Prediction-market portfolios sit awkwardly inside conventional margin engines — payoffs are binary, contracts correlate through systematic factors that don't map cleanly to delta exposure, and a position you'd call a hedge on paper can leave threshold-divergence basis risk uncovered.

With CFTC-regulated bitcoin perpetual futures now live on Kalshi (May 29, 2026), a new question opens up: how does a perp's linear delta interact with a strip of Kalshi binary contracts on the same underlying? The dashboard below models that explicitly for two assets (BTC + SPX), and the second tab carries forward the 8-cluster portfolio margin framework that preceded this work.

Tour the four views first (illustrated below — sticky feature index at the top jumps you to anything that looks interesting), then drive the live dashboard further down the page.

A perp tracks spot one-for-one — its delta is constant at +qty and its PnL is linear. A Kalshi binary "S > K by T" has a digital payoff with delta that peaks near the strike and decays away from it — so a strip of binaries at multiple strikes builds a step function payoff and a bell-curve delta surface.

The two instruments share the same underlying but their PnL shapes are fundamentally different — and that's where the analytic interest lies. A long perp + long binary strip at upside strikes amplifies the bullish bet past each strike. A long perp + short binary at the same strike caps your upside (a synthetic covered-call). A short perp + long binary builds an asymmetric structure that profits more in tails than at the median. Cross-margining them isn't conceptual — it's just summing two delta surfaces and watching where they cancel.

With Kalshi's BTCPERP approval (May 29, 2026) and Coinbase's Deribit-via-FCM pathway, the universe of regulated perp products with matched Kalshi binary strips just multiplied. Cross-asset views like this one stop being illustrative and start being load-bearing for the trading book.

The perp leg

A long perp position with quantity q at entry spot S₀ has PnL q × (S − S₀) at any current spot S. Delta (∂PnL/∂S) is constant at q. No curvature, no time decay; the funding mechanism keeps the contract tethered to spot continuously.

The binary leg

A Kalshi binary "S > K by T" pays $1 if the underlying clears the strike at expiry, $0 otherwise. Under risk-neutral pricing (with rates and dividends approximated as zero for sub-year contracts):

• Price = N(d₂) where d₂ = (ln(S/K) − σ²T/2) / (σ√T)
• Delta = φ(d₂) / (S × σ × √T) — peaks when S ≈ K, decays as the strike moves far away
• Implied probability of the event ≈ binary's market price

Portfolio aggregation

Net delta = perp_qty + Σ binary_qty × digital_delta(S, K, T, σ). The "delta-hedge perp lots" KPI shows how many perp lots would flatten the binary book at the current spot — this is the perp's natural role as a continuous delta tool against a step-shaped binary portfolio.

The PnL curve

For each spot in a scanning range, the engine computes the perp's linear PnL plus each binary's digital PnL, and renders the total. The chart makes the asymmetry visible — perp PnL is a straight line; binary PnL has flat-then-step regions corresponding to each strike clearing.

Implied probability extraction

For binaries at the same expiry, prices give P(S > K) at each strike. Differences between adjacent strikes give bucket probabilities (P(K_i < S < K_{i+1})), letting you read a market-implied distribution off the strip directly.

This is a research and education tool. It is not investment advice, not a trading system, and not a settlement-grade risk system. Specifically:

• Sample portfolios are illustrative. The BTC and SPX positions shown are constructed to demonstrate the analytics, not real books.
• Black-Scholes assumes log-normal spot and constant vol. Real crypto spot has fat tails, jumps, and stochastic vol — so the risk-neutral "implied probability" from a binary price differs from the true market expectation, often materially in crypto.
• Zero rates assumed. Acceptable for sub-year Kalshi contracts; the small rate adjustment doesn't materially change the cross-asset shapes the dashboard surfaces.
• No transaction costs, slippage, or funding-rate friction. The perp's linear PnL is the spot move; in reality you pay 8-hour funding (Kalshi) or hourly (Hyperliquid) which compounds against you when long-funded.
• The Margin Framework tab is a reference view. The full interactive 8-cluster Monte-Carlo lives in the v1 legacy dashboard and the framework PDF. Bringing that engine into v2 as a fully interactive port is on the roadmap.
• Political event cross-margining is not yet modeled. Elections, Clarity Act, war scenarios — these need event-specific delta models that aren't in this build.

• Live binary prices. Replace static entry prices with a Kalshi-API mark layer once a feed contract is in place.
• Political event modeling. Election outcomes, regulatory events (Clarity Act, MiCA milestones), war scenarios — each as a named-state Markov layer that overlays the perp linear delta.
• Full Monte-Carlo port. Bring the 8-cluster cross-portfolio margin engine from the v1 dashboard into v2 as a native interactive component.
• Vol surface. Replace single-σ assumption with a per-strike, per-expiry surface fit from the binary strip itself (model-implied vol backed out of digital prices).
• ETH + SOL underlyings. Extend the two-asset model to full crypto coverage with cross-correlation aware margining.