A working framework for money, credit and markets

Everyone uses money every day. Most people can tell you what it does — it pays for things, it measures value, it stores wealth across time. Ask them what it actually is, and the answer gets complicated surprisingly quickly.

This isn't ignorance. It's the result of an education system and a financial industry that both teach people to use money without teaching them to understand it. The distinction matters because if you don't understand what money is, you can't fully understand what a price means — and if you can't read prices clearly, you are operating with a significant and largely invisible disadvantage.

Money is a measuring tool that changes its own length

The clearest way to understand money is as a unit of measurement. It measures the value of things relative to each other — an hour of labour against a loaf of bread, a company's annual earnings against its market price, a government's debt against its ability to repay. This is money's primary function as a unit of account, and it's the function most relevant to investors.

The problem is that unlike other units of measurement — a metre, a kilogram, a second — money is elastic. The unit itself changes. A pound in 1990 measured something different from a pound in 2000, and something different again today. This is not merely a philosophical observation. It has direct, practical consequences for every investment decision.

Consider what it means when a house price rises. There are two possibilities: the house has become more valuable, or the unit of measurement has shrunk. Usually it's some of both. But the investor who doesn't ask the question — who treats the nominal price as though it's denominated in a fixed unit — is reading only half the information available to them.

This is the real/nominal distinction, and it is one of the most practically important concepts in investing. The nominal return is what the number says. The real return is what's left after accounting for the changing value of the unit. An investment that returns eight percent in a year when inflation runs at six percent has delivered a real return of roughly two percent. An investment that appears to hold its value in nominal terms while inflation runs at ten percent has lost a tenth of its real purchasing power. The number flatters. The unit deceives.

How money becomes more or less elastic

Money doesn't change its value randomly. The primary mechanism is credit — the expansion and contraction of the total supply of money in the system.

When credit expands — when banks lend more freely, when central banks suppress interest rates, when governments run large deficits — the amount of money in circulation grows. More units chasing the same pool of assets means each unit buys less. The measuring rod shrinks. Prices rise, not necessarily because assets are worth more in any fundamental sense, but because the denominator has changed.

When credit contracts — when lending tightens, when rates rise, when debt is repaid or defaulted on — the reverse occurs. Fewer units, same pool of assets. Prices fall. The measuring rod extends.

This is the connection between monetary conditions and asset prices that most commentary treats as mysterious or unpredictable. It isn't. The relationship is mechanical. Not precise in its timing, but consistent in its direction. The investor who understands it reads rising asset prices during credit expansions differently from rising asset prices during credit contractions — because the information content is different.

Where the elasticity flows

One of the phrases that most neatly conceals this complexity is "inflation-adjusted." It sounds like a correction — implying a uniform process, prices rising steadily over time, which a simple adjustment at the end sets right. It relegates inflation to the long run. Something that happens gradually, in the background, eventually accounted for.

This understates what is actually happening. Inflation is cumulative — which matters — but more importantly it is unequal and immediate. The elastic unit doesn't stretch uniformly across the economy. Sometimes the elasticity flows into asset prices — equities, property, financial instruments — while consumer prices remain largely stable. Sometimes it flows into commodities and consumer goods while asset markets are subdued. Sometimes both happen simultaneously. And markets themselves are inconsistent in how they respond: sometimes inflation is the only thing they can see, pricing it into every decision; sometimes they ignore it almost entirely, treating it as a long-run abstraction while it quietly erodes real returns in the present.

The decade following the 2008 financial crisis is the clearest recent example. Consumer prices rose slowly. Central banks congratulated themselves on price stability. At the same time, asset prices inflated dramatically — equities, property, bonds — a period of significant monetary expansion that the standard measure simply wasn't looking for. The investor who read the headline figure and concluded that inflation wasn't a factor missed one of the dominant dynamics of the period.

The investor's question, therefore, is not just is money elastic right now? but where is the elasticity going? The answer changes what you should hold, how you should read apparent price stability, and what any single inflation measure actually tells you.

The practical implication

Every price you look at has two components: what the asset is doing and what the unit of measurement is doing. Separating these is not a technical exercise requiring specialised tools. It requires the habit of asking a simple question: is this price change telling me something about the asset, or something about the money?

In practice, it is usually telling you about both simultaneously. The investor who has absorbed this — who automatically asks both questions when they see a price move — has a genuine analytical advantage over the one who takes the nominal figure at face value.

The credit cycle, which we examine in Section 2, is the mechanism through which changes in the elasticity of money play out across markets over time. Understanding what money is makes that mechanism legible. Without this section, Section 2 is a description of patterns. With it, it's an explanation of causes.

