{"abstract":"Far out-of-the-money options fall below the minimum requirement.","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":"Halving the OTM reduction still leaves the minimum comparison unchanged in form.","family":"w2-options_payoff_and_settlement-naked-short-margin-otm-reduction-placement","id":"FA-61626","implementations":{"attempt":{"sha256":"70b63bb0042b2a8921eeb99480927344bf0dae730168309e8406b1e5c6a0e1f2","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 / 2, 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 otm reduction placement 1', ['C', 80.0, 110, 8.0, 10, 100], 16000.0], ['regression otm reduction placement 2', ['P', 120.0, 100, 0.5, 2, 100], 2100.0], ['partial repair probe 1', ['P', 100.0, 90, 15.1, 1, 10], 251.0], ['partial repair probe 2', ['P', 104.25, 100, 15.1, 2, 100], 6340.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 100.0, 95, 0.5, 10, 10], 2050.0], ['normal control 2', ['C', 104.25, 90, 3.4, 10, 10], 2425.0]], [['regression otm reduction placement 1', ['P', 104.25, 90, 0.5, 2, 10], 190.0], ['regression otm reduction placement 2', ['P', 120.0, 90, 0.5, 2, 100], 1900.0], ['partial repair probe 1', ['C', 100.0, 110, 1.25, 2, 100], 2250.0], ['partial repair probe 2', ['P', 92.5, 90, 8.0, 2, 100], 4800.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 92.5, 90, 1.25, 10, 100], 19750.0], ['normal control 2', ['P', 100.0, 105, 8.0, 10, 10], 2800.0]], [['regression otm reduction placement 1', ['C', 92.5, 110, 1.25, 10, 100], 10500.0], ['regression otm reduction placement 2', ['P', 104.25, 90, 0.5, 1, 10], 95.0], ['partial repair probe 1', ['P', 104.25, 100, 8.0, 10, 100], 24600.0], ['partial repair probe 2', ['C', 104.25, 105, 1.25, 10, 10], 2135.0], ['boundary control 1', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['boundary control 2', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['normal control 1', ['C', 92.5, 90, 15.1, 10, 100], 33600.0], ['normal control 2', ['P', 80.0, 95, 0.5, 10, 10], 1650.0]], [['regression otm reduction placement 1', ['P', 104.25, 90, 3.4, 1, 100], 1240.0], ['regression otm reduction placement 2', ['C', 80.0, 105, 3.4, 2, 100], 2280.0], ['partial repair probe 1', ['P', 104.25, 95, 3.4, 10, 100], 15000.0], ['partial repair probe 2', ['P', 92.5, 90, 1.25, 2, 100], 3450.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['P', 80.0, 100, 8.0, 2, 100], 4800.0], ['normal control 2', ['P', 92.5, 100, 1.25, 1, 100], 1975.0]], [['regression otm reduction placement 1', ['C', 80.0, 95, 1.25, 10, 100], 9250.0], ['regression otm reduction placement 2', ['C', 80.0, 95, 0.5, 1, 10], 85.0], ['partial repair probe 1', ['P', 100.0, 95, 0.5, 10, 100], 15500.0], ['partial repair probe 2', ['P', 104.25, 95, 8.0, 2, 100], 3920.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 120.0, 110, 0.5, 10, 100], 24500.0], ['normal control 2', ['P', 92.5, 110, 1.25, 2, 100], 3950.0]]]\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":"2dcd1625dcc61240527f39bd8722e9fc785223a6dc48214f5b2db15ff8c5a5e7","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), floor_base * Fraction(10, 100)) - otm\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 otm reduction placement 1', ['C', 80.0, 110, 8.0, 10, 100], 16000.0], ['regression otm reduction placement 2', ['P', 120.0, 100, 0.5, 2, 100], 2100.0], ['partial repair probe 1', ['P', 100.0, 90, 15.1, 1, 10], 251.0], ['partial repair probe 2', ['P', 104.25, 100, 15.1, 2, 100], 6340.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 100.0, 95, 0.5, 10, 10], 2050.0], ['normal control 2', ['C', 104.25, 90, 3.4, 10, 10], 2425.0]], [['regression otm reduction placement 1', ['P', 104.25, 90, 0.5, 2, 10], 190.0], ['regression otm reduction placement 2', ['P', 120.0, 90, 0.5, 2, 100], 1900.0], ['partial repair probe 1', ['C', 100.0, 110, 1.25, 2, 100], 2250.0], ['partial repair probe 2', ['P', 92.5, 90, 8.0, 2, 100], 4800.