A Story from the GFC: How Macro Fits into Our Analysis

Soybeans, Human Errors, and why It Needs to be the "the Macro & the Micro"

I once asked a friend who worked at the Fed during the Great Financial Crisis (GFC): How did it get so out of control? Didn’t they see the housing bubble and system-wide leverage as a ticking time bomb?

His answer was more candid and nuanced than I expected, and it reinforced a key lesson: the institutions and people are human, prone to the same errors as the rest of us.

The difference is that our mistakes stay contained. In my opinion, there is little evidence that the business and debt cycles are safer than they were in 2020 or 2008. This is one reason why understanding both macro and micro dynamics is essential.

This framework allows you to know when to lean into risk and when to step back. It’s not about calling every turn—it’s about recognizing when the tide is going out before you're left swimming naked.

We end with a story from the GFC, the era when the tide was rushing out as soybeans made their all-time highs.

Top-Down (Macro) & Bottom-Up (Micro)

We approach commodity trading the same way most of us were taught economics: a mix of Econ 101 (Micro) and Econ 102 (Macro). Macro is the top-down view—how policy, money supply, and regulation shape markets. Micro focuses on price and quantity—the supply-and-demand mechanics. Remember your Ps and Qs.

Think of each category like building blocks. Models can be built top-down or bottom-up, and include one category of variables or all three.

1. Individual Commodity Fundamentals

2. Weather

3. Macro Drivers

Some agricultural firms argue that since they have no edge in macro, it's best to ignore it. That may have been valid in 1995, not in 2025. Today, there is too much money chasing across asset classes. Governments, agencies, and institutions make vast amounts of data publicly available. The edge comes from combining sector-specific expertise with publicly available data.

The first indications that consumers are willing to pay more for beef come from the macro data. If the economy is growing or inflation is rising, this has knock-on effects across the agricultural complex.

Here is a brief list of excellent public data resources:

• FRED Website

• Treasury Fiscal Data

• San Francisco Fed

• New York Fed

We’ll provide a more detailed list of macro resources and applications in a future note.

Trending vs Mean-Reverting

Our goal isn’t to predict if it’s going to rain—it’s to help you manage business and financial risks with data—distill numerous variables and data inputs into models that provide probabilistic outcomes, allowing you to make informed decisions with confidence.

2024 AiQ ECMWF model and corn futures normalized. The forecast threat sent prices shooting higher, and improved weather broke them.

So let’s begin by breaking down the big picture with a basic question: What kind of market regime are we in?

Start simple. Is the commodity trending? Does price have a function? Either ration demand and encourage production, or do the reverse? Are we in a weather market with asymmetric directional risk?

Last month, US corn carry-out corn bulls ran head-first into a benign start to summer weather in the Northern Hemisphere, increased South American production, and trade policy uncertainty. Even a crude oil spike provided little relief. It’s easy to see in hindsight, but the clues were there. AiQ’s recommendations have not included corn.

The second layer: Is the broader market trending or chopping around?
Is the commodity price driven by investment flows or just a result of chopping through headlines and noise?

We incorporate commodity-specific data to answer these questions for every commodity, properly accounting for factors like storability, substitutability, and market participation. All of which traders and owners intuitively understand, but lack the tools to quantify in real time. It’s a challenge of big data and math.

Simple calculations involve seasonal deviations and correlation breakdowns. The decomposition of statistical price drivers gives insights into where we are in the cycle. These same tools, at the micro level, can also be applied at the macro level.

Macro Trends Are a Function of Liquidity