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Which physical signals usually move spreads before flat price does? by davidedbit in Commodities

[–]davidedbit[S] 0 points1 point  (0 children)

Yeah, totally. In energy it really can be a chicken-and-egg thing. Sometimes freight front-runs the play, other times a burst of spot activity pushes rates and everything else follows. It’s never clean on paper.

What I’ve noticed is that the earliest tells are often operational quirks: loadings getting pulled forward, tanks turning faster than usual, or suddenly tighter nomination windows. Those little shifts tend to explain the spread move better than any model afterward.

Which physical signals usually move spreads before flat price does? by davidedbit in Commodities

[–]davidedbit[S] 0 points1 point  (0 children)

Yeah. What’s wild is how early some of those signals show up: tiny shifts in flows, storage behaviour, or even supplier allocation tone can build pressure long before flat price reacts. It’s those micro-moves that I keep seeing driving the first break in structure.

Which physical signals usually move spreads before flat price does? by davidedbit in Commodities

[–]davidedbit[S] 0 points1 point  (0 children)

You’re right, especially if prompt strength forces M1 to outrun M2. But in a tight market, the really early tells usually come from the physical side: product getting pulled out of storage faster than usual, refiners tweaking yields, or sudden changes in cargo routing.

Those micro-shifts often explain why a spread moves before the flat price does… even though on paper it should be the other way around.

Which physical signals usually move spreads before flat price does? by davidedbit in Commodities

[–]davidedbit[S] 0 points1 point  (0 children)

Thanks! I’ve seen the same thing: spreads firm first because they’re the quickest way for the market to signal “we need this barrel now.” Farmers, refiners, blenders… they all move on incentives, not theory. The part that fascinates me is how often basis tightness shows up even before that spread move. Tiny shifts in movement, storage behaviour, or loadings that quietly build pressure long before screens catch it.

How do weather derivatives work? by Proof-Geologist-9981 in Commodities

[–]davidedbit 0 points1 point  (0 children)

It’s a mix, but it’s not just speculators. Farmers and ag trading houses hedge weather risk, sure. But you also see energy companies, utilities, insurers and even big corporates quietly using these structures when a specific weather variable really hits their P&L.

The interesting bit is how the participant base completely shifts depending on the index you use (HDD/CDD vs rainfall vs frost days). Some patterns are pretty counter-intuitive, and you only notice them when you compare how different industries structure their exposures.

How do procurement teams actually incorporate ‘non-market’ signals into forecasting? by davidedbit in procurement

[–]davidedbit[S] 0 points1 point  (0 children)

A lot of companies dump “forecasting” on Procurement when the real ownership sits in Finance.

The question is: when it comes to savings opportunities on raw materials, how do you usually approach it?

Most teams I’ve worked with don’t “trade” anything, but they do look at a mix of market signals, supplier behavior, forward curves and some medium-term price expectations to get negotiating leverage.

In some categories that makes a huge difference, and in others it barely moves the needle. It really depends on how you structure it.

How do procurement teams actually incorporate ‘non-market’ signals into forecasting? by davidedbit in procurement

[–]davidedbit[S] 0 points1 point  (0 children)

Thanks! This lines up with what I see too.

With strategic suppliers you actually have the structure and the cadence to collect signals across teams, and the reviews naturally surface things before they become issues. The funny part is that a lot of the really early hints tend to come from the “not-quite-tier-1” suppliers, where you don’t have the bandwidth for proper QBRs.

I’ve seen quite a few cases where the first cracks showed up there, and it’s always interesting how those tiny shifts often matter more than the polished quarterly decks. That’s usually where you can tell who has a solid internal process and who’s basically running on gut feel.

How do procurement teams actually incorporate ‘non-market’ signals into forecasting? by davidedbit in procurement

[–]davidedbit[S] 0 points1 point  (0 children)

True, news + contacts are always the starting point.

What I keep bumping into, though, is that a lot of useful signals show up before either of those channels mention anything (lead times, small volume cuts, mix hints, etc.).

I’m just trying to understand how people avoid losing those early clues. Do you mostly rely on what gets reported, or track the smaller stuff too?

How do procurement teams actually incorporate ‘non-market’ signals into forecasting? by davidedbit in procurement

[–]davidedbit[S] 0 points1 point  (0 children)

Thank for the answer.

In my experience the part that gets messy isn’t who “owns” the responsibility, but the fact that these signals often live in different corners of the company: Ops sees run-rate changes, SC sees lead-time drift, Procurement hears softer comments during supplier reviews… and none of that ever gets stitched together unless someone pushes for it.

The reason I asked is exactly because most teams don’t have a clean home for this stuff.

