The question an entry desk wants answered is whether a contract that has just started attracting flow is early or already late. The trending tab looks like the instrument for it. Three time windows, six leaderboards, sixty rows, refreshed continuously. Capture that daily for a quarter and you have a panel, and from a panel you can fit a survival curve and read a half life off it.
You can. The number will be wrong in a specific direction, and the corrections that make it right are more useful than the curve itself, because they tell you what the board is actually measuring.
Board membership is a rank, not a level
Start with the instrument's definition. Each leaderboard holds exactly ten rows, and the tab reports sixty markets tracked across six boards. Membership is therefore relative and hard capped. A contract leaves the board when nine others beat it, which can happen while its own volume is flat or rising.
That has a direct consequence for the estimator. Every exit from the board is right-censored, not an observed death. You have not seen attention end, you have seen it fall below the tenth ranked alternative on a day when the alternatives happened to be strong. Treat exits as deaths and your half life will be biased short, and it will be biased short by an amount that varies with how busy the rest of the platform was, which means the bias is correlated with exactly the market conditions you would want the estimate to be robust across.
The correction is to record rank as well as membership, and to treat the leaderboard as a threshold-truncated observation of an underlying continuous quantity. If you can pull the volume figure alongside the row, which the board displays, you have the level as well as the rank for the top ten, and you can at least model the truncation rather than ignore it.
Deduplicate to events before anything else
The most damaging confound is visible in the capture without any statistics at all. On the Most Liquid board, every one of the ten rows is the same 2028 nominee question on the same venue, listed once per candidate. On the Most Cross-Listed board, the first three rows are one Toronto mayoral question and the next seven are one UK leadership question. On the volume board, rows seven, eight and nine are one Natus Vincere against Fnatic fixture sliced into two game winners and the series result.
Multi outcome markets therefore hold board slots by construction, and they hold them for as long as the parent event exists, which for a nominee market is years. Single outcome fixtures hold one slot for one afternoon. A tenure curve fitted on rows will show a long tail that is entirely an artefact of how two venues chose to enumerate their listings.
Collapse to an event key before fitting. Same underlying question, same resolution date, any venue, any leg, one observation. This single step will change the estimate more than every other correction combined, and it is also the step most likely to be skipped because the raw rows look like clean data.
Expiry is a competing risk and it dominates the naive curve
The second correction is the one that determines whether the number means anything. Contracts do not only leave the board because interest faded. Many leave because they no longer exist.
On the captured 24 hour volume board, nine of the ten rows were sports or esports fixtures with resolution inside roughly a day. Those contracts have a maximum possible board tenure set by their tenor, not by attention. They cannot appear on a 30 day board in the sense you care about, because they will have settled. Pool them with long dated policy contracts and the resulting half life is mostly a description of the tenor mix of the platform's listings, which changes with the sporting calendar.
Handle it as a competing risk rather than by filtering after the fact. Record, for every observation, the contract's end date and therefore its remaining tenor at first appearance. Then fit on the subpopulation whose remaining tenor exceeds your intended holding period, because that is the only population an entry timing rule can act on anyway. A separate curve for the same day fixture population is worth having, but it is a different question with a different answer and it should never be averaged with the first.
The three windows are nested, not independent
The third correction is definitional. The 24h, 7d and 30d boards are not three samples of the same process. A contract that qualifies on a 30 day window is by construction eligible on the shorter ones, and volume inside the 24 hour window is contained in the 7 day figure and again in the 30 day figure.
Treating the three boards as independent observations of persistence therefore triple counts the long dated contracts and inflates the tail. The useful framing is not persistence across windows but the ratio between them. For a given event, the 24h volume divided by the 7d volume tells you whether flow is accelerating or decaying, on a single day's snapshot, without needing a panel at all. A contract whose one day share of its own seven day volume is well above a seventh is having a moment. One well below a seventh had its moment earlier in the week.
That ratio is available from a single capture, it is immune to the rank truncation problem, and it is the closest thing on this page to a decay measurement that does not require you to fit anything.
What a half life can and cannot tell an entry desk
Assume you do the work properly. Deduplicated to events, conditioned on tenor, truncation modelled, ratios rather than nested memberships. You now have a defensible statement of the form that the median long dated contract entering the volume board remains in the top ten for some number of days.
Be clear about what that does not establish. It says nothing about returns. Board tenure is a measure of flow, and flow is not direction. A contract can hold the top of the volume board for a fortnight while its price does nothing, and the two most heavily traded contracts on the board can move in opposite directions. Any claim that entering early in the tenure distribution is profitable requires the price series, an execution assumption, and a cost model, none of which are on this page.
What the half life legitimately supports is a capacity and staleness rule. If the median tenure for your eligible population is short, then a research process with a multi day turnaround is systematically arriving after the flow, and either the process gets faster or it stops using attention as a trigger. If the median tenure is long, the board is telling you about durable interest rather than news, and the urgency implied by the word trending is misleading.
There is also a hard ceiling worth carrying into the same memo. The deepest book on the whole Most Liquid leaderboard was $4.7M, and the top of the 24 hour volume board was $4.1M. Even the contracts with the most attention on the platform support institutional participation measured in low hundreds of thousands at defensible participation rates. A precise half life on a strategy that cannot be sized is a well specified answer to a question that does not pay, and the sizing work should be done before the survival analysis rather than after it.