{"abstract":"Options at the minimum requirement exclude their own premium.","category":"Options payoff and settlement","checks":8,"contract":"Inputs kind, underlying price, strike, premium, contracts and multiplier. Out-of-the-money amount is max(K-S,0) for calls and max(S-K,0) for puts. Per-unit requirement = premium + max(20% of underlying - OTM amount, 10% of floor base) where the floor base is the underlying for calls and the strike for puts. Return requirement*multiplier*contracts rounded to cents.","evaluation_group":"w2-options_payoff_and_settlement-naked-short-margin","failed_approach":"Dropping the premium entirely understates every requirement.","family":"w2-options_payoff_and_settlement-naked-short-margin-premium-inclusion","id":"FA-61631","implementations":{"attempt":{"sha256":"3ca2599ecd1bc307cdc0b5b9ace200c23ac896208d6275a8e20220d5a6a16d48","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(kind, underlying, strike, premium, contracts, multiplier):\n    S = Fraction(str(underlying))\n    K = Fraction(str(strike))\n    P = Fraction(str(premium))\n    otm = max(K - S, 0) if kind == 'C' else max(S - K, 0)\n    floor_base = S if kind == 'C' else K\n    req = max(S * Fraction(20, 100) - otm, floor_base * Fraction(10, 100))\n    return float(round(req * multiplier * contracts, 2))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression premium inclusion 1', ['P', 120.0, 95, 3.4, 1, 100], 1290.0], ['regression premium inclusion 2', ['C', 80.0, 90, 0.5, 2, 10], 170.0], ['partial repair probe 1', ['P', 104.25, 110, 3.4, 1, 100], 2425.0], ['partial repair probe 2', ['P', 100.0, 95, 3.4, 1, 10], 184.0], ['normal control 1', ['P', 80.0, 90, 8.0, 1, 10], 240.0], ['normal control 2', ['P', 80.0, 105, 15.1, 2, 10], 622.0], ['normal control 3', ['P', 100.0, 100, 15.1, 1, 100], 3510.0], ['normal control 4', ['C', 100.0, 110, 1.25, 1, 100], 1125.0]], [['regression premium inclusion 1', ['P', 120.0, 95, 1.25, 1, 100], 1075.0], ['regression premium inclusion 2', ['C', 92.5, 110, 0.5, 10, 100], 9750.0], ['partial repair probe 1', ['P', 80.0, 95, 1.25, 1, 100], 1725.0], ['partial repair probe 2', ['P', 92.5, 105, 8.0, 1, 10], 265.0], ['normal control 1', ['C', 100.0, 95, 0.5, 10, 10], 2050.0], ['normal control 2', ['C', 100.0, 110, 1.25, 2, 100], 2250.0], ['normal control 3', ['C', 100.0, 110, 15.1, 1, 10], 251.0], ['normal control 4', ['P', 120.0, 95, 0.5, 2, 100], 2000.0]], [['regression premium inclusion 1', ['P', 120.0, 95, 3.4, 1, 100], 1290.0], ['regression premium inclusion 2', ['P', 120.0, 95, 1.25, 10, 10], 1075.0], ['partial repair probe 1', ['C', 92.5, 90, 3.4, 10, 100], 21900.0], ['partial repair probe 2', ['P', 80.0, 95, 8.0, 10, 10], 2400.0], ['normal control 1', ['C', 92.5, 95, 8.0, 2, 10], 480.0], ['normal control 2', ['C', 104.25, 105, 1.25, 1, 10], 213.5], ['normal control 3', ['P', 92.5, 95, 1.25, 10, 100], 19750.0], ['normal control 4', ['C', 80.0, 95, 3.4, 1, 100], 1140.0]], [['regression premium inclusion 1', ['C', 80.0, 90, 15.1, 2, 10], 462.0], ['regression premium inclusion 2', ['P', 120.0, 105, 1.25, 10, 10], 1175.0], ['partial repair probe 1', ['P', 100.0, 95, 3.4, 1, 10], 184.0], ['partial repair probe 2', ['P', 100.0, 100, 1.25, 2, 10], 425.0], ['normal control 1', ['C', 80.0, 100, 1.25, 1, 10], 92.5], ['normal control 2', ['P', 120.0, 95, 0.5, 2, 10], 200.0], ['normal control 3', ['P', 80.0, 100, 15.1, 2, 10], 622.0], ['normal control 4', ['C', 80.0, 105, 0.5, 2, 100], 1700.0]], [['regression premium inclusion 1', ['C', 80.0, 100, 15.1, 2, 100], 4620.0], ['regression premium inclusion 2', ['P', 104.25, 90, 8.0, 1, 100], 1700.0], ['partial repair probe 1', ['P', 80.0, 95, 3.4, 10, 100], 19400.0], ['partial repair probe 2', ['P', 80.0, 105, 0.5, 1, 10], 165.0], ['normal control 1', ['C', 120.0, 105, 3.4, 2, 100], 5480.0], ['normal control 2', ['C', 80.0, 95, 8.0, 10, 10], 1600.0], ['normal control 3', ['C', 100.0, 90, 0.5, 10, 100], 