How to Become a Good Commodities Analyst

All right, this sub is kind of quiet and it's a shame. With almost 9,000 readers it also seems like about half of you all are "new to commodities" looking to get your feet wet. We should have more conversations like this one, but to get there we need more people who know their industry. This is the first entry of my guide entitled How to become a good commodities analyst. If it's well received I'll write a part deux.

I have about 10 years’ experience in agriculture, fertilizers, and a little bit in energy so this will largely view commodities through those lenses. Others with similar or different experiences chime in below in the comments, I’m happy to learn how your opinions or resources differ from mine.

Lets start with what I think is the most important skill and habit to develop. I believe the absolute best way to be good at your job as a commodities analyst is to hoard data, all of it, on your hard drive and in your brain.

The most frequently used data should be on your hard drive and it should be up-to-date. These are the models about which your boss will ask your opinions and reasoning. Supply and demand models, pricing models and databases, tangential models that inform your S&D models, stuff you're in at least monthly.

In your brain, you should hoard the location of infrequently used data. Knowing what data is available in the universe will allow you to answer questions from your boss like "how does sun spot activity affect La Niña severity and Brazilian soybean yield". Just knowing that a database of sunspot activity, La Niña severity, and Brazilian soybean yields exists somewhere will let you say, "I don't know, but I can let you know by 3pm". This differs from requests like "how many hopper rail cars does BNSF send through Kansas on average in May", only BNSF knows that one. If you hoard the location of enough data, you'll be able to answer more ad hoc questions and have opinions about increasingly nuanced drivers of supply and demand. Like, "how does ethanol profitability react to corn prices and what is the effect on grain elevator basis in northwest Iowa", I don't keep have a model to answer that question, but my boss knows I'm the first person they talk to if something weird like that comes up.

In terms of available data, there are three tiers of data: public, private, and proprietary.

Public Data Public data is exactly what it sounds like, it's provided directly by the government or has been legislated to be released to everyone for free (think public company quarterly reports). Public data is where most of the important commodity data comes from and it's extremely important to know the largest reports and have opinions on what the next report is going to say. Figure out what reports your boss or colleagues consider important, download the underlying historical data, know when it's released, and get comfortable with what drives each data series. For example, with corn the most important report is the WASDE report, released monthly, and the most important drivers are ending stocks, demand, price, and supply. If you're in the United States, one thing our federal government does really well is provide an absolute trove of data on commodities especially for the economy, demographics, agriculture, & fossil fuels. In general, most developed economies have good public data. I would also say Brazil and maybe Argentina have good agriculture data. Generally, the less independent the data departments are, the less you can trust the data (think China). I would argue that the U.S. and European Union are the gold standards for trust in public data.

For agriculture become comfortable navigating USDA.gov and all its department sites (NASS, FAS, AMS, etc.), learn how to perform custom queries at Quickstats, PSD Online, and all the local data from AMS Market News.

For energy, the EIA.gov website has a staggering amount of data on prices and demand. I'm only in here on an ad hoc basis, so someone else can chime in, but this page is a good place to start

Demographics the U.S. Census bureau is where I go for U.S. population by segment, and World Bank for global, but there are other sources.

Economic data you can get from the Bureau of Labor Statistics, trade data comes from the U.S. Census and International Trade Commission

For pricing data you usually need a subscription with a data aggregator, but often there are highly correlated public data series like this one. For commodities the Commitment of Traders Report is important to understand.

Private Data Private data costs money, sometimes a LOT of money. If your boss has P&L responsibilities, they won't flinch if you come to them with a subscription that costs $5,000 per year. What this means though is that these services need to make you better at your job commensurate with the subscription costs. Private data aggregation is highly competitive and very lucrative so there are large established firms (think Bloomberg, IHS Markit, etc.), medium firms (barchart.com), and startups (there are tons of weather and AI startups).

Even though it costs money, that doesn’t mean it’s bad. These companies earn their money for having better data, more data, or easier to format data than government sources. Get comfortable with your firm’s data subscriptions and use that data. If you see that your firm isn’t using a service TELL YOUR BOSS, you’ll look like a rockstar and cancelling an unused service will pay a good chunk of your salary. If your google searches or industry contacts suggest a new service, research it, reach out to the service and ask for a demo and if they give free trials. If the demo with just you or a peer goes great and you see yourself using the service regularly, get the subscription cost and go talk to your boss. If they don’t fall out of their chair hearing the number, schedule another demo with them. If your boss likes it, get the free trial (if available) and use the service for a week and show your boss what is useful. You’ll look like a rockstar.

Finally, if your company has a Bloomberg terminal, learn how to use it! Bloomberg (the man) is a mega-billionaire because he figured out that firms will pay a LOT of money for well formatted data. Bloomberg (the company) effectively takes poorly formatted public data and reformats and indexes it. If you can work a Bloomberg terminal, that should be your first stop for public data. They also are increasing the amount of private data they provide. It’s all in one place and it’s all formatted consistently. Bloomberg terminal fluency is a marketable skill and it should be in your resume/CV, LinkedIn, and mentioned in every interview.

Proprietary data This is the data that only your company has and is likely underutilized. This would most likely be sales data (shipments, pricing, forward sales commitments, etc.). Other proprietary data includes any databases you create by collecting your own data through web scraping, aggregating sales knowledge, etc. Do this, you’ll look amazing if your data is ever useful. I’ve had my own proprietary data used in anti-trust cases, to justify investment decisions, and understand competitor decision making. Having useful proprietary data is a great way to meet the C-Suite in your first couple years at a firm.

If you’re at a large firm you’re likely running some kind of SAP system. In my experience these are painful to learn and there are usually just a few people who know how to pull information out. Be that person. Use the system, be able to quickly pull sales data with multiple qualifiers and dimensions (July sale prices and volumes shipped to Montana sold in August). You’ll quickly be identified as a poweruser and your department VP will quickly know your name and come to you for data instead of sending in an IT ticket.

In conclusion, understanding where to find data is by far and away the most important skill to have as a commodities analyst. Hoard actual data on your PC, but also hoard knowledge of what data is available, where it is, and what it is. A $5.00/bushel corn price will mean something different if it is the near-by futures contract, the new-crop contract, cash prices paid by all Iowa farmers in June, or the price at an elevator in Minnesota last Friday.

Knowing whether relevant data is available, how fast you can access it, whether it’s trustworthy, and how fast you can analyze it to answer a question is 100 times more important than answering right away. But, for questions that come up frequently hoarding data and having it handy will give visitors an immediate answer and you’ll look like someone who knows your stuff.

edit: formatting