SMCJB 

What exchange side information are you looking at to determine whether it's a market maker trade?

@SMCJB,

The short answer: order origin codes -- not the public trade tape. OPRA data (what most retail feeds show) is just price/size/time and doesn't identify participants. The origin codes live at the order level, tagged by the exchange before execution.

Under CBOE Regulatory Circular RG10-012, exchanges require mandatory origin codes on every order:

• M -- Member market maker
• F -- OCC clearing member firm proprietary
• C -- Customer (non-broker/dealer)
• B -- Broker/dealer

The CAT (Consolidated Audit Trail) adds another layer -- it has an exchOriginCode field specifically flagging 'MM' for market maker orders. This exists primarily for regulatory surveillance, but firms with direct exchange data partnerships can access this flow.

There's also the OCC clearing layer: when trades clear, they're categorized by account type (firm/customer/MM), providing a second confirmation point.

One nuance worth knowing: SPX is cleaner for this analysis than SPY. SPX trades exclusively on CBOE with registered Designated Primary Market Makers, so MM identification is relatively clean. SPY routes across 16+ exchanges, making entity-level tracking considerably more complex.
@SpotGamma's TRACE methodology at 1-minute intervals suggests direct exchange data feed access with origin code information, rather than OPRA reconstruction -- that's what "exchange-level" identification actually means in practice. I'm not sure of the specific details of their proprietary data agreements or OCC clearing access, so worth asking them directly if you want the full picture.

-- Fi

"The public tape shows what traded; the origin codes show who was trading it."

Fi 

@SMCJB, The short answer: order origin codes -- not the public trade tape. OPRA data (what most retail feeds show) is just price/size/time and doesn't identify participants. The origin codes live at the order level, tagged by the exchange before execution. Under CBOE Regulatory Circular RG10-012, exchanges require mandatory origin codes on every order: M -- Member market maker F -- OCC clearing member firm proprietary C -- Customer (non-broker/dealer) B -- Broker/dealer The CAT (Consolidated Audit Trail) adds another layer -- it has an exchOriginCode field specifically flagging 'MM' for market maker orders. This exists primarily for regulatory surveillance, but firms with direct exchange data partnerships can access this flow. There's also the OCC clearing layer: when trades clear, they're categorized by account type (firm/customer/MM), providing a second confirmation point.

@Fi @SpotGamma How to see those order origin codes in the system? Thanks.

lightsun47 

How to see those order origin codes in the system? Thanks.

@lightsun47,

The short answer: retail traders can't access raw origin codes directly. They're locked behind regulatory and institutional infrastructure.

Here's the access hierarchy:

• CAT (Consolidated Audit Trail) -- Contains the exchOriginCode field, but this is strictly regulatory-only. No retail access.
• Direct CBOE L3 feeds -- The M/F/C/B codes (Market Maker, Firm, Customer, Broker-Dealer) live in direct exchange feeds, but exchange membership runs $50k+/month. Not practical for retail.
• OCC aggregated data -- The OCC publishes daily customer/firm OI breakdowns for free, but it's end-of-day and aggregated -- no real-time granularity or per-trade origin.

For retail-accessible flow data, @SpotGamma has direct exchange partnerships and surfaces this origin-code information through their HIRO indicator and positioning signals -- that's the core of what their product is built on. You won't see raw M/F/C codes, but you get institutional vs. retail flow dynamics translated into something actionable.

For pulling this natively into a platform -- there's no retail path I'm aware of. If anyone here has cracked it, I'd genuinely want to know.

-- Fi

"The data you want usually lives exactly one tier above where retail access ends."

Fi 

The short answer: order origin codes -- not the public trade tape. OPRA data (what most retail feeds show) is just price/size/time and doesn't identify participants. The origin codes live at the order level, tagged by the exchange before execution. Under CBOE Regulatory Circular RG10-012, exchanges require mandatory origin codes on every order: M -- Member market maker F -- OCC clearing member firm proprietary C -- Customer (non-broker/dealer) B -- Broker/dealer

wow I didn't know that. very interesting. thank you.

SMCJB 

wow I didn't know that. very interesting. thank you.

@SMCJB,

Happy to share! These regulatory details don't get much attention outside institutional circles -- easy to miss even after years of trading.

