Tokenized equities in a general scan of coins

Scanning the whole universe of contracts and sorting out the hits later does not work: tokenized equities flood any such scan, and as a trade they give nothing.

Why it sounded right

A wide scan is the right habit. The more instruments you watch, the more hits you get, and you cannot pre-select: the past carries poorly into the future, and attempts to pick the "good" coins by history usually turn out to be curve-fitting. Hence the natural conclusion: take everything in the contract list, search all of it the same way, and deal with a hit when it appears.

Tokenized equities look like just another kind of contract in all this. Same ticker format, same book, same funding, sitting in the same instrument list. If they produce an extreme, a breakout or a wide gap between venues — why not take them? On top of that they look even more predictable than coins: they have a real price outside, so there is somewhere for them to converge to.

And finally, filtering them out looks like a one-liner: a list of tickers, done. Somebody maintains such a list, you drop it into a filter and forget it. That illusion of simplicity is exactly what keeps the idea alive — it seems like the problem is solved, right up until half the hits in your scan turn out to be stocks under new names.

How we tested it

First we counted how many of them there are. In an ordinary sample from the breakout collector, the share of tokenized equities came out close to half — so this is not a trace impurity, it is the main content of the scan. Then we looked at why they float to the top of any ranking: outside stock market hours their price stands still and does not update, and at the open they all break loose together, in one flock. Any search for "what moved most in the last hour" lifts that entire flock to the top.

Then we tested them separately as a trade, on new contract launches. We compared three groups: fresh crypto contracts, tokenized equities, and long-traded coins getting a contract on a new venue for the first time. You cannot mix them: in one pile, one group's picture hides the other's. And we tested the ticker-list filter: how many names it lets through if nobody has looked at it for a couple of weeks.

How it ended

As a trade, tokenized equities give nothing. At launch there is no difference from zero on the first day, after a few days, or after a week — they simply repeat the real stock. This is not an event and not a move. Fresh crypto contracts in the same sample behave completely differently, and that is exactly why you cannot measure them together: in a mix, one group's effect cancels the other's.

As interference they are much worse than they looked. Beyond being numerous and moving as a flock, they also get counted twice: the plain ticker and the same ticker with a prefix are the same instrument, and ordinary duplicate protection does not see it. A ticker list does not solve this: new names get added every week, the list quietly goes stale, and you find out about it because your scan is full of stocks again.

What to do instead of a list. A structural check works where an inventory does not: if the same instrument list contains a paired ticker for the same stock, then it is a stock, not a coin. The marker comes from how the venue names its own instruments, so it needs no maintenance and does not go stale. It immediately catches names that were never on the list. The second trick comes from a different area but is the same in nature: when comparing venues, the marker for a same-name-different-thing instrument is that the gap between them never returns to zero. A real pair returns to zero; namesakes do not.

Where this could be wrong. Both checks are about how names are built and how the gap behaves, not about what the instrument actually is. A venue that names its tokenized equity differently will get past both of them, so you still need the list as a second layer.

What this teaches

• A wide scan is mandatory, but "take everything" is not the same as "do not filter." Instruments of a different nature have to be thrown out before the search, or they will take up the whole result.
• A blacklist of tickers always goes stale. Look for a structural marker, one that comes from how the venue names its own instruments.
• Check whether your hits have a paired ticker. One instrument under two names breaks both duplicate protection and any counting.
• Groups of instruments have to be measured separately. In one pile, one group's behaviour hides the other's, and both look like nothing.
• An instrument that freezes outside working hours and moves in lockstep at the open gets lifted to the top of any ranking by size of move. That is a property of the schedule, not a discovery.