Prediction-Market Alpha Layer
A clean feed of prediction-market probabilities mapped to your existing macro and event-driven framework — Fed move probabilities, geopolitical risk markers, election-implied probabilities, joined to the equity sector exposures and macro positions they should influence.
- Engagement
- 6–10 week build · ongoing pred-market data feed
- Built for
- Macro PMs · Event-driven PMs · Policy-themed funds
Kalshi and Polymarket aggregate informed bettors who care intensely about being right. The implied probabilities on Fed rate decisions, geopolitical outcomes, election results — they move before macro markets do. Most funds aren't wiring those probabilities into their decision stack.
What this is
A custom integration layer that takes prediction-market probabilities — Kalshi, Polymarket, select smaller markets — and joins them to the framework your fund already uses to size macro and event-driven positions.
Three layers:
- Ingestion. Per-market data feeds with documented latency. Source-reliability scoring per contract, per market. Backfill of historical contract resolutions for backtests.
- Mapping. Pred-market contracts → the macro factors, sector exposures, and event probabilities your existing models consume. The mapping layer is the work; the raw prices are commodity.
- Disagreement detection. Surfaces where pred-market disagrees with the rates curve (for Fed contracts) or equity-implied probability (for event contracts) — the moments where the signal matters.
How it's built
Direct API or websocket integration per market. Polars-based normalization pipeline. Disagreement detection runs on top of your fund's existing rates curve and equity vol surface — pulled via your existing data infrastructure or built into the engagement.
What you get
- Per-contract live and historical data, normalized.
- The mapping from contract universe to your fund's macro factor framework.
- Disagreement alerts when pred-market diverges from other implied-probability series.
- Backfill for backtest validation.
- Documented per-contract reliability so PMs know when to trust the series.
Engagement is shape, not list.
Length and price are functions of the data and the destination. The shape below is the typical engagement.
- Length
- 6–10 week build · ongoing pred-market data feed
- Lead
- Bogdan
- Cadence
- Async, weekly
- Bar
- Production
Scoped during the discovery call against the actual data and the operation it integrates with.
Principal engineer. Architecture and most code ships through one keyboard.
Written updates between, calls when the decision needs the room.
Async correctness, capacity under burst, observability at every boundary.
Products this composes with.
Same suite, or vertical-specialized versions in another.
- Same suite · Hedge Fund Suite
Alternative Data Signal Engine
A production pipeline that ingests one or more unconventional datasets, normalizes against a fund-internal schema, and serves processed factor scores, back-tested signals, and event-time alerts to the research stack.
- Same suite · Hedge Fund Suite
Cross-Lingual News & Filings Intelligence
Intraday sentiment scores and event extractions for tickers, sectors, and macro themes, sourced from non-English news, regulatory filings, and social — covering the languages where your existing stack goes dark.
- Same suite · Hedge Fund Suite
Macro Risk Overlay
A regime classifier trained on rates, vol, credit-spread, and macro-data series — paired with a recommended position-sizing and hedging overlay that the portfolio construction team consumes alongside the existing risk framework.
What buyers ask about this one.
Aren't prediction-market prices already public?
The prices are. The work is mapping them onto your decision framework — converting the implied probabilities into the macro factors and equity exposures your PMs already trade on, joining the prediction-market series against your existing macro data, and surfacing the moments where pred-market disagrees with the rates curve or the equity-implied probability.
Which markets do you cover?
Kalshi (Fed moves, jobs reports, geopolitical, elections), Polymarket (broader event coverage, less curated, more liquid for some themes), Manifold and PredictIt where signal is clean enough. Source-specific reliability scoring — Kalshi data quality is higher than Polymarket on most macro contracts; the layer reflects that.
Distinction from your Prediction Markets work for platforms themselves?
Different product, different buyer. The platform-side work (pricing, simulation, intelligence tools FOR Kalshi/Polymarket-class operators) is its own engagement. This layer is for hedge funds CONSUMING prediction-market signal. Two distinct buyers, two distinct deliverables — we keep them separate.
What's the latency?
Near-real-time for the major contracts (Kalshi Fed-decision, Polymarket high-volume events). Daily for the thin contracts where intraday noise dominates. Per-contract documented.
Pricing?
Scoped against contract coverage and the latency tier you need. Discovery call covers both.
If the deliverable matches the gap, the next step is one call.
We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.
Bogdan and team · async-first · OP—2026