high prices by a few seasons, just as prolonged low prices take time to erode farmer margins and effectively reduce global production.
Over a multi-decade horizon, this generates a self-correcting mechanism where high prices become the “cure” for low supply and strong demand, incentivizing larger production and tempering consumption. Similarly, low prices become the “cure” for oversupply by disincentivizing production.
So high prices incentivize additional supply and softer demand then reduce prices, which discourages production and revives demand — setting the stage for higher prices once again, and the cycle repeats itself over time.
As a result, coffee prices — like those of other commodities — tend to follow a wave-like pattern, oscillating between bullish and bearish cycles, much as the broader economy moves through phases of expansion and recession.
A simple way to think about a coffee market cycle is to ask: “where are we in the longer-term supply–demand adjustment process, and how are past prices still shaping future production and consumption?”
In other words, cycles reflect the lagged consequences of both prices and supply - how high or low prices today, combined with supply (abundant or scarce), set the stage for the next phase of the market.
To identify a cycle, statistics provide three must-know rules:
A cycle is not seasonal
It has no fixed calendar or predictable timing
It can last for years, not just months
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Since it’s not seasonal, nor predictable, predicting the inflection points of a coffee cycle is a “ninja-tier” skill for a coffee professional to have. Cycles are slow, noisy, and driven by lagged responses, so by the time the data clearly confirms a turn, prices might have already moved.
At the end of the day, this is why supply and demand matter so much in the coffee market, and why we, as coffee market researchers, build, update, and protect our S&D database so carefully (full access to our S&D balance sheets is available to our Silver and Gold clients only. Sign up here). The S&D is the framework that helps us understand where we are in the cycle and anticipate its inflection points.
The problem is that cycles take time, and to paraphrase Lord Keynes: prices can move against us far longer than we can remain solvent. This means that even if your cycle view is right, noise can dominate prices for long stretches and push the market against you before the cycle actually turns.
For that reason, a coffee professional also needs to be aware of the noise — short-term flows, positioning, macro shocks, weather headlines, and other random factors.
Noise: The Random Factor
Noise is random variation in data that does not carry systematic or predictive information about the underlying process. That’s the statistical definition, but... what does that actually mean?
Well, noise is like the tiny ripples on top of ocean waves. The big waves and the tide have a clear pattern and direction. But the small splashes and little surface movements caused by random gusts of wind don’t change the ocean’s overall motion. They just make it look messy.
In coffee, noise refers to unpredictable price movements that occur within a broader price trend or cycle. They are the short-term fluctuations that sit on top of the larger, meaningful forces driving the market.
The must-know rules to identify noise, according to statistics, are:
Noise has no pattern and it’s unpredictable (unlike a cycle, a trend or even seasonality)
It does not follow a trend, seasonality, or a cycle
It is often referred to as “random”
In practical terms, noise is not the event — it’s the price response that cannot be modeled in advance.
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Hailstorms in Brazil are good examples of noise in coffee markets. They tend to be high-impact at the micro level but usually low-impact at the macro level.
Because hail events are typically highly localized, they are unlikely on their own to materially reduce national production, and so any initial price impact tends to fade over time. Of course, there are exceptions: usually when such events are widespread in key regions, or recurrent.
Apart from hailstorms, some of the other classic candidates for noise verification are:
Unverified crop-damage anecdotes
Rumors of port congestion
Intraday currency swings
Algorithmic triggers on fund / speculative positions
Short-term index fund rebalancing
Single-day weather model flips (such as GFS vs. ECMWF disagreements)
Short-lived heatwaves or excess rain in key origins
Isolated frost scares (very common during the Brazilian winter)
Does this mean that the factors above are always noise?
Not necessarily, but it does mean that a good practice for coffee professionals is to verify them before assuming they are shifting the underlying market fundamentals.
A simple way to verify whether an event is noise or a fundamental change is to ask:
“Is this price movement caused by a predictable factor, or is it unpredictable and random?”
“If it is random, could it have a lasting impact on supply or demand that might eventually develop into a new trend, or is it truly transitory?”
Note that the fact that noise is random and unpredictable doesn’t mean it can’t have a lasting impact on prices. In most cases it doesn’t, but in specific situations we need to ask whether the effect might persist.
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In addition to persistence, another important qualifier for identifying noise is whether the sources are unverified. Unconfirmed information can often amplify short-term noise that doesn’t reflect the underlying fundamentals.
For example, the 2022 invasion of Ukraine was a major geopolitical shock, but for coffee, it was largely an exogenous noise, briefly pressuring prices through USD strength, without changing the underlying supply and demand balance.
In contrast, the July 2021 frost in Brazil was unpredictable to the most extent, but it significantly affected the crop, creating a lasting impact on S&D that contributed to drive a multi-year bullish trend alongside other factors such as drought. It fits the definition of noise because it was largely unpredictable, but its market expression was ultimately a bullish trend.
Since noise is random, staying skeptical and informed is ultimately the main way to protect against it. Noise is unpredictable, so the goal isn’t to forecast it, but to understand it as soon as it happens and react fast and appropriately. The key is therefore timing.
The primacy of timing is why our premium research subscribers receive daily reports with key highlights and analysis. This way our clients can quickly identify what’s driving the market, and are able to categorize noise vs substantive changes, and determine whether the impact on price will be temporary or lasting.
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Conclusions
Viewing coffee through a time-series lens helps organize price behavior across different horizons and avoid costly mistakes from misinterpretation of price action and daily events.
In your own trading and analysis, we recommend a simple daily exercise: when you hear news and rumors in the coffee market, make an effort to classify the information into buckets of noise vs price drivers.
Further refine those buckets with deepening questions: Does this new information reinforce or challenge the broader price trend? Are the original drivers of that trend starting to lose momentum?
Where does coffee currently sit within the larger cycle? Is this price swing capable of disrupting the larger trend or cycle, or is it merely temporary noise? At which point are we in the harvest calendar, and how is that likely to shape prices in the short-term horizon?
For a coffee market professional, framing these questions and categorizing factors within a time series is a valuable practice. It helps make sense of price action and approach it with greater objectivity, laying out the groundwork for more accurate price forecasting, one of the most essential skills a coffee professional can master.
We always advise clients to try this approach independently, however, if you would like assistance in this process or you simply want to observe how we do this process, we invite you to subscribe to a free trial of our Premium Coffee Research.
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