Section 1 established that money is elastic and credit is the primary mechanism of that elasticity. This section shows what happens when that mechanism operates across an economy over time.

The answer is cycles. Not random fluctuations, not unpredictable events, but recurring patterns of expansion and contraction that have been observable for as long as credit has existed. The specific trigger changes — tulip bulbs, railway shares, mortgage-backed securities — but the mechanism underneath is consistent. Understanding it doesn't give you the ability to predict timing. It gives you the ability to read the condition of the system at any given moment. That is far more useful.

The Minsky framework

Hyman Minsky was an economist who spent most of his career being largely ignored, then became briefly famous when the 2008 financial crisis validated his life's work with terrible precision.

His central observation was simple: stability breeds instability. Periods of economic calm encourage risk-taking. Risk-taking, collectively and over time, creates fragility. The fragility eventually produces the instability that calm had obscured.

He described the progression in three stages, defined by the relationship between borrowers and their debt.

The critical point is that economies — and markets — tend to move through these stages progressively during a credit expansion. What begins as prudent lending gradually becomes speculative, then Ponzi, without any single actor intending the outcome. The system drifts toward fragility because each individual decision seems reasonable in the context of prevailing conditions. This is what makes it so persistent. The people inside it are not foolish. They are rational, given what they can see at the time.

The self-reinforcing loop

Credit expansion is self-reinforcing in both directions, and this is what gives cycles their characteristic shape.

During expansion: rising asset prices increase the value of collateral, which supports more lending, which funds more asset purchases, which raises prices further. Each step validates the previous one. Optimism is rewarded. Risk-taking looks like skill. The cycle feeds itself.

During contraction: falling asset prices reduce collateral values, which tightens lending conditions, which reduces demand for assets, which depresses prices further. The same mechanism that amplified the rise amplifies the fall. The Minsky moment — the point at which forced selling begins and the self-reinforcing loop runs in reverse — is rarely visible until it has already arrived. By the time it is obvious, the most expensive decisions have usually already been made.

The emotional architecture

The cycle is not merely a mechanical process. It is driven by human behaviour — by fear and greed operating at individual level, now running collectively at market scale.

Early in the cycle, when assets are cheap and sentiment is negative, the rational action is to buy. It feels irrational because the narrative is uniformly bearish and the recent experience is of losses. Late in the cycle, when assets are expensive and sentiment is euphoric, the rational action is to reduce exposure. It feels irrational because the narrative is uniformly bullish and the recent experience is of gains.

This inversion — where the rational action consistently feels irrational and the irrational action consistently feels rational — is why the cycle persists across generations of investors who have studied it. Intellectual understanding of the mechanism does not neutralise the emotional pull. The fear of missing a rising market and the fear of holding through a falling one operate below the level of conscious reasoning. This is not a character flaw. It is the architecture.

What this means in practice

Understanding the credit cycle does not provide a timing tool. Nobody knows when the Minsky moment will arrive. What it provides is a reading of embedded risk — a sense of where in the cycle the system currently sits and what that implies about the risk and reward of different positions.

A market in late Ponzi-finance territory carries substantial embedded risk regardless of whether the trigger has appeared. A market emerging from forced contraction, with credit conditions still tight and sentiment deeply negative, carries far less embedded risk — often independently of what prices are doing in the short term.

The investor who can read cycle position — not predict it, read it — makes materially different decisions from the one who treats each market moment as independent of what preceded it.

Section 3 builds a working model from these components. The model doesn't require precise cycle identification. It requires enough pattern recognition to avoid the most expensive mistakes — the ones made by investors who act as though the cycle doesn't apply to them.

Sections 1 and 2 established two things. First: money is a measuring tool that changes its own length, with credit as the primary mechanism of that change. Second: credit expansion and contraction, operating through human behaviour over time, produces cycles — identifiable phases with consistent emotional and structural characteristics.

This section shows how to assemble those components into something usable — a framework for reading market conditions that any investor can apply, regardless of experience, strategy or asset focus.

Before describing what the model is, it is worth being clear about what it isn't.

What a working model is not

A working model of markets is not a forecasting system. It does not tell you when the cycle will turn, what the Minsky moment will be triggered by, or what any asset will do next quarter. Anyone offering that is selling something the evidence doesn't support.

It is also not a trading system — a set of entry and exit signals, a mechanical set of conditions that determines what to buy and sell. Those systems exist in abundance and share a common weakness: they are calibrated to conditions that have already occurred.

What a working model provides is orientation. A read of the environment. An understanding of the forces currently operating and the embedded risk they imply. The investor with a working model makes decisions in context. The investor without one makes decisions in isolation — treating each market moment as independent of everything that preceded it.

