Prediction markets for hedge funds.
Alpha and tail-risk in a regulated event-contract surface — Kalshi and Polymarket, normalized.
Cross-venue research, normalized intents, risk gates, and reconciliation across Kalshi and Polymarket — wired through your existing accounts. Mandate fit, sleeve construction, and the full execution + portfolio ledger on one surface. The broader infrastructure overview lives at/institutions.
Dutch privateer at dawn — the original alpha hunter at the edge of the chart.
Four sleeves a hedge fund prediction market mandate fills
Most mandates use one or two of these. The fit-test is whether the named exposure is cleaner expressed as a binary contract than as an option, CDS, or futures position.
Data and execution architecture for funds
Five layers, two ownership boundaries. The fund owns Signal and Risk Policy (BYOM and BYOR); SimpleFunctions owns Research, Execution, and the Reconciliation feed; the Venue owns the account and the order book. Capital never leaves the fund’s venue account.
Sample workflows
Two concrete sleeves end-to-end — one event-driven alpha sleeve, one tail-hedge basket. Both run the same five-layer architecture; the difference is sizing, cadence, and acceptable basis risk.
Event-driven alpha sleeve — Fed-cut basket
01Research: pull cross-venue probability for every active Fed-cut contract; cross-reference with the OIS strip via /query-econ02View: encode the desk's thesis (e.g., December cut underpriced by 6pp on Kalshi vs OIS) as a sized view in the fund's model layer03Risk: size by view conviction × fund-side risk policy; verify against the desk's daily-loss and concentration caps04Intent: submit normalized intents with an idempotency key, optional price-trigger, and conservative max-size; runs through dry-run first05Reconcile: hourly pull of fills + open positions back into the fund's OMS; mark-to-current pricing for end-of-day NAV
Tail-hedge sleeve — geopolitical binary basket
01Research: identify a basket of low-probability geopolitical contracts (escalation, treaty failure, sanctions threshold) trading at 3–8¢02View: size each leg as a fraction of the gross hedging budget; the basket is the position, individual legs are insurance premiums03Risk: cap aggregate basket cost as a percentage of fund AUM; rebalance on a fixed cadence (monthly is typical)04Intent: submit small-size intents across the basket; dry-run validates cost and routing; live submission is incremental05Reconcile: track basket carry vs realized payouts; the sleeve's P&L is the difference between premium decay and tail payouts
How integration works
Four operational facts a fund operator needs before binding a strategy.
Onboarding
Bind Kalshi (RSA) and/or Polymarket (Ethereum) keys through dry-run. Dry-run flows the full pipeline — risk gates, normalization, route — without submission. Flip individual strategies to live when the soak satisfies the desk.
Capital + settlement
Capital sits in the fund's venue account; cash settlement at expiry follows the venue's rules. The platform reads positions and writes intents through the BYOK credential the fund supplies.
Pricing
Software subscription, tiered by seat / agent / volume after a technical review. No per-trade commissions; venue trading fees pass through.
Audit + reconciliation
Authenticated portfolio-ledger reads expose intents, risk-gate decisions, recorded fills, and grouped attribution with actor + timestamp + source. CSV / JSON / Parquet export wired into the desk's accounting pipeline as an integration step.
Liquidity and capacity — the honest version
Kalshi and Polymarket are real venues with real capacity, but the books are not uniform. Five things to know before sizing a fund-grade sleeve.
Per-contract depth
Top 50 markets typically show $50K – $500K resting at top-of-book. Larger sizes execute via incremental orders; the screener exposes per-market depth so the fund can size before it commits.
Total book at market
Aggregate across all tracked Kalshi + Polymarket markets is a meaningful number, but it is not a uniform pool. Liquidity concentrates in the top 20–50 contracts; the long tail is thin and fund-sized orders move it.
Ramp guidance
Most desks ramp over weeks, not days. Start at 10–20% of intended sleeve size, watch slippage on the screener's slippage-adjusted IY, increase only when realized slippage matches the model's assumption.
Basis risk
Binary event contracts settle to a venue-defined event resolution. The fund's underlying exposure may be continuous (a return distribution) — the binary is an approximation. Don't treat a binary as a perfect hedge for a continuous exposure.
Capacity ceiling
For systematic strategies in the top 20 contracts, fund-sized notional is feasible; for long-tail strategies, capacity is mandate-dependent and venue-dependent. Talk to the venue's institutional desk in parallel — Kalshi has one, Polymarket's capacity model is different.
Read next from the library
Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.
From Boesky to Bots: Porting Hedge Fund Alpha to Prediction Markets
Classic hedge fund strategies map onto Polymarket and Kalshi with surprising fidelity. Ten mappings from cleanest analog to most speculative — Levy, Buffett, Greenblatt, Tartaglia, Griffin, Meriwether, Soros, Taleb — with documented cases, dollar amounts, and the 2024–2026 academic evidence.
