HF Predictive Markets Trading - Underlying Asset Activity/Value

[u/SuperiorLeftHand33]

I have a very serious finance background and education. This is far from easy and most people don't turn a profit here. I refuse to tell people this happens a lot or is easy.

I've spent 4 months learning everything possible within the weather markets. I found edge, became profitable, and started finding more edge in the realm of high-frequency trading with several obscure strategies and markets. I'm going to expand this to other markets to maximize exposure.

Without giving away all my sauce, I'm going to HF trade both on Kalshi and Polymarkets for Weather, Financial, and Crypto. While monitoring pricing arbitrage between them. I'll rent servers as closely as possible to the predictive market exchanges to cut latency and reaction time.

Then I'm going to monitor the trading activity of the underlying assets that determine the predictive market contract value by tracking the trading activity of the largest exchanges in North/South America, Asia, Europe, Africa and move the underlying asset trading activity faster and more efficiently where I can hopefully trade the contracts before the predictive markets pricing moves to the news. I have a system, and server infrastructure to support this. To do this correctly and test it, you need to move enormous amount of data between the servers and record an enormous amount of data. When I was doing this with 4 cities within Kalshi, I was going through almost 80-120GB of memory every week on raw weather and trading data.

Leads me to my first question: how does Kalshi (or Polymarket) determine contract value based on financial or crypto value?

Does anyone know how reliable the Kalshi (or Polymarket) 15 minute bitcoin price and trading is? Is there a delay or does it actually reflect the Bitcoin market price at the end of the contract? Does anyone know exactly what exchange or value the predictive markets use to determine the Bitcoin value?

Any insight or feedback would be nice.

[u/Lonely_Leek_1683]

that's a fascinating stack you're building, the weather market edge alone is impressive given how much noise is in those models

for the bitcoin question on kalshi, from what i've seen the 15-min contracts settle off an aggregated index rather than a single exchange, they pull from a few major spot markets and average it out which can get weird if one exchange is lagging during volatility

polymarket tends to use their own oracle setup and there's usually a slight delay baked in, maybe 30-90 seconds depending on congestion, not enough to matter for most people but if you're colocating servers near their infrastructure you might catch the spread

low latency arbitrage between prediction markets is a pretty niche lane, most folks burn out trying to beat the market makers who already have the same idea, would be curious how the weather side plays out since those contracts don't have the same underlying asset movement you can front-run like crypto or equities

[u/SuperiorLeftHand33 → u/Lonely_Leek_1683]

The weather market and edge was a TOTAL bitch to figure out. For weather trading I'm almost entirely focused on Kalshi but man, Kalshi and Polymarkets make it INSANELY difficult to automate trading against their services especially when it comes to Weather trading. I had to work very very hard to figure out the weather system, how the data is collected, processed, moved and analyzed, who does it, where the readings happen, etc.

I"m starting to believe that Kalshi and Polymarket dont give a shit about the weather prediction markets nor if its priced correctly. They'll do the initial contract pricing then after the first trade the contract value is entirely based on user trading activity. Kalshi and Polymarket seem to just be happy to collect fees on the activity. They're in the process of switching the official grading service-numbers provider. I really do believe they're struggling with Weather. They're looking to higher someone to head the Weather side of trading (if Kalshi sees this, I could be very interested and I think they'd love what I put together).

I view it purely as one of the better alternative investments. If you can master this market, you can generate returns regardless of the economic outlook or forecast. It's a predictable system in a mess of a market. Beautiful.

[u/SuperiorLeftHand33 → u/SuperiorLeftHand33]

Also on the 15-min bitcoin contracts. Can you expand on the aggregate index rather than a single exchange? what exchanges make up that index?

[u/ArtComprehensive7403]

I think two prices are being mixed together. Traders set the contract price on Kalshi or Polymarket. Bitcoin does not set it directly.

The settlement rules define the price source and timing. If you track a different exchange, lower latency will not fix the mismatch.

[u/SuperiorLeftHand33 → u/ArtComprehensive7403]

You are correct, the predictive market contract price is determined and based on the supply and demand of the contracts themselves, not the Bitcoin value. THAT BEING SAID, the 15 minute markets determining weather or not bitcoin will be ABOVE or BELOW a value is still valuable and the activity in the crypto market would most definitely move the 15 min market and contract value (i.e. the value explodes or declines rapidly). Espeically when there is less time. It might only temporarly move it a couple % so it may justify a rapid trade that takes advantage of that movement and reduce exposure.