20500.0], ['normal control 4', ['P', 120.0, 100, 15.1, 10, 10], 2510.0]]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"8b082d5a6c55508c3b8364a5a403ef347498831c8dfc0c2b01fcf7202339fbe4","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(kind, underlying, strike, premium, contracts, multiplier):\n    S = Fraction(str(underlying))\n    K = Fraction(str(strike))\n    P = Fraction(str(premium))\n    otm = max(K - S, 0) if kind == 'C' else max(S - K, 0)\n    floor_base = S if kind == 'C' else K\n    req = max(P + S * Fraction(20, 100) - otm, floor_base * Fraction(10, 100))\n    return float(round(req * multiplier * contracts, 2))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression premium inclusion 1', ['P', 120.0, 95, 3.4, 1, 100], 1290.0], ['regression premium inclusion 2', ['C', 80.0, 90, 0.5, 2, 10], 170.0], ['partial repair probe 1', ['P', 104.25, 110, 3.4, 1, 100], 2425.0], ['partial repair probe 2', ['P', 100.0, 95, 3.4, 1, 10], 184.0], ['normal control 1', ['P', 80.0, 90, 8.0, 1, 10], 240.0], ['normal control 2', ['P', 80.0, 105, 15.1, 2, 10], 622.0], ['normal control 3', ['P', 100.0, 100, 15.1, 1, 100], 3510.0], ['normal control 4', ['C', 100.0, 110, 1.25, 1, 100], 1125.0]], [['regression premium inclusion 1', ['P', 120.0, 95, 1.25, 1, 100], 1075.0], ['regression premium inclusion 2', ['C', 92.5, 110, 0.5, 10, 100], 9750.0], ['partial repair probe 1', ['P', 80.0, 95, 1.25, 1, 100], 1725.0], ['partial repair probe 2', ['P', 92.5, 105, 8.0, 1, 10], 265.0], ['normal control 1', ['C', 100.0, 95, 0.5, 10, 10], 2050.0], ['normal control 2', ['C', 100.0, 110, 1.25, 2, 100], 2250.0], ['normal control 3', ['C', 100.0, 110, 15.1, 1, 10], 251.0], ['normal control 4', ['P', 120.0, 95, 0.5, 2, 100], 2000.0]], [['regression premium inclusion 1', ['P', 120.0, 95, 3.4, 1, 100], 1290.0], ['regression premium inclusion 2', ['P', 120.0, 95, 1.25, 10, 10], 1075.0], ['partial repair probe 1', ['C', 92.5, 90, 3.4, 10, 100], 21900.0], ['partial repair probe 2', ['P', 80.0, 95, 8.0, 10, 10], 2400.0], ['normal control 1', ['C', 92.5, 95, 8.0, 2, 10], 480.0], ['normal control 2', ['C', 104.25, 105, 1.25, 1, 10], 213.5], ['normal control 3', ['P', 92.5, 95, 1.25, 10, 100], 19750.0], ['normal control 4', ['C', 80.0, 95, 3.4, 1, 100], 1140.0]], [['regression premium inclusion 1', ['C', 80.0, 90, 15.1, 2, 10], 462.0], ['regression premium inclusion 2', ['P', 120.0, 105, 1.25, 10, 10], 1175.0], ['partial repair probe 1', ['P', 100.0, 95, 3.4, 1, 10], 184.0], ['partial repair probe 2', ['P', 100.0, 100, 1.25, 2, 10], 425.0], ['normal control 1', ['C', 80.0, 100, 1.25, 1, 10], 92.5], ['normal control 2', ['P', 120.0, 95, 0.5, 2, 10], 200.0], ['normal control 3', ['P', 80.0, 100, 15.1, 2, 10], 622.0], ['normal control 4', ['C', 80.0, 105, 0.5, 2, 100], 1700.0]], [['regression premium inclusion 1', ['C', 80.0, 100, 15.1, 2, 100], 4620.0], ['regression premium inclusion 2', ['P', 104.25, 90, 8.0, 1, 100], 1700.0], ['partial repair probe 1', ['P', 80.0, 95, 3.4, 10, 100], 19400.0], ['partial repair probe 2', ['P', 80.0, 105, 0.5, 1, 10], 165.0], ['normal control 1', ['C', 120.0, 105, 3.4, 2, 100], 5480.0], ['normal control 2', ['C', 80.0, 95, 8.0, 10, 10], 1600.0], ['normal control 3', ['C', 100.0, 90, 0.5, 10, 100], 20500.0], ['normal control 4', ['P', 120.0, 100, 15.1, 10, 10], 2510.0]]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"b18272baced6de3a7bb6376d50af91a679800999f02fc423cb96ed11413b20a5","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(kind, underlying, strike, premium, contracts, multiplier):\n    S = Fraction(str(underlying))\n    K = Fraction(str(strike))\n    P = Fraction(str(premium))\n    otm = max(K - S, 0) if kind == 'C' else max(S - K, 0)\n    floor_base = S if kind == 'C' else K\n    req = P + max(S * Fraction(20, 100) - otm, floor_base * Fraction(10, 100))\n    return float(round(req * multiplier * contracts, 2))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression premium inclusion 1', ['P', 120.0, 95, 3.4, 1, 100], 1290.0], ['regression premium inclusion 2', ['C', 80.0, 90, 0.5, 2, 10], 170.0], ['partial repair probe 1', ['P', 104.25, 110, 3.4, 1, 100], 2425.0], ['partial repair probe 2', ['P', 100.0, 95, 3.4, 1, 10], 184.0], ['normal control 1', ['P', 80.0, 90, 8.0, 1, 10], 240.0], ['normal control 2', ['P', 80.0, 105, 15.1, 2, 10], 622.0], ['normal control 3', ['P', 100.0, 100, 15.1, 1, 100], 3510.0], ['normal control 4', ['C', 100.0, 110, 1.25, 1, 100], 1125.0]], [['regression premium inclusion 1', ['P', 120.0, 95, 1.25, 1, 100], 1075.0], ['regression premium inclusion 2', ['C', 92.5, 110, 0.5, 10, 100], 9750.0], ['partial repair probe 1', ['P', 80.0, 95, 1.25, 1, 100], 1725.0], ['partial repair probe 2', ['P', 92.5, 105, 8.0, 1, 10], 265.0], ['normal control 1', ['C', 100.0, 95, 0.5, 10, 10], 2050.0], ['normal control 2', ['C', 100.0, 110, 1.25, 2, 100], 2250.0], ['normal control 3', ['C', 100.0, 110, 15.1, 1, 10], 251.0], ['normal control 4', ['P', 120.0, 95, 0.5, 2, 100], 2000.0]], [['regression premium inclusion 1', ['P', 120.0, 95, 3.4, 1, 100], 1290.0], ['regression premium inclusion 2', ['P', 120.0, 95, 1.25, 10, 10], 1075.0], ['partial repair probe 1', ['C', 92.5, 90, 3.4, 10, 100], 21900.0], ['partial repair probe 2', ['P', 80.0, 95, 8.0, 10, 10], 2400.0], ['normal control 1', ['C', 92.5, 95, 8.0, 2, 10], 480.0], ['normal control 2', ['C', 104.25, 105, 1.25, 1, 10], 213.5], ['normal control 3', ['P', 92.5, 95, 1.25, 10, 100], 19750.0], ['normal control 4', ['C', 80.0, 95, 3.4, 1, 100], 1140.0]], [['regression premium inclusion 1', ['C', 80.0, 90, 15.1, 2, 10], 462.0], ['regression premium inclusion 2', ['P', 120.0, 105, 1.25, 10, 10], 1175.0], ['partial repair probe 1', ['P', 100.0, 95, 3.4, 1, 10], 184.0], ['partial repair probe 2', ['P', 100.0, 100, 1.25, 2, 10], 425.0], ['normal control 1', ['C', 80.0, 100, 1.25, 1, 10], 92.5], ['normal control 2', ['P', 120.0, 95, 0.5, 2, 10], 200.0], ['normal control 3', ['P', 80.0, 100, 15.1, 2, 10], 622.0], ['normal control 4', ['C', 80.0, 105, 0.5, 2, 100], 1700.0]], [['regression premium inclusion 1', ['C', 80.0, 100, 15.1, 2, 100], 4620.0], ['regression premium inclusion 2', ['P', 104.25, 90, 8.0, 1, 100], 1700.0], ['partial repair probe 1', ['P', 80.0, 95, 3.4, 10, 100], 19400.0], ['partial repair probe 2', ['P', 80.0, 105, 0.5, 1, 10], 165.0], ['normal control 1', ['C', 120.0, 105, 3.4, 2, 100], 5480.0], ['normal control 2', ['C', 80.0, 95, 8.0, 10, 10], 1600.0], ['normal control 3', ['C', 100.0, 90, 0.5, 10, 100], 20500.0], ['normal control 4', ['P', 120.0, 100, 15.1, 10, 10], 2510.0]]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"A deterministic toy contract stated explicitly in the contract field; no claim of conformance to any exchange or clearing rulebook. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-options_payoff_and_settlement-naked-short-margin-premium-inclusion","generated_at":"2026-09-29T14:46:57.056578+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Option expiry, exercise and settlement engines move cash and shares; a wrong branch misstates obligations.","repair":"Add the premium outside the max().","root_cause":"The premium is placed inside the first argument of max().","sha256":"ec65fec9a174c3a842e7253dd51e70a49ee0e44d79577322843c1fd21b2f1520","title":"Uncovered short option margin requirement: premium is only part of the percentage branch · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":45.619,"exit_code":1,"observations":[{"actual":950.0,"check":"regression premium inclusion 1","expected":1290.0,"passed":false},{"actual":160.0,"check":"regression premium inclusion 2","expected":170.0,"passed":false},{"actual":2085.0,"check":"partial repair probe 1","expected":2425.0,"passed":false},{"actual":150.0,"check":"partial repair probe 2","expected":184.0,"passed":false},{"actual":160.0,"check":"normal control 