Why "Prediction Market Index Funds" Are Mathematically Dubious
Index funds need continuous returns, shared factor exposures, and meaningful weights. Binary prediction-market contracts have none. A naive PM index converges to noise, not a return.
How I track my macro thesis across 49 Kalshi contracts without checking the screen
How I use a causal tree and 15-minute heartbeat to monitor 49 Kalshi contracts for my Iran-oil-recession macro thesis without watching the screen.
Causal trees for prediction markets: turning macro intuition into tradeable structure
Learn how to build causal trees — hierarchical probabilistic models — that turn macro intuition into tradeable prediction market structure on Kalshi and Polymarket.
SimpleFunctions vs Oddpool vs Raw Kalshi API — Which Prediction Market Tool Should You Use?
Compare SimpleFunctions, Oddpool, and raw Kalshi/Polymarket APIs for prediction market trading. Honest breakdown of features, pricing, and when to use each tool.
Event Contract
Event contracts are binary instruments tied to real-world events. Learn how they work on Kalshi and Polymarket.
FAQ
What about Polymarket?
Cross-jurisdiction mandates run both venues; US-only mandates typically run Kalshi alone. The platform supports either or both — the fund decides which venue's account to bind via BYOK.
How deep is the orderbook on a typical contract?
Top 50 markets typically show $50K – $500K resting at top-of-book; the long tail is meaningfully thinner. The screener exposes per-market depth and a slippage-adjusted yield; size accordingly. Don't assume uniform depth across the venue.
How does a fund actually scale into a position?
Most desks ramp incrementally — 10–20% of intended sleeve size first, observe realized slippage on the screener's slippage-adjusted IY, and increase as the realized number tracks the model. SimpleFunctions intents support price-triggers and idempotency keys, which let a desk script ramp logic without double-fills.
Tax treatment?
Kalshi event contracts are typically treated as Section 1256 contracts (60/40 long-term/short-term blend) for US tax purposes — the standard CFTC futures treatment. Polymarket treatment depends on the fund's structure.
How does NAV reporting work?
The platform exposes authenticated portfolio read models for recorded positions, fills, attribution, risk, and mark-to-current review. NAV calculation itself remains with the fund administrator. Venue-side statements stay authoritative for capital movement; CSV / JSON / Parquet export is wired as an integration step when the desk needs it.
How does this compare to CDS, options, and futures?
Event contracts pay a fixed dollar on a binary outcome; CDS pays on a credit event with continuous notional; options pay a continuous payoff on price; futures track price linearly. For named-event exposure (election, policy decision, geopolitical breakout), binary contracts are more capital-efficient than options or CDS. For continuous exposures (rates, FX, equity vol), traditional instruments remain the cleaner hedge — the binary is an approximation.
What is the basis risk?
Binary settlement is the main basis. The contract pays on the venue-defined event resolution; the fund's underlying exposure may be a distribution. Two specific cases worth flagging: (1) timing basis — the contract resolves at expiry, the fund's exposure may be continuous through the period; (2) definition basis — the contract's resolution criteria may differ subtly from the fund's economic event. Read the venue's rulebook for every contract you size into.
What is the framing for LP communication?
For Kalshi: "regulated event contracts on a CFTC-designated contract market." Funds typically describe the sleeve as "event-contract derivatives" in offering documents and the platform as "third-party software for trading and risk-checking event contracts." LPs accept this framing in practice.
What AUM bands does this fit?
Sub-$100M funds typically use the platform as a research + sizing tool with small live-trading sleeves. $100M – $1B funds run dedicated event-contract sleeves of meaningful size. $1B+ multi-strats run baskets and tail-hedges across both venues, often with capacity coordination through the venue's institutional desk. Capacity is mandate-dependent; we recommend a capacity conversation early in onboarding.
What integrations are needed?
Three layers for a real fund integration: (1) BYOK credential binding for Kalshi and / or Polymarket; (2) portfolio ledger/read API review, with reconciliation export wired into an accounting pipeline only when required; (3) intent submission either through the platform's REST surface, the agentic CLI, or a custom client. Most desks finish dry-run integration within one to two business weeks.
What does the platform actually do during a trade?
It accepts a normalized intent (market, side, size, price, trigger, expiry, idempotency key), runs the fund's configured risk gates, maps the intent to the venue's order shape, submits through the BYOK connection, and surfaces the status state machine + audit record back to the fund.
Related surfaces
Institutional infrastructure
Audit log, BYOK, reconciliation — the software layer between raw venue API and fund operations.
Prediction market hedging
Map real-portfolio exposures to event contracts as binary or basket hedges.
Prediction market execution
Intents, triggers, routing, monitoring — the execution surface fund signals talk to.
Prediction market funds
For GPs raising capital to deploy systematically into Kalshi and Polymarket.
Quant trading
Systematic strategies on Kalshi and Polymarket — backtests, signals, calibration.
Macro traders
Fed cuts, recession, inflation, election, geopolitics — binary contracts on the macro view.
Real-time data API
Sub-second WebSocket and REST surface — the live feed strategies actually consume.