The three questions

The model consists of three questions, derived directly from Sections 1 and 2. They are not asked once. They are asked regularly — monthly at minimum, more frequently when conditions are moving quickly.

How to use the model

The three questions don't require hours of research or access to proprietary data. They require honest observation and a willingness to reach conclusions that may be uncomfortable.

The practical discipline is to answer them briefly, in writing, at regular intervals — and then to compare each answer to the previous one. The direction of change is often more informative than the current reading. Credit conditions moving from loose to tighter, even modestly, carries different implications than conditions that are tight but stable. Sentiment shifting from optimism to complacency carries different implications than sentiment that is already fully euphoric. The model reads movement as much as it reads position.

Investors who apply this consistently report the same experience: it doesn't tell them what to do. It tells them what they're doing in context. That context changes decisions at the margin — position sizes, entry points, the patience to wait for better conditions — in ways that compound meaningfully over time.

What good looks like

The investor who has absorbed this model doesn't make confident market predictions. They maintain an ongoing orientation to the environment. They know roughly where the cycle is and what that implies about embedded risk. They notice when the elasticity of money changes direction. They read price movements in the context of the unit those prices are denominated in.

And when conditions deteriorate — as they reliably will — they are not surprised by the direction, even if they couldn't have specified the timing or the trigger.

That is not a guarantee of good outcomes. It is the foundation that makes good outcomes more likely and catastrophic ones less likely. Which, over a full market cycle, is most of the job.

The three sections that precede this one have covered significant ground. What money is. How credit creates cycles. How to read the environment those cycles produce. This section addresses the question that follows from all of it: what does this actually change?

The honest answer is: it changes what you look at and how you interpret what you see. It doesn't change the fundamental uncertainty of markets. It doesn't replace analysis of individual assets, businesses or instruments. What it provides is the environmental layer — the context within which any specific investment decision is made.

The perspective shift

The most immediate practical effect of absorbing this framework is a change in the questions asked before any significant decision.

The investor without it asks: is this a good investment? Is the price right? Does the analysis support it?

The investor with it asks those same questions — and then asks: is this the right environment for this kind of investment? Where in the credit cycle are we? Is the embedded risk in current conditions consistent with the position I'm considering? What does the elasticity of money right now mean for how I should read this price?

These are not more complex questions. They are more complete ones. The analysis of an individual investment and the reading of the environment it exists in are separate exercises, and both are necessary. Conflating them — treating a good investment as automatically appropriate regardless of conditions — is one of the most consistent sources of avoidable losses.

The mistakes this prevents

Every significant investment error has a context. Most share a common feature: the investor acted as though current conditions were permanent.

The investor who bought technology stocks in late 1999 at multiples that only made sense if growth would continue indefinitely acted as though the conditions of the expansion were permanent. The investor who sold everything in March 2020 acted as though the conditions of the contraction were permanent. The investor who held through the 2008 credit contraction without understanding what was driving it — treating it as a temporary blip in a durable uptrend — acted as though the conditions that preceded it were permanent.

Understanding the credit cycle makes it harder to act as though any condition is permanent. The mechanism that produces expansions also produces the seeds of their end. The mechanism that produces contractions also produces the conditions for recovery. This knowledge doesn't tell you when the transition will come. It reminds you, consistently, that it will — and that acting as though it won't is one of the most expensive assumptions an investor can make.

What the framework can't do

It would be dishonest to overstate what four sections of foundational thinking can deliver.

The framework does not provide timing. It does not tell you which assets to hold, in what quantity, or at what price. It does not resolve the specific decisions that come with managing a real portfolio under real conditions.

More importantly: it does not eliminate the psychological pressures that cause intelligent investors to act against their own best judgement. The framework described here is intellectual. The decisions made in real markets, with real money, under real pressure, engage a different part of the human architecture. Understanding the credit cycle conceptually does not immunise you from acting irrationally when you are personally positioned in the wrong part of it.

This is the gap that the full course — First Principles: Developing Your Money Mind — addresses directly. Not just the framework for reading markets, but the disciplines for managing your own decision-making when the two are working against each other. The working model you now have is the foundation. What's built on it is the work of the course.

The closing thought

The investors who perform consistently over time are not the ones with the most sophisticated models or the most proprietary information. They are the ones who understand the environment they are operating in, maintain an honest orientation to it, and make decisions in context rather than in isolation.

That understanding begins with knowing what money is, how credit drives the system that money flows through, and how to read the conditions that system produces.

You now have that. What you do with it is the next question.