What Institutional-Grade Crypto Trading Actually Means

Margin Management Infrastructure

In systematic trading, margin is often seen as a constraint rather than a system. For single-exchange strategies, this might be true. It typically ends up being a basic constraint that determines how many positions one can open. In practice, when strategies straddle several exchanges, margin behavior is one of the main determinants of whether a strategy can be operated consistently. It becomes a more sophisticated problem of moving funds between exchanges to optimize margin utilization across venues.

Moreover, perp venues compute equity differently, apply different collateral haircuts, use different mark price inputs, and enforce liquidation through venue-specific maintenance schedules. The result is that maintaining “the same margin” can have meaningfully different liquidation risk depending on where it is held.

Blockhouse treats margin management as a core layer of infrastructure. The objective might not be to predict where markets go, but optimal utilization of margin can still offer ample opportunity to squeeze more alpha out of any strategy. As such, it is critical to maintain a continuous, venue-aware view of liquidation proximity and to respond consistently as buffers expand or compress.

Portfolio Liquidation Distance (PLD)

PLD is a proprietary metric, and the primary metric we use to track liquidation proximity across a multi-venue book.

It is computed in real time across all open positions and venues, producing a continuous read on how close any position is to liquidation under the venue’s current margin rules. The intention is to make liquidation risk measurable and comparable across venues rather than inferred from a patchwork of dashboards.

Conceptually, PLD answers:

Here, the details matter because while we can treat “distance to liquidation” as a universal concept, the inputs depend on the venue:

• Maintenance margin schedules and how they scale with position size

• Equity definitions (including how unrealized PnL is treated)

• Collateral weighting and haircuts by asset

• Mark price construction and index inputs

• Margin mode behavior (cross vs isolated), and venue-specific nuances inside each

PLD is computed using live venue state - positions, balances, and margin usage - so the metric updates as conditions change. That includes changes driven by the market, changes driven by funding and basis moves, and changes driven by margin adjustments from the venue.

Margin Management Server

To monitor PLD and respond quickly as it approaches cautionary levels, we have a dedicated server built exclusively for this purpose.

It continuously ingests margin state across connected venues and maintains a consolidated view of margin health, and each instance is dedicated to an individual client’s trading account. The server monitors PLD, margin usage, and venue-specific risk indicators in real time. When buffers compress or margin usage approaches thresholds, the server can trigger alerts or protective actions before liquidation becomes a near-term outcome.

Protective actions are configurable and depend on venue capabilities and client preferences, but typically include:

• Rebalancing collateral across venues or sub-accounts to restore buffer

• Reducing exposure on the leg driving margin pressure

• Adjusting hedges to reduce liquidation proximity

• Pausing new risk on a venue while state certainty is degraded (e.g., stale websockets, throttling, degraded endpoints)

In standard operation, despite the management system having to take in multiple inputs, the resulting action is often very simple. More often than not, the only proactive action that needs to be taken is simply a transfer of excess funds from one account to another. It is rare that the margin system needs to affect open positions or materially impact trading operations.

In fact, the most common pattern in multi-venue books is that margin tightens first on one venue, not everywhere at once. This is especially true when operating long-short strategies, as token price changes can have inversely correlated effects on margin utilization across the two venues as prices move in opposite directions. The standard resolution is simply shifting the newly excess margin on one venue to the now constrained one.

Single Venue vs Cross-Venue Margin Monitoring

Margin risk is straightforward when you only trade on one venue and you can live inside a single margin model. It becomes more operationally complex when exposure spans multiple venues with different collateral sets and different liquidation mechanics.

Even when a book is directionally neutral, margin can compress due to:

• Temporary basis dislocations and widening spreads

• Changes in collateral composition and haircut impacts

• Asymmetric liquidity conditions across venues

• Venue rule changes that shift maintenance requirements

• Transfer latency when collateral needs to move between accounts

The margin server is designed to keep the system aware of these changes in real time and to reduce reliance on manual reconciliation. This is particularly relevant in strategies that are deployed continuously, where the operational requirement is consistency rather than occasional intervention.