1","expected":240.0,"passed":false},{"actual":320.0,"check":"normal control 2","expected":622.0,"passed":false},{"actual":2000.0,"check":"normal control 3","expected":3510.0,"passed":false},{"actual":1000.0,"check":"normal control 4","expected":1125.0,"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression premium inclusion 1\", \"actual\": 950.0, \"expected\": 1290.0, \"passed\": false}, {\"check\": \"regression premium inclusion 2\", \"actual\": 160.0, \"expected\": 170.0, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 2085.0, \"expected\": 2425.0, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 150.0, \"expected\": 184.0, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": 160.0, \"expected\": 240.0, \"passed\": false}, {\"check\": \"normal control 2\", \"actual\": 320.0, \"expected\": 622.0, \"passed\": false}, {\"check\": \"normal control 3\", \"actual\": 2000.0, \"expected\": 3510.0, \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": 1000.0, \"expected\": 1125.0, \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":45.321,"exit_code":1,"observations":[{"actual":950.0,"check":"regression premium inclusion 1","expected":1290.0,"passed":false},{"actual":160.0,"check":"regression premium inclusion 2","expected":170.0,"passed":false},{"actual":2425.0,"check":"partial repair probe 1","expected":2425.0,"passed":true},{"actual":184.0,"check":"partial repair probe 2","expected":184.0,"passed":true},{"actual":240.0,"check":"normal control 1","expected":240.0,"passed":true},{"actual":622.0,"check":"normal control 2","expected":622.0,"passed":true},{"actual":3510.0,"check":"normal control 3","expected":3510.0,"passed":true},{"actual":1125.0,"check":"normal control 4","expected":1125.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression premium inclusion 1\", \"actual\": 950.0, \"expected\": 1290.0, \"passed\": false}, {\"check\": \"regression premium inclusion 2\", \"actual\": 160.0, \"expected\": 170.0, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 2425.0, \"expected\": 2425.0, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 184.0, \"expected\": 184.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 240.0, \"expected\": 240.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 622.0, \"expected\": 622.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 3510.0, \"expected\": 3510.0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 1125.0, \"expected\": 1125.0, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":51.164,"exit_code":0,"observations":[{"actual":1290.0,"check":"regression premium inclusion 1","expected":1290.0,"passed":true},{"actual":170.0,"check":"regression premium inclusion 2","expected":170.0,"passed":true},{"actual":2425.0,"check":"partial repair probe 1","expected":2425.0,"passed":true},{"actual":184.0,"check":"partial repair probe 2","expected":184.0,"passed":true},{"actual":240.0,"check":"normal control 1","expected":240.0,"passed":true},{"actual":622.0,"check":"normal control 2","expected":622.0,"passed":true},{"actual":3510.0,"check":"normal control 3","expected":3510.0,"passed":true},{"actual":1125.0,"check":"normal control 4","expected":1125.0,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression premium inclusion 1\", \"actual\": 1290.0, \"expected\": 1290.0, \"passed\": true}, {\"check\": \"regression premium inclusion 2\", \"actual\": 170.0, \"expected\": 170.0, \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": 2425.0, \"expected\": 2425.0, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 184.0, \"expected\": 184.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 240.0, \"expected\": 240.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 622.0, \"expected\": 622.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 3510.0, \"expected\": 3510.0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 1125.0, \"expected\": 1125.0, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}