Autonomous FX Risk Mitigation Agent with OpenAI Agents SDK and Claude 4 Sonnet
With institutions rapidly scaling cross-border liquidity operations, institutional FX risk requires proactive hedging strategies that execute in fractions of a second when exposure limits are breached. Autonomous agents can actively monitor rate differentials and trigger automated forward contracts or swap orders. In this challenge, you will implement an autonomous FX hedging agent using the OpenAI Agents SDK powered by Claude 4 Sonnet. The agent will monitor real-time multi-currency exposure and autonomously trigger hedge executions when volatility indices cross predefined risk bands.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an autonomous FX risk mitigation agent using OpenAI Agents SDK and Claude 4 Sonnet to hedge dynamic multi-currency positions.
How work is evaluated
Evaluates portfolio value protection under simulated currency market shocks.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
exposure_limit_enforced
Verifies unhedged risk is driven below target max exposure
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
sharpe_ratio_improvement
Relative improvement in portfolio Sharpe ratio post-hedging • target: 1.8 • range: 0-5
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Set up OpenAI Agents SDK agent definitions with custom dynamic function tools
Integrate Claude 4 Sonnet via API adapter endpoints for advanced mathematical reasoning
Enforce maximum downside loss limits through strict tool guardrails
Build real-time position audit traces for treasury risk officer evaluation
Reference links and supporting material
Historical foreign exchange spot and forward curves under periods of elevated macroeconomic volatility.
Challenge setup
Evaluates portfolio value protection under simulated currency market shocks.
Challenge input
JSON portfolio snapshot and FX rate shock matrix
OpenAI Agents SDK
Official framework for multi-turn autonomous agent loops.
Claude 4 Sonnet
Advanced model offering superior mathematical reasoning and precision.
Evaluated output
JSON containing execution_orders and unhedged_risk_ratio
- Verifies unhedged risk is driven below target max exposure
- Relative improvement in portfolio Sharpe ratio post-hedging • target: 1.8 • range: 0-5
- Benchmark: FinRisk-Hedging-Bench
- Sharpe Ratio Improvement target: 1.8
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- OpenAI · Required
- Claude Code · Optional
- Claude Code · Optional
- Claude 4 Sonnet · Optional
Evaluation contract
- exposure_limit_enforced · Weight 1
- sharpe_ratio_improvement · Weight 1
Metrics
- sharpe_ratio_improvement · Target 1.8
Benchmarks
- FinRisk-Hedging-Bench
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON portfolio snapshot and FX rate shock matrix
Output: JSON containing execution_orders and unhedged_risk_ratio
Execution harness: Python
Evaluation tools
- OpenAI Agents SDK · Agent Framework
- Claude 4 Sonnet · Language Model
Recipe freeze marker
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