Black-Scholes 2D rainbow option (MOL tensor grid)

DISADVANTAGES2 · dim 841

A baseline wins. At the comparison noise level, the best baseline beats SolvSRK by at least 10 percentage points of survival, or by at least 0.05 balanced score when survival is tied. Use the winning baseline named on the problem page — not SolvSRK. All verdicts →

841D MOL discretisation of the 2D Black-Scholes backward PDE on a 31x31 log-S1 x log-S2 tensor grid for a max-of-two-asset rainbow call. 9-point stencil with rho cross term -- LRDE row-1 GREEN.

Finance

Problem definition

Margrabe 1978; standard 2D MOL

Canonical RHS excerpt from the registered callable used for this benchmark cell. Expand it to verify the state equations; it is not a standalone runnable fixture.

Show canonical RHS excerpt
def rhs(t: float, y: np.ndarray) -> np.ndarray:
    return A_csr @ y + g_arr
Parameters
  • A_csr = sparse_matrix(shape=(841, 841), nnz=7225)
  • g_arr = repeat(0, 841) [shape=(841,)]
Initial condition
y(0) = [0, 0, 0, 0, 0, 0, …] [shape=(841,), min=0, max=174.105792153]
Horizon
t ∈ [0, 0.5]

Canonical RHS excerpt captured from the same registered callable used for the published benchmark. Frozen closure values are summarized below; helper imports and solver settings are intentionally omitted.

Fingerprint

Spread: low

Default noise: none

Recommendation snapshot

Clean best: SolvSRK

Noisy best: SciPy DOP853

Coverage

14 solver arms · clean + 5 noise levels

Ranked on survival, precision, and speed

Versions & freeze

Methodology →
Freeze
2026-08-13
libsolvsrk
2.3.0
SciPy
1.14
SUNDIALS
CVODE (bundled backend)

20 seeds/cell default · 14 arms · TRL 4–5 · simulation-lab validated · this page: Black-Scholes 2D rainbow option (MOL tensor grid) (black-scholes-2d-rainbow-option-mol-tensor-grid)

Governed SolvTune benchmark freeze; per-arm medians only. RHS definitions and raw trial rows are not published.

Self-reported by Resonix Labs · not independently verified

Results matrix

Pick an objective and a noise level to rank all arms on survival, median SCD, median nfev, and median wall time. Medians across seeds.

Objective

Best overall trade-off of survival, precision, and speed.

Noise level

#SolverSurvivalSCDnfevWallScore
1SolvSRK
100%
10.76,2481.17 s0.874
2SciPy RadauSciPy
100%
10.61,362420 ms0.872
3SciPy DOP853SciPy
100%
9.5981 ms0.845
4SciPy LSODASciPy
100%
8.91332 ms0.832
5Tsit5external
100%
8.5156653 ms0.821
6SciPy RK45SciPy
100%
8.31762 ms0.816
7CVODE Adamsexternal
100%
8.01,79983 ms0.809
8CVODE BDFexternal
100%
7.51,78376 ms0.798
9SciPy RK23SciPy
100%
7.56477 ms0.797
10SciPy BDFSciPy
100%
7.31,045171 ms0.793

At Clean, best balanced arm is SolvSRK.

Values are medians across seeds, measured by Resonix Labs on Resonix hardware and not independently verified; nfev and wall are on reference lab hardware (indicative). Under injected noise only SolvSRK and the SciPy arms are run. How we measure accuracy → · Verification status →

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SolvSRK · 30-day trial

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Cite this page

Replace the access date. Pin the freeze ID and library versions when comparing against a later export. Cite it as what it is — a self-reported vendor benchmark, not an independently verified result. The note field says so; please keep it.

@misc{resonix_evidence_black_scholes_2d_rainbow_option_mol_tensor_grid_2026,
  title        = {Resonix Evidence Portal: Black-Scholes 2D rainbow option (MOL tensor grid)},
  author       = {{Resonix Labs (Canada) Inc.}},
  year         = {2026},
  howpublished = {\url{https://resonix.tech/evidence/problems/black-scholes-2d-rainbow-option-mol-tensor-grid}},
  note         = {Self-reported vendor benchmark; internally generated by Resonix Labs and not independently verified. Accessed YYYY-MM-DD. Freeze 2026-08-13; libsolvsrk 2.3.0; SciPy 1.14.}
}

Related

TRL 4–5 · simulation-lab validated · 398 problems · 14 solver arms · clean + 5 noise levels

Freeze: 2026-08-13 · scipy 1.14 · libsolvsrk 2.3.0 · Methodology

Self-reported by Resonix Labs · not independently verified · Verification status