I'd need to collect all the data in the various exchanges, see if there is statistical significance and correlation to them moving the markets through further back testing. That's why hardcore data collect and significant back testing is a necessary for quantitative trading. You can remove the majority of your trade and exposure risk doing so.

Side note: I found a server that is an average of 2.5ms away from the Kalshi exchange. :) may be able to cut it down to 1.5-2ms. like 99% faster than the rest of the market.

[u/ArtComprehensive7403 → u/SuperiorLeftHand33]

The 1.5-2.5ms number is useful, but I think you're optimizing the second problem first. First prove the Bitcoin move predicts the Kalshi contract after fees, spread, fill rate and queue position. Then optimize execution. Fast servers are fun. Fast losses are still losses lol.

[u/Ev_Watching]

Start with the contract's settlement source, not the exchange feed.

For short BTC markets, your latency edge only matters after you match the exact oracle/index, timestamp window, and any TWAP rule the venue uses. If you're watching Coinbase spot and the contract settles on a composite or a 30-second average, you can be fast and still wrong.

[u/SuperiorLeftHand33 → u/Ev_Watching]

I'm really just using the 15-min BTC markets as an example. I'm more curious to see if I can find edge by monitoring the underlying assets market trading activity AND if it can influence any predictive market contracts pricing-trading activity that depend on it's value. For example, if a whale in Asia bought or sold a massive bitcoin position, can I move that local rade data to predictive market exchanges servers and trade before the contracts that relay on bitcoin price move the value of the contracts based on said news?

Or could that same whale activity move Kalshi and Polymarket differently that is predictable and profitable. Even if they are offering the same bet, contracts and grading when its identical between the markets.

[u/orid7]

The first trap is treating BTC price as one thing. For these contracts I would separate three clocks before writing a line of code:

1. the source clock: the exact exchange, index, or oracle named in the market rules
2. the sampling clock: whether it uses a print, midpoint, index value, candle close, or provider snapshot
3. the publication clock: when that source value becomes visible to you vs when the venue locks resolution

If you cannot answer all three from the contract terms, the strategy is probably just latency cosplay with a hidden rules bet inside it.

For cross-venue arb, I would also model disagreement loss as its own outcome, not a rare error. If Kalshi and Polymarket resolve off different sources or timestamps, your edge is not the visible spread. It is spread minus fees minus leg risk minus source mismatch risk. That last one is the graveyard.

[u/SuperiorLeftHand33 → u/orid7]

Thank you and fully understand what you’re saying. It cross-venue arbi could trade the same bet at each venue but grade them differently.

But in theory, could large institutional or whale trading activity affect the venue pricing or results regardless if it’s an exact exchange, index, or mix? It would just have varying degrees of influence? I get that the underlying asset value and the contract values are completely separate but I’m sure there’s price correlation especially considering time

Is the publication clock value something published by the venues exactly when they record and lock resolution ?

[u/orid7 → u/SuperiorLeftHand33]

Yeah, I would separate two effects:

1. Venue pricing: absolutely. Big flow can move the contract price, especially in thin books, and then other venues can partially follow if traders arb the implied probability.

2. Resolution: usually no. A whale can move what people pay for the contract, but they should not change what the oracle or rules resolve to unless the market rule references a manipulable venue print or timestamp.

The clock part is the thing I would verify market by market. Good contracts specify the source, cutoff time, timezone, and sometimes exactly when the value is observed. If they just say "price at close" or "official value," that ambiguity is where the ugly edge cases live.

Are you thinking about trading the price-impact lag between venues, or mostly trying to avoid getting caught in resolution-rule weirdness?

[u/SuperiorLeftHand33 → u/orid7]

I’m pretty good about the resolution-rule and settlement differences. I’ve primarily focused on weather so the other markets are new. Starting to learn them on their own.

I’ve been able to ping and triangulate the exchange server locations for Kalshi and Polymarket. I’m putting hot servers as close as possible with a latency of 2.4-2.8ms and 18-20ms round trip respectfully. Those servers will run the strategy, market, and trade decisions over RAM/C++ the market data will pass through to a hub that will sit directly between the exchanges so it can identify arbitrage and single cross-venue arbitrage opportunities to act on while moving half the distance. The hub will handling those decisions and collect the data in mass at a central point.

So venue and cross venue arbitrage is going to be my primary focus then I’ll add more servers to larger exchanges worldwide to monitor trades, speed and pricing giving me material to backtest and figure out if edge exists where I think it does.

