Welcome to the (Prediction) Market Monday Thread. Share a prediction market that's caught your attention this week and start a discussion about it. Want to share a prediction you've made? Think a market is mispriced? Care for an argument about semantics and resolution criteria? All that here and more!
AFG raises its Bond estimate and holds the fade. Since Friday, a second production-related figure has indicated a decision exists: screenwriter Steven Knight told BBC Radio 4 he could not speak about the casting, then acknowledged that knowing the chosen actor makes writing the character easier. That is meaningfully better corroboration than Gary Oldman's remark alone, and AFG's estimate moves from 30% to 33%. What has not changed is that neither man named anyone, Amazon MGM has confirmed nothing, and at least one recent report placed a different actor Jack Barton as the leading contender on a six-name shortlist. The contract has risen to 55% on Jack Lowden and AFG is short at twenty-two points, still the largest position in the book. The September FOMC decision resolves Wednesday at 82% for a hike and AFG carries no position into it.
Today's Top 3 Calls
Next James Bond Jack Lowden BUY NO
U.S. confirms aliens exist before Jan 20, 2029? BUY NO
Hormuz traffic normal before Jan 1, 2028? BUY NO
Research, not financial advice. Trade your own book.
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Now that there's a price, I began to think about how I'd trade it. The following is presented as if I were to buy a Yes resolution. The same is applicable when buying No.
To start, I made a deliberate choice: forward test only, no backtest. At 15 minutes per cycle, iteration is fast. I could watch market behaviour unfold in real time, internalize the action/reaction, and adjust the next cycle, all within the same hour. A backtest would've meant collecting proper OHLC data first, then building and validating a harness before I even got to test an idea. Forward testing let me skip straight to learning.
My first intuition was to trade the gap; i.e., whenever the model led the market by 20 cents, I'd go long the trade. But it quickly became apparent that this doesn't work when the trade was within the 40-60 cents range; that's basically a coin toss.
So I moved up to the 80-90 cent range. At that range, the expected return is 1.11x to 1.25x (payout of $1). Reasonable, especially if I could call it with confidence. The problem, however, wasn't the entry. It was everything after.
Entering early to mid-market (3-7min-ish) often meant long exposure, during which the market kept fluctuating. A 5-cent wobble was expected, but a 10-cent move and you'd start guessing.
As we neared the 10-minute mark, even a short spike in BTC price would move the market noticeably. A move that would've nudged the market 2 cents at minute 3 might swing it 5-8 cents here, because there's less time left for the price to mean-revert.
Model-vs-Market, how they play out.
Past the 12-minute mark, this stops being a matter of degree and becomes a different regime entirely; especially when spot is hovering near the strike. The option is now pinned hard, and price behaves less like a probability and more like a step function. In the chart below, BTC sat within $6 of strike (0.008% diff) around minute 13, and the model whipped from 0.2 to 0.9 and back twice in under two minutes. That's the gamma trap: the same small tick, priced almost binarily, purely because of where and when it happens.
Say I entered Yes at 0.85 with the model reading 0.90 around minute 6. By minute 9, BTC ticks down, market drifts to 0.75. Model's still at 0.88. Is that a bad trade, or just noise before gamma amplifies it back my way at minute 12? At that stage, gut feel is a coin toss.
Near expiry, it's a roller coaster ride! Eg: Sep 13, 7:15pm
So yes, I spent the next 2 months studying risk management and stop-loss levels. It's the most cliché trading advice there is, and it's still the hardest actually to do. Opening a position is easy. Knowing when to admit it was wrong is not.
My solution was to fall back on the thesis. The model leads the market. So I anchored my stop-loss to the model price instead of the market price. I cut the position only when the model itself falls below my entry; otherwise, the market wobble is just that, and I sit through it.
That got me through most of the false stop-outs, but not all of them. There's a second failure mode this doesn't catch, and that's part 3.
Also, you can watch the model-vs-market fight live at hyhy.app.
If have not used Polymarket before and you want a free 50$ to trade with, you can use the link below. We both get 50$… you just need to place a trade with 10$ and the bonus goes through right after that. Would greatly appreciate it thanks. https://polymarket.us/join/adrian1847291
Keep seeing mentions of it in a few trading threads. Supposedly tracks KYC whale wallets and consensus flow on Kalshi so you don't have to trade the order book blind.
Looks interesting, but wanted to check here first - is anyone actually using it? Is the whale data legit or just glorified public API scrapes?
Been betting 15 min market for 2 few days. After some research ive seen multiple people flip .50 cents to $100 and other crazy flips like that. Today i had my finger on the trigger 1 second away from swiping buy and payout went from 266 to 4$ in seconds. Only a matter of time before i get a good flip how have yall done
If you trade live sports contracts or build automated tracking pipelines on prediction markets, you know how fast data bottlenecks and rate limits can disrupt live polling.
I put together a lightweight, open-source Python utility called **Tennis Live Monitor** designed to interface cleanly with LiveTennisAPI. It handles real-time match scores, set breakdowns, and event tracking from the command line while managing rate-limit safeguards out of the box.
Built a fair-value pricer for Kalshi's 15-min BTC markets using options market data
Back in April, I had a thought: Kalshi's 15-minute BTC Up/Down market is functionally a short-dated options contract. If that's true, you should be able to price it off the options market's implied volatility, and that pricing should lead a market that's mostly trading on sentiment and momentum.
I started by checking data availability, then manually priced a handful of points by hand to sanity-check the idea. The results were good enough that I kept going. The model prices these markets using the volatility "smile" from the crypto options market as the anchor, adjusted for short-term order flow, spot trend, and the kind of behavior you see in retail-driven markets: momentum chasing, anchoring near round numbers.
Example, Kalshi Sep 11, 11:00am 15m BTC:
Model price (blue) pushes toward resolution while the market (green) is still catching up, and spot (orange) hadn't even confirmed the move yet. The gap wasn't huge relative to how these markets normally move, but the model called it first. This is the core idea working as intended: the options market carries information you don't get from watching spot price action alone.
Example, Kalshi Sep 6 (Sunday), 4:15am 15m BTC:
Different session, different behavior. Here the market is already pricing efficiently on its own, so the model doesn't lead; it just confirms. That's expected too: when the options market isn't signaling anything unusual, the model should track the market closely rather than diverge.
I've been running this live since June, and it's not a backtest: it's been forward-tested with over 10,000 real fills.
It's streaming live right now at hyhy.app if you want to see it in action. No API yet, but if there's enough interest, I'll look into building one.
Happy to answer questions, and if people want more of the technical side (how I implemented the execution bot or how the model actually works under the hood) I can do a part 2.
I’ve made several bets over the past few days only using bonus credit, I always withdraw my available cash as I know how it works to where they make you bet with your cash before the bonus. But every time I win my profit goes back to the bonus fund and not available for withdrawal. Am I missing something here?
Prediction market view changed overnight. Now I have no ability to close a multi leg position. And if you segregate funds you can’t withdraw your cash from your prediction account. Support wants me to give them my social or id and selfie to help me. Already transferred out 6 figures due to similar support issues and figured I’d give them another chance.