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 92.5, 90, 1.25, 10, 100], 19750.0], ['normal control 2', ['P', 100.0, 105, 8.0, 10, 10], 2800.0]], [['regression otm reduction placement 1', ['C', 92.5, 110, 1.25, 10, 100], 10500.0], ['regression otm reduction placement 2', ['P', 104.25, 90, 0.5, 1, 10], 95.0], ['partial repair probe 1', ['P', 104.25, 100, 8.0, 10, 100], 24600.0], ['partial repair probe 2', ['C', 104.25, 105, 1.25, 10, 10], 2135.0], ['boundary control 1', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['boundary control 2', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['normal control 1', ['C', 92.5, 90, 15.1, 10, 100], 33600.0], ['normal control 2', ['P', 80.0, 95, 0.5, 10, 10], 1650.0]], [['regression otm reduction placement 1', ['P', 104.25, 90, 3.4, 1, 100], 1240.0], ['regression otm reduction placement 2', ['C', 80.0, 105, 3.4, 2, 100], 2280.0], ['partial repair probe 1', ['P', 104.25, 95, 3.4, 10, 100], 15000.0], ['partial repair probe 2', ['P', 92.5, 90, 1.25, 2, 100], 3450.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['P', 80.0, 100, 8.0, 2, 100], 4800.0], ['normal control 2', ['P', 92.5, 100, 1.25, 1, 100], 1975.0]], [['regression otm reduction placement 1', ['C', 80.0, 95, 1.25, 10, 100], 9250.0], ['regression otm reduction placement 2', ['C', 80.0, 95, 0.5, 1, 10], 85.0], ['partial repair probe 1', ['P', 100.0, 95, 0.5, 10, 100], 15500.0], ['partial repair probe 2', ['P', 104.25, 95, 8.0, 2, 100], 3920.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 120.0, 110, 0.5, 10, 100], 24500.0], ['normal control 2', ['P', 92.5, 110, 1.25, 2, 100], 3950.0]]]\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":"08ab6805f9a42e1d574509cecb794c772754a82564a0c657aee010d2dac39eb5","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 otm reduction placement 1', ['C', 80.0, 110, 8.0, 10, 100], 16000.0], ['regression otm reduction placement 2', ['P', 120.0, 100, 0.5, 2, 100], 2100.0], ['partial repair probe 1', ['P', 100.0, 90, 15.1, 1, 10], 251.0], ['partial repair probe 2', ['P', 104.25, 100, 15.1, 2, 100], 6340.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 100.0, 95, 0.5, 10, 10], 2050.0], ['normal control 2', ['C', 104.25, 90, 3.4, 10, 10], 2425.0]], [['regression otm reduction placement 1', ['P', 104.25, 90, 0.5, 2, 10], 190.0], ['regression otm reduction placement 2', ['P', 120.0, 90, 0.5, 2, 100], 1900.0], ['partial repair probe 1', ['C', 100.0, 110, 1.25, 2, 100], 2250.0], ['partial repair probe 2', ['P', 92.5, 90, 8.0, 2, 100], 4800.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 92.5, 90, 1.25, 10, 100], 19750.0], ['normal control 2', ['P', 100.0, 105, 8.0, 10, 10], 2800.0]], [['regression otm reduction placement 1', ['C', 92.5, 110, 1.25, 10, 100], 10500.0], ['regression otm reduction placement 2', ['P', 104.25, 90, 0.5, 1, 10], 95.0], ['partial repair probe 1', ['P', 104.25, 100, 8.0, 10, 100], 24600.0], ['partial repair probe 2', ['C', 104.25, 105, 1.25, 10, 10], 2135.0], ['boundary control 1', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['boundary control 2', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['normal control 1', ['C', 92.5, 90, 15.1, 10, 100], 33600.0], ['normal control 2', ['P', 80.0, 95, 0.5, 10, 10], 1650.0]], [['regression otm reduction placement 1', ['P', 104.25, 90, 3.4, 1, 100], 1240.0], ['regression otm reduction placement 2', ['C', 80.0, 105, 3.4, 2, 100], 2280.0], ['partial repair probe 1', ['P', 104.25, 95, 3.4, 10, 100], 15000.0], ['partial repair probe 2', ['P', 92.5, 90, 1.25, 2, 100], 3450.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['P', 80.0, 100, 8.0, 2, 100], 4800.0], ['normal control 2', ['P', 92.5, 100, 1.25, 1, 100], 1975.0]], [['regression otm reduction placement 1', ['C', 80.0, 95, 1.25, 10, 100], 9250.0], ['regression otm reduction placement