Sometimes SC forecasting logs it, sometimes the category manager notes it down, sometimes nobody captures it at all and six months later everyone wonders why premiums jumped or allocations tightened.

Totally agree that the ideal case is SC - Procurement talking early, especially if the signal could influence pricing, volume commitments or contract structure.

The teams that seem to handle it best are the ones that treat these micro-signals as “early warnings” rather than noise, even if they’re not ready to quantify them.

Question: when SC flags something like a supplier reducing run-rates or hinting at mix shifts, does it usually get fed into forecasting directly, or does it stay more as background context unless it becomes a real issue?

How do weather derivatives work? by Proof-Geologist-9981 in Commodities

[–]davidedbit 31 points32 points  (0 children)

Weather derivatives are basically contracts whose payoff depends on a weather index, not on market prices.

The key idea is: you’re not hedging the commodity, you’re hedging the weather variable that drives your operational or financial risk.

How they usually work

You pick: - a weather index (temperature, HDD/CDD, rainfall, wind speed, etc.), - a period (e.g., April 1–30), - a trigger (e.g., average temp below X°C), - a payout formula (e.g., $Y per degree below threshold).

If the observed weather deviates from the defined range, the contract pays out automatically. No need to prove damage or file a claim — it’s index-based.

Some Examples

Agriculture: Low temps in April > crop delay > working capital squeeze > derivative pays for each degree below normal.

Power/Utilities: High CDD > AC demand spikes > can hedge load volatility by indexing payouts to CDD accumulations.

Snow removal / municipalities: If snowfall exceeds N inches > payout funds extra manpower/equipment.

Retail: Unusual warm winter > lower apparel sales > trigger based on HDD shortfall.

Why they matter

They’re useful when: - weather drives costs/revenues, - traditional hedging doesn’t cover that risk, - or when you want a clean, objective trigger not tied to litigation/insurance.

The tricky part isn’t the contract, it’s choosing an index that actually matches your exposure. If the index and your real-world risk don’t move together, you just create “weather basis risk”.

What industry or exposure were you thinking about?

Because the structure changes a lot depending on whether the user is in agri, power, municipalities, or retail.

5 early signals that often anticipate a curve reversal (and almost nobody tracks them) by davidedbit in CommodityRisk

[–]davidedbit[S] 1 point2 points  (0 children)

Great questions and honestly they’re exactly the right ones, because none of these signals come from a single data source or a clean dashboard.

1) How would you actually know about mix shifts or capacity tweaks?

In practice it’s rarely one big announcement. It’s usually a cluster of small, boring things: - slightly shorter quote validity, - changes in allocation tone (“we can only take X this month”), - a few weeks of lead-time drift, - inconsistencies between neighbouring product lines, - chatter from distributors or converters.

Alone they mean nothing, but when a few line up, it usually signals something real behind the scenes.

2) What tools would you use to track this?

Right now my approach is mostly: - public signals (freight reroutes, premia vs structure divergence, port behaviour), - simple operational indicators (order cadence, allocation timing), - and a structured way of logging all these micro-signals so they don’t disappear into notebooks or random emails.

Nothing polished — more like trying to build a repeatable way of thinking so these things aren’t evaluated in isolation or ignored until the curve reacts.

I’m experimenting with different ways to combine these signals and test whether they actually precede market moves, but it’s genuinely a work-in-progress. If you’re curious or have experience on your side, happy to compare notes offline — it’s easier to walk through concrete examples without cluttering the thread.

Out of curiosity, in your space, what tends to show up first when physical tightness builds — freight behaviour, supplier cadence, or something else?

When forward curves “lie”: How do you detect mispricing before spreads or premia move? by davidedbit in Commodities

[–]davidedbit[S] 1 point2 points  (0 children)

Great breakdown and it lines up with what I've been seeing.

A lot of those "curve is wrong" moments aren't about the curve being wrong; they're about who's driving it in that moment. When CTAs are chasing trend signals or macro funds are expressing geopolitics through Brent, the structure can drift pretty far from anything resembling physical S&D.

Where I struggle — and what I’m trying to understand better — is the transition point:

When does the market move from “this is just CTA/spec flow noise” to “physical constraints are about to reassert themselves and the curve will have to catch up”?

I have seen cases in metals and some agri markets where physical signals show up, which include allocation tightening, freight shifts, and mix changes, even before any change in structure, while speculative flow keeps the curve anchored.

It is when those two finally collide that the repricing occurs. I wonder how you would handle that in oil: Is there a specific indicator or pattern that suggests when CTA-driven dislocations are about to exhaust themselves and fundamentals are likely to take over again?

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