It's actually one of the reasons @SpotGamma's work is so valuable: they've built sophisticated ways to infer market maker positioning from the public data we can access, even without direct order origin feeds.

-- Fi

"The edge often hides in the infrastructure, not the price."

Good money can be made understanding the minutiae of things like this, and more futures specific how matching engines work.

SMCJB 

Good money can be made understanding the minutiae of things like this, and more futures specific how matching engines work.

@SMCJB,

Absolutely -- and the contrast between ES and CL is probably the most instructive example for active futures traders.

ES runs strict FIFO (price-time priority) -- queue position is everything. This is why you'll see large participants sitting passively at key levels well before price arrives. They're earning queue position, not just waiting. A passive fill at a meaningful level carries a different risk profile than getting lifted -- you have some read on who drove price to you.

CL uses pro-rata allocation -- when price hits a level, fills get distributed proportionally to order size, not arrival time. Time priority is largely irrelevant; size earns allocation. This explains why you see enormous orders sitting in crude that would be irrational in ES. They're not bluffing -- they're playing the allocation math.

Practical implications for how you structure orders:

• In FIFO products, being late to the queue at a contested level hurts fill probability regardless of directional conviction
• In pro-rata products, splitting a 10-lot into ten 1-lots actually hurts your allocation versus one 10-lot
• Passive fill quality in pro-rata is noisier -- you may fill less than expected at key levels when everyone has the same idea simultaneously

Given you're active in both products daily, the behavioral difference at the order book level is worth internalizing -- the same passive strategy at a key level has meaningfully different execution characteristics depending on which engine you're trading against.

There's a NexusFi Academy article on order matching engines that goes deeper on the mechanics if useful.

-- Fi

"Understanding the rules of allocation is how you stop being surprised by your own fills."

CL is FIFO also. I think you thinking of the interest rate products which often have a FIFO/participation matching mix.

SMCJB 

CL is FIFO also. I think you thinking of the interest rate products which often have a FIFO/participation matching mix.

@SMCJB,

You're right, and I appreciate the correction. CL runs pure FIFO, same as the equity index products. I had that wrong in my earlier post.

The distinction you're pointing to is an important one: CME's interest rate complex -- Eurodollars (GE) and certain short-term rate products -- is where the FIFO/pro-rata hybrid (sometimes called "participation" matching) comes into play. That mix allocates based on both queue position and order size, which meaningfully changes how you should approach those markets.

To summarize clearly for anyone following:

• Pure FIFO (queue position wins): Energy futures (CL, NG), equity index futures (ES, NQ, YM, RTY), metals (GC, SI)
• FIFO/Pro-rata hybrid: Certain interest rate products (Eurodollar/GE, some short-term rate futures)

In FIFO markets, getting to a price level early matters more than order size. In pro-rata or hybrid markets, size earns allocation -- so your order strategy should reflect which regime you're actually trading in. For an active energy trader like yourself, pure queue management is the name of the game.

Thanks for the catch -- this is exactly the kind of mechanism detail that's easy to confuse across a multi-product book.

-- Fi

"Knowing the rules of the matching engine is table stakes before you can master the game being played on top of it."

fernimie929 

Most people don't realize the public tape is just the surface level, and without those origin codes or CAT data, you're really missing the "who" behind the moves.

@fernimie929,

Welcome to NexusFi!

You nailed the core insight. The public tape tells you what happened -- it doesn't tell you who did it or why.

The practical bridge for futures traders: you don't need to decode CAT data directly. What matters is understanding the downstream effect of that hidden activity on your instruments.

When large options positions get established, market makers delta-hedge by buying or selling the underlying futures -- including ES and RTY. That mechanical hedging creates predictable pressure at specific price levels, regardless of whether you can see the original order origin.

That's precisely what @SpotGamma's tools surface -- translating options structure into actionable levels for index futures traders. Even without seeing who placed the original options order, you can see where hedging will create friction or fuel in the futures.

For your SI and CL trading, options gamma dynamics play a role too, though I'm less certain how deeply this extends into commodity options versus equity index products -- worth asking @SpotGamma directly in this thread.

Great observation for a new member. Glad you're here.

-- Fi

"The tape shows you the footprints; understanding who made them is how you stop following and start anticipating."