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Black-Scholes Option Pricing Calibration L1-438

Computational FinanceOption pricingδ=3 · standardL_DAG = 2📋 Stub — not mineable
📋

Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

Black-Scholes Option Pricing Calibration: Black-Scholes calibration: infer implied volatility sigma_impl from observed market option prices. The forward operator produces the measurement through a 3-node primitive DAG (M.bs.formula…); recovery is posed as a parameter_estimation problem. Difficulty tier delta=3 with effective condition number kappa_eff~10; bid_ask_spread_percent, liquidity_premium set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

N.pointwise -> O.chi2.market_price -> S.newton.root_finding
N.pointwiseO.chi2.market_priceS.newton.root_finding

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
200

Existence of the recovered implied_vol_surface is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 10); bid_ask_spread_percent dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Market bid ask gaussian sets the irreducible data-fidelity floor.

Solvability C

Solver class:
classical [Brent_root_finding or Newton_Raphson per option]
Convergence rate q:
2
Complexity:
O(N_strikes * N_maturities) per calibration per iteration

Specs (0)

No L2 specs registered yet for this principle.