Deep dives into prediction-market mechanics, venue security and settlement risk.
INTELLIGENCE ARCHIVE
The screen shows a probability. The real story is the machinery behind it: incentives, liquidity, evidence, and the rules that turn a prediction into a payout.
Why contract literacy, information boundaries, and accountable automation belong inside a trading strategy—not in a disclaimer added afterward.
A strong trading culture does not reward the loudest forecast. It rewards honest updates, dissent, clean records, and decisions that survive an unfavorable result.
Loss aversion, outcome bias, and the urge to get even can overpower a sound forecast. Here is how to design a trading process that gives judgment a fighting chance.
Turn ‘I knew it’ into an auditable forecast. Probability buckets, Brier scores, and honest comparisons reveal what conviction alone cannot.
HFT is a trading method; prediction markets are a market category. Their collision is less a replacement story than a contest over information, inventory, and execution.
An inside look at Infiniti's research, Kalshi trading, ledger, and risk views—and why a connected workflow matters more than another flashing quote.
From LMSR to outcome-token pools, automated market makers turn inventory into quotes. The mechanism explains liquidity—but does not promise accurate probabilities.
Supplying liquidity means selling immediacy while carrying inventory and information risk. A practical look at AMMs, order books, and the hidden cost of being available.
‘Reign supreme’ should mean command of your process, not a promise to beat everyone. A field guide to contract literacy, specialization, and disciplined execution on Kalshi.
Compare safety across prediction market venues. Kalshi offers CFTC regulation; Polymarket offers non-custodial trading. Learn which matches your risk tolerance.
Learn how arbitrage scanners detect price gaps across Kalshi and Polymarket, execute both legs automatically, and what to check before you trade.
Full Kelly, half Kelly, and the binary-specific formula for sizing YES/NO positions when the payoff is $1 or nothing.
Why the same event trades at two prices, how long the gap stays open, and the execution engineering required to capture it.
Bid/ask depth ratios, queue position, and what the shape of a prediction market orderbook tells you about the next five minutes.
Favourite-longshot bias is fifty years old, persists in binary markets, and still gets traded against incorrectly. Here's the careful version.
The first 90 seconds after breaking news follow a repeatable pattern. Trade the pattern, not the headline.
Inventory risk, spread capture, and the quoting math for providing liquidity in YES/NO markets.
When candidate A + B + C prices sum to 104%, someone is mispriced. Negative-risk mechanics, conversion, and the exhaustive-set check.
Losing streaks in 55%-accurate trading are longer than your intuition says. Size for the streak you'll actually get.
Convert prices to probabilities, track their velocity, and use cross-market consistency checks to find what's actually mispriced.
CPI prints, Fed meetings, verdict dates: scheduled catalysts create predictable volatility patterns you can structure trades around.
A grounded strategy for Infiniti Markets: turn fragmented market data into explainable research, controlled execution, and a measurable learning loop without confusing AI ambition with exchange authorization.
A cheap fill can be an expensive signal. Understand adverse selection, stale quotes, and why execution quality matters more than fill rate.
Above, by, official, first, and revised can turn similar-looking markets into different trades. A practical contract-reading checklist.
A worked total-cost example shows why an attractive probability estimate can still produce an unattractive trade.
Different tickers do not necessarily mean different risks. Separate correlation, logical dependence, and genuine settlement hedges.
Near-expiry contracts hide asymmetric downside, reference-price differences, and shrinking exit options. Understand the last-minute trap.
A city forecast is not a settlement observation. Learn why station identity, daily windows, and preliminary reports matter for weather contracts.
Headline versus core, monthly versus annual, adjusted versus unadjusted: map the exact inflation statistic before the release hits.
Advance, second, third, and annual updates tell different information stories. Match GDP contracts and backtests to the correct data vintage.
Polls estimate preferences, not settlement probabilities. Understand sampling, turnout, shared error, and the missing step from vote share to outcome.
A practical scenario review for binary contracts: total-loss clusters, missing exits, stalled settlement, and the difference between a cap and a safe size.
Set up price alerts across Polymarket and Kalshi to catch arbitrage spreads. Learn to match markets, set thresholds net of fees, and wire alerts to execution.
Prediction markets let you trade on the outcome of real-world events. How event contracts work, what prices mean, and how to place your first trade on Kalshi or Polymarket.
Spread, depth and slippage on Polymarket's order books — how to tell whether the price you see is the price you'll actually get.
Election and sports contracts both settle at $1 or $0, but their information flow, liquidity cycles and edge sources are completely different animals.
Who decides whether a contract pays $1 or $0, how disputes are handled, and why the resolution source matters more than the market title.
How much of your bankroll to risk on a single event contract — the Kelly formula, fractional Kelly, and why most traders should bet far less than full Kelly.
How 15-minute up/down crypto contracts work, what drives their pricing, and the discipline required to trade them without churning your account.
Who provides the liquidity on Kalshi and Polymarket, how market makers set their quotes, and what their behavior tells you about fair value.
The five errors that account for most prediction market losses — and the specific habit that fixes each one.
A novice's guide to entering prediction market trading: open a free Infiniti Terminal account, link Polymarket or Kalshi API keys safely, and test strategies in paper mode before risking capital.
Deploying AI trading agents for Polymarket event contracts means connecting an autonomous execution layer to binary YES/NO markets so trades fire on logic, not instinct.
Choosing between Infiniti Markets and Kairos for prediction market trading comes down to one question: do you need automated strategy execution or low-latency unified order routing?
To backtest prediction market strategies on Kalshi historical data, you need to pull event-contract data via Kalshi's API, build a friction-aware simulator, and measure performance with metrics suited to binary markets.
Active prediction market traders who rely on manual dashboards are already losing ground.
A prediction market trading terminal is worth paying for in 2026 if you trade frequently across both Polymarket and Kalshi, run automated strategies, or need quantitative analysis beyond what native interfaces provide.
No-code routes to running Polymarket arbitrage — where the edges actually are, what tooling executes them, and the execution risks that eat theoretical spread.
A source-verified review of the security surface an institutional participant inherits when trading Polymarket: the Polygon settlement layer, the conditional-token collateral model, the hybrid order book, smart-wallet custody, API authentication, and the optimistic oracle that decides who gets paid.
Your API keys are only as safe as the bot handling them. Permission scoping, AES-256 at rest, TLS 1.3 in transit, key rotation and how Kalshi and Polymarket authentication actually differ.
Side-by-side venue mechanics — maker/taker economics, order-book depth, settlement rules and the regulatory posture behind each book.