The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Tarek Mansour no published score: only 1 usable exchange on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
1exchanges match
1on raw tape
0redirected or not addressed
Answered raw tape D 4 · C 4 · P 4 · Cm 3 3.85

Q to create liquidity. Cause like in the stock exchange, you don't have to incentivize high frequency trading firms to create, you know, sub second liquidity. They are very excited to take on that project themselves and build the high speed interconnect between New York and Chicago to accomplish and everything like that. And so is this just the stage that prediction markets are at or is there something fundamentally different?

A I think this is what I was talking about, which is that this idea that you need, so So maybe finishing that sort of line of thought, and then like, I'll get to the, to the answer there. You now have a model where you need liquidity to be built on the fly, much faster, much more dynamically, right? And, and the market makers, the traditional Wall Street market makers are not geared up for that. It's not like they can spin up a new desk to price like politics or price culture in, in an hour, right? And so, but this is the part that gets really interesting, which is like, and this goes back to the foundational principles around prediction markets is like, A lot of these markets, the people that will price them the best may not actually be the experts or the authority figures that you usually would think about. It's actually Random people, like, you know, that live.

AI assessment note: “market makers, the traditional Wall Street market makers are not geared up for that”

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