I always assumed these 15-minute crypto prediction markets worked in the obvious direction:

BTC moves on Binance → Kalshi reprices

Makes sense. Binance has the giant spot/perp market, and the prediction market is basically reacting to it.

But I came across some second-by-second data this week that makes this a lot more interesting.

The question was basically:

When Kalshi’s 15-minute BTC market moves, does BTC on Binance tend to move in the same direction immediately afterward?

Apparently, increasingly yes.

The correlation between a Kalshi move and Binance's move over the following ~2 seconds:

January: 0.036 June: 0.145 August: 0.173

So we're not talking about some magical 90% predictive signal here. 0.173 is still fairly weak on its own.

What caught my attention is that the relationship has increased almost 5x since January.

And if that's real, the interesting question is why.

One possibility is that the people trading these markets aren't just watching Binance and clicking YES/NO.

Market makers and automated traders can be looking at:

• multiple CEX order books
• perp positioning
• liquidations
• futures
• order-flow imbalance
• other proprietary signals

They form a short-term view of where BTC is about to go, then express that view in the prediction market.

Which creates a strange feedback loop:

traders anticipate BTC move → Kalshi reprices → BTC move appears on Binance

At that point Kalshi isn't just reacting to Bitcoin.

Its market price is effectively becoming a public signal produced by a bunch of competing short-term forecasting systems.

There are some obvious caveats.

Correlation doesn't prove Kalshi is causing or even independently predicting the move. Both markets could simply be reacting to the same information with slightly different latency.

And the test I really want to see is the opposite direction:

Binance move → Kalshi over the next 0–2 seconds

Then compare the two.

But if this lead keeps getting stronger as these markets get more liquid, that's a genuinely interesting development.

We might eventually reach a point where watching the prediction market becomes useful even if you have absolutely no intention of trading prediction markets.

Anyone here with access to proper tick data who can test the lead/lag in both directions?

Upfront, I run an analytics site for Polymarket, so this is my thing and the numbers come from our own index. Take that as you will.

Reason I built it. There are something like nine POLY allocation estimators live right now and most of them either want you to connect a wallet or quote you a token amount for a token that does not exist. There is also at least one page impersonating Polymarket with a check eligibility button that just drains you. So the bar was low.

What it actually does. You paste an address, nothing to connect and nothing to sign. It scores that wallet against the eight metrics that showed up most often across fifteen published airdrop formulas, Arbitrum, Optimism, dYdX, LayerZero, Jito, Jupiter, EigenLayer and so on. Weights are printed on the page. Farmer risk is a separate number instead of being folded into the score, so a big volume wallet cannot hide behind it.

The aggregate came out more interesting than I expected. Across 1,848,077 wallets with at least 10 fills and 100 dollars of notional, the median readiness score is 31 out of 100. Only 636 wallets score above 90. 87,186 carry farming shaped patterns, mostly entries clustered up near a dollar where there is almost no risk left.

What surprised me most is that raw volume is a weak signal historically. Across those fifteen formulas, adjusted volume appeared in 8 and was almost never linear, dYdX gave 30x the allocation for 1000x the volume. Distinct active days and capital held over time appeared nearly as often and were taken much more literally. Realised profit appeared in 2 out of 15.

Things it does not do, since I would rather say it than have someone find out. It cannot tell you your allocation, no criteria exist yet and Polymarket's own help page still says no airdrop has been announced. It does not check funding graph clustering because we do not index USDC transfers, and the page says NOT CHECKED there instead of showing a fake clean. And if you paste your MetaMask address it will probably show nothing, because Polymarket trades through a proxy wallet, you want the address from your Polymarket profile URL or just type your username.

Genuinely curious what people here think about the filtering question. LayerZero only qualified about 21% of wallets that had touched the protocol and Arbitrum around 27%. If Polymarket does something similar, most of that 1.85M never sees anything regardless of score. If you were the one designing it, what would you gate on?

So Kalshi isn't just prediction markets anymore.

Since end of May they're the first CFTC-regulated perpetual futures exchange in US history

They just dropped a live cost dashboard, and the numbers surprised me.

Crossing $100k of BTC:

• $37 on Kalshi
• $49 Hyperliquid
• $58 Binance
• $56 Bybit

source: https://compareperps.kalshi.com/

How is the regulated venue the cheap one? Pretty sure it's a market/land grab - they've been waiving fees for early users, and they raised $1B in May so they can subsidize this for years.

Worked too, $1B volume in the first week.

another interesting part is how mad the incumbents are: CME is literally suing the CFTC over the approval, and Kalshi just filed yesterday for perps on the S&P 500 and copper. Even BitMEX, who INVENTED the offshore perp, is shutting down in September.

Anyone here traded these yet vs Hyperliquid? Curious if the pricing holds once the promo era ends.

Hey all. I've been working on an arbitrage strategy for Polymarket's 5-minute crypto up/down markets and after the move to TWAP settlement earlier this month, I've been reevaluating what indicators are best to trigger trade signals within my bot. I wrote this artwork for the members over at Poly Research & Robotics and figured I would share it too incase it helps anymore.

