| Job ID | Type | Status | Objective value | Created | Download |
|---|---|---|---|---|---|
| Portfolio rebalancing | Completed | -14.2 | Today, 10:23 | · | |
| Credit risk diversification | Running | — | Today, 09:15 | — | |
| Reinsurance pool | Completed | -31.5 | Yesterday, 14:02 | · | |
| Minimum variance portfolio | Failed | — | Jun 12, 2025 |
Minimum‑variance portfolio construction
Discretize asset weights into binary variables, encode cardinality and sector constraints as QUBO penalties, then call /v1/solver/optimize. Æ Hive returns the top‑k lowest‑variance portfolios with feasibility flags and one‑click download of CSV, ZIP, and PDF risk reports.
from aeq import Solverclient = Solver(api_key="aeq_sk_...")problem = client.risk.portfolio_qubo(cov_matrix=sigma,num_assets=20,max_assets=12,sector_limits={"tech": 0.25})result = client.optimize(problem, backend="auto")print(result.best_solution) # variance: 0.0187, feasible ✓result.download("risk_report.pdf")
Credit risk & capital allocation
Optimize loan portfolios to minimize concentration risk while meeting regulatory capital requirements. Æ Hive's API handles QUBO formulation from your covariance data, runs QAOA with error mitigation, and delivers ranked solutions with full auditability — essential for model risk management (SR 11‑7, IFRS 9).
POST /v1/solver/optimizeAuthorization: Bearer aeq_sk_...Content-Type: application/json{"linear": [-0.12, 0.34, -0.05],"quadratic": [[0,1,-0.02],[2,5,0.18]]}✓ Response (top 3 solutions)Rank 1: var=0.011, feasible ✓ | Rank 2: var=0.013, feasible ✓
Reinsurance & catastrophe risk pooling
Select the optimal mix of reinsurance treaties to minimize total risk exposure under Solvency II or IFRS 17 constraints. Æ Hive handles binary selection variables, loss distributions, and treaty limits as a single QUBO — giving actuaries quantum‑enhanced treaty structures in hours, not weeks.
from aeq import Solverproblem = {"linear": [0.05, 0.03, 0.07, 0.02],"quadratic": [[0,1,0.01],[2,3,-0.02]]}result = Solver(api_key).optimize(problem)print(result.best_solution) # selects treaties 1 & 3
Formatted for stakeholders, includes efficient allocation, risk contribution, and classical comparison.
Raw solution vectors, objective values, and feasibility flags for every job.
Complete package: QUBO, QAOA circuit (OpenQASM), raw bitstrings, and convergence plot.