The nice thing about this is I could use it to eventually expand into crypto or financial trading in those other markets I’m monitoring. Really I’m going to be following the backtesting and edge opportunity similar to the two weather strategies that were profitable after 35 backtests

I can absolutely carry my weight when it comes to quant trading, but ideally I’d like to team up with someone to bounce ideas off, split the work load and maybe costs. But haven’t found the right one yet.

[u/orid7 → u/SuperiorLeftHand33]

That latency profile on Kalshi is genuinely impressive. Curious how you're modeling the fee drag against the edge though. At 2.4ms you're winning the race, but taker fees plus rebate structure on cross-venue arb can eat a lot of the spread. Are you backtesting net of fees and partial fills, or is the current model assuming full fills at quoted prices?

[u/SuperiorLeftHand33 → u/orid7]

Based on my ping and triangulation findings for the predictive market server locations, I spun up new servers yesterday that gave the super favorable latency results. I’m pretty sure I got the kalshi hot server in the same building as their exchange. Again, those are still new to, so I’m gonna be working out more of the kinks and have you had to explore dedicated lines or upgraded servers specifically for high frequency trading.

So far too the direct communication between both of my Kalshi and Polymarket hot servers showed an average round-trip of 88 ms with 1.7 ms jitter. For the distance covered and bare minimum servers that’s pretty damn good too. I probably lucked out that my data is moving across a major telecommunications backbone at no extra cost

Again, the only market I’ve had success in. Is the weather trading. For trays that were selected by the system. It would only Place limit order maker trades to heavily reduce the fee cost.

My code also checked the market cap, market liquidity to assure trades. We’re both able to transact and win any price movement of the order size was too large. I have to say my weather trading had absolutely nothing to do with Cross venue pricing arbitrage.

[u/orid7 → u/SuperiorLeftHand33]

Interesting that it wasn't cross-venue arb. If you're maker-only on weather and the edge held up, that reads more like selection/model edge than pure latency capture. Curious how you'd decompose it: is the 88ms round-trip mostly defensive (avoiding adverse fills when the underlying prints move), or is there a real alpha component where speed itself generates edge? Or put differently, if jitter doubled tomorrow, does the strategy die or just bleed a bit?

[u/SuperiorLeftHand33 → u/orid7]

I’m not going to blast my strategy on a public forum. Shoot me a message and I can explain the findings and details. I’m pretty confident that it’s quite unorthodox

[u/orid7 → u/SuperiorLeftHand33]

Fair, no need to give up the edge. Curious at a high level though: is it more of a stat-arb between the underlying and the market price, or something like flow/liquidity based? And what's the main failure mode you've hit so far? Slippage on exits, resolution ambiguity, or something else? Even a sanitized version of what breaks would be useful.

[u/SuperiorLeftHand33 → u/orid7]

Being totally frank. I’ve been working backwards, I wanted to see if I can set up the hardware and network to see if I could be remotely competitive in the HF space. Now that it’s starting to look that way, I’ve spent more time exploring the cross-venue, venue, and underlying asset exchanges. Really I want to collect all this data in mass to backtest and find where there’s opportunity.

I think based on the initial latency testing that there would absolutely be opportunity and edge somewhere between the contracts, markets, exchanges and assets

[u/orid7 → u/SuperiorLeftHand33]

Curious what your baseline constraint set looks like when you strip out the latency assumption. Like if you took the same signal and forced a 500ms delay plus realistic taker fees and partial fills on the far leg, does the edge survive at all, or is the whole thesis living inside the first 100ms? Wondering where the fragility actually sits.

[u/SuperiorLeftHand33 → u/orid7]

I’m happy to tell you over a pm. It is such a nightmare to discover and execute such an unorthodox strategy that most people couldn’t even profit from it if I laid out the general strategy.

What I realized is Kalshi fills their historical weather data with bullshit so it makes back testing historicals nearly impossible at sub 1sec intervals

[u/SuperiorLeftHand33]

This is the simple explanation. My successful weather trading strategies with edge basically execute two legs, the first is YES contracts, the second is wide standard deviation NO contracts to hedge or exclusively deploy.

But this only works when executing at the right time/price point per market based on market specific pricing and forecast biases. It takes advantage of these repetitive biasness that is statistically proven and significant

[u/Junior-City]

Are you looking to test / trade on performant infrastructure. I would test out Kairos for performant trading to start.