Order-book imbalance is the indicator/signal that my arb bot fires on. We compute it from Binance's order-book depth feed and use it to decide when to open a position on the Polymarket contract, which is a detail worth stating up front because it turns out to matter more than anything else here.

To find out what the indicator is actually worth, we pulled a month of full-depth books, roughly 52,000 markets and 13 million seconds of order book. That tape is from April, which puts it squarely in the old settlement regime. For this particular indicator that matters less than you might expect, because order-book imbalance describes what the book is doing inside the cycle rather than how the market eventually resolves, and the mechanism behind it has nothing to do with settlement. Anything specific to the closing minute is a different story and should be treated with suspicion until somebody re-runs it on post-TWAP data.

The short answer on the indicator itself is that it gives you around 1-1.5 seconds of warning before the price moves on polymarket (it ranges quite a bit).

WHAT OBI IS:

Order-book imbalance is a single number describing how lopsided the order book is.

An order book is really just two queues: the people waiting to buy on one side, and the people waiting to sell on the other. OBI compares how big those two lines are. A book made up entirely of buyers reads +1, a book made up entirely of sellers reads -1, and a balanced book reads zero. It counts the shares waiting at each level and never looks at prices.

You can run the same calculation on any order book you can get depth for. Ours runs on Binance's book for the underlying coin, because that is where the size and the price discovery are. The alternative is to run it on Polymarket's own book for the contract you are trading, and the difference between those two choices is the single most important decision in this whole setup. More on that below.

Here is a real Polymarket book from the tape, taken from an ETH market on april 12:

bid  0.33   456.87 shares
ask  0.35     5.00 shares      OBI +0.80

There were 456 shares trying to get in against 5 shares willing to sell to them. One second later the offer had been cleared, the price had moved three and a half cents, and the imbalance itself had already halved.

That is the entire mechanism. An extreme reading is not a forecast in any deep sense; it is a statement that one side of the book is about to run out. Once the thin side gets cleared the price moves by construction, and the imbalance that predicted the move is consumed in the same instant.

This also explains a property that catches people out, which is that OBI is not a trend indicator. Measured against the price change at every offset around the reading, the correlation is negative at every point before it. The lopsided book appears after price has been pushing the other way, rather than before it. If you are using OBI to confirm a trend, you are using it backwards.

HOW MUCH WARNING YOU GET:

https://preview.redd.it/sxergiufw9kh1.png?width=2400&format=png&auto=webp&s=66843abcaaef90892718b5eaee49fd44d92b97cb

https://preview.redd.it/93y4p4dhw9kh1.png?width=2400&format=png&auto=webp&s=3e39a6721823554314068102eb48fe462f0e0c6a

Once the order book tips heavily to one side, how long is it before the price on Polymarket actually moves?

the short answer is that you get about two seconds of useful warning, and the whole effect is spent inside fifteen.

the clearest way to see it is to follow a single spike forward in time. Each figure below is the share of spikes that had produced a full one-cent price move by that point, either in the direction the imbalance was leaning or against it.

After 1 second, 36% of spikes have already produced a one-cent move in the predicted direction, against only 10% that have moved a cent the other way. This is the point at which the relationship between the imbalance and the price is at its strongest, and nothing that happens later is anywhere near as clean.

After 2 seconds, 44% have moved a cent in the predicted direction and 16% have moved against it. Starting from a randomly chosen second instead of a spike, the equivalent figure is 19%. Counting only the spikes that produce a move at all, the typical wait is two seconds, where from a random starting point the same wait runs to eight.

after 5 seconds, 56% have moved in the predicted direction and 29% have moved against it. This is the widest that gap ever becomes, and it narrows steadily from here.

After 7 seconds, the imbalance reading has decayed to half its original strength. The book you measured has largely been traded away by this point.

These measurements are obviously specific to this one moment that I'm featuring here for this article, but you get the idea. Many times the signal has decayed much quicker than 7 seconds. This example is an extreme imbalance.

HOW TO PUT IT IN YOUR BOT:

https://preview.redd.it/sumzd5a42akh1.png?width=2400&format=png&auto=webp&s=b7450b7392f4ec77808a9559537d6d2a4920a683

https://preview.redd.it/ujollt152akh1.png?width=2400&format=png&auto=webp&s=ef2b285f6e149000a8cd4f9e8334ee39d30fc565

The calculation is small. This is the version I run:

n = min(10, len(bids), len(asks))

bidW = sum(bid_size[i] * (n - i) for i in range(n))
askW = sum(ask_size[i] * (n - i) for i in range(n))

obi = (bidW - askW) / (bidW + askW)     # -1 to +1

Take the top ten levels of each side, weight them so the front of the queue counts heaviest, and then compare the two totals. Use the resting sizes only and never the prices they sit at. Every reading is computed fresh from a single snapshot, with no memory of the one before it.

The way you set up your config and what OBI values trigger different actions in your bot make a world of difference. Similar to any betting model, it's all about how you weight the data that makes the difference, not the data itself.

For me, I'm building an arbitrage trading bot on the polymarket up / down crypto markets, so I am using this signal to trigger a buy on one of the sides (mostly the dominant side for my opening trade of the pair) and then once the polymarket price catches up the OBI we observed on Binance, then we capture the other site for a share price that is within range for a profitable pair to be captured.

EXAMPLE:

1. Observe OBI +.8 (we see that way more people are trying to buy than sell...)
2. Bot purchases Up share at .60 a share (down is currently .40/.41)
3. OBI evens out, buyers get in, price moves up...
4. Down share price drops to .35, and we buy for a captured spread of 5% on the money we deployed into that pair.

now keep in mind, this isn't perfect and I'm still deep in development but I wanted to share this technique because it's been by far the most helpful and reliable indicator/signal for successfully capturing these pairs, and if you've build arbitrage bots before you know it's incredibly hard to main consistent pair accumliation.

If you're interested in polymarket trading bot development, and you're working on something similar...join us over at Poly Research & Robotics. We're a 1,500+ member free community dedicated to developing trading bots and strategies. We offer free guides, free trader reports, and polymarket historical data of many market categories that you can use to test out the above mentioned OBI (or use it to backtest any strategy you're working on).

If you have any tips or suggestions please leave them in the comments!

Strategy:

He enters markets where the price is still low - 3-20¢ per “Yes” - meaning the market is still uncertain about the outcome.

He doesn't wait for the weather forecast to be confirmed.

He goes in early, before most people have made up their minds.

The win rate with such a risky strategy is a full 49%.

When it goes the right way, it yields hundreds and thousands of percent in profit.

A small risk on trades that don't work out, and a huge payoff on those that do.

Top 3 deals:
$22 -> $322 (+1 357%)
$9 -> $102 (+1 098%)
$5 -> $83 (+1 483%)

He isn't the smartest trader. He just understands where the market rewards asymmetry.

His wallet: https://future.news/address/0xfd37c3c95979a46195ec5152439f820ca2d19135

Looking at Polymarket wallet Llalalala (ranked #129 in Politics), who just cashed out massive positions on Monday (including selling $238k on Putin staying in power at 92¢ and $80k on the Iranian government remaining intact at 93¢).

Across 21 months and 119 predictions, this account made $412,688 using one basic play: selling panic and buying status quo.

• This wallet systematically buys 80¢–90¢ "NO" contracts that bet the world looks the same in December.
• On the Iran contract alone, the wallet scaled up over 6 months, buying $1.5k at 50¢, $94k at 82¢, and $106k at 89¢, before closing the full $620k turnover position flat for an $11.8k profit at 93¢.
• The account's biggest loss ($93k) came from the one time it broke its own rule and bet on Iran's Supreme Leader being gone by March 31. It hasn't bet on a black swan since.

It’s a classic case of taking low APY yield in exchange for taking on massive tail-risk. Currently, the wallet has another $111k locked up in similar "status quo" bets for the end of the year.

⚠️ Disclaimer ⚠️

1. This is not a scam and requires no monetary investment, only time.

2. If I'm violating any rules, let me know and I'll take down the post.

With the admin's permission, I'll continue...

If you've heard of Polymarket and know how to navigate that system, you can earn some money with the OKX exchange. You just need to:

1. Sing-up here: https://okx.com/ul/XdnKmIV

2. Verify your account (KYC)

3. Find the event within the app and start betting with the points you earn.

I already participated in a Season 1 event about The World Cup. They gave out nearly $4,000,000 USD in prizes using the same method: you're assigned a certain number of points, you bet them, you climb the leaderboard, and at the end, you win a share of the prize.

In Season 2 there are 2 prizes:

1. The grand prize ($300k USDT).

2. Five weekly prizes ($60k USDT).

There are several markets to bet on:

1. Soccer (LaLiga, Premier League, and Liga 1)

2. NFL

3. Formula 1

4. Tennis

5. eSports (so far, only League of Legends).

How to earn points?:

1. By checking in daily

2. By placing a certain number of bets

3. By winning your bet (obviously).

The process is something like this:

You receive points > You place your bet > If you win, you collect your winnings > You move up the leaderboard > You claim your share of the prize at the end.

That's pretty much it. In Season 1 I made about $35, but that was because I got busted during the match England lost (never trust an Englishman, lol).

We'll see how it goes in this Season 2.

Good luck.

I run a small prediction markets research firm. Here's what three months of tracking Brier scores vs. Kalshi's implied probabilities actually looks like: wins & losses.

If you want free prediction markets research three times a week, top three calls with edge scores, I publish them on Substack: https://axiomforecastinggroup.substack.com/

• Total scored forecasts: 5
• Correct: 4
• Incorrect: 1
• AFG Brier: 0.111 vs Market Brier Score: 0.132
• Accuracy: 80%

With the upcoming rematch of the undefeated and 8th division world champ, the market currently weighs it as a 50/50 match.

Floyd has this unmatched defense and counter-attack techniques that could potentially just exhaust Pacman in a long fight.

On the other hand, the pound for pound on the early rounds can throw punches that equates to a shotgun.

What's your take on this one?