Multi-Market Crypto Futures Trading Platform with Dynamic Portfolio Optimization

Customer

Challenge

• Risk-first architecture: Enforce exposure, leverage, and per-asset limits across a fast-moving derivatives venue - without revealing sizing rules or thresholds.
• Volatility & drawdown control: Implement volatility-aware allocation and account-level drawdown protections that can pause or scale risk when conditions shift.
• Cost and churn discipline: Balance trade frequency against fees and slippage.
• Auditability & ops reliability: Provide governance-grade logs, explainable decisions, and recoverable processes for unattended operation.

Solution

Approach: A cross-functional Marsbridge squad - Quant Lead, Risk/Execution Engineer, Data Engineer, and DevOps/QA - delivered an end-to-end risk-managed stack with clear separation between research signals and production controls.

Risk policy & controls

Configurable caps per instrument/group, volatility-scaled allocation, and account-level kill-switch/drawdown halt mechanisms.

Strategy-agnostic execution & monitoring

Orders routed via derivatives exchange API with server-side reconciliation; process supervision, safe restarts, and real-time risk dashboards with alerts.

Backtesting & stress testing

Leakage-safe walk-forward tests, what-if scenario engine for volatility/price shocks, and standardized governance reporting (returns, DD, exposure).

Technologies & tools

Process

1. Discovery & risk charter - define risk objectives, redaction boundaries, and governance artifacts.
2. Data & research - assemble standardized histories; prototype vol-scaled allocation under leakage-safe tests.
3. Risk-control layer - implement exposure caps, drawdown halts, abstention logic, and margin checks; dry-run on historical replays.
4. Paper execution - bring up the exchange API in a non-live environment; validate end-to-end orders and reconciliations.
5. Stress & resilience - scenario testing, failover drills, and recovery procedures.
6. Handover - runbooks, dashboards, and sanitized reports; client retains ownership of any live-trading logic.

Results

• Controls-centric operation: The platform enforces limits (exposure, leverage, drawdown) and pauses when risk deteriorates - reducing tail-risk pathways.
• Transparent oversight: Governance-grade logs and standardized reports increased operator trust and review efficiency.
• Reusable foundation: The risk-control layer is strategy-agnostic, allowing new research to plug in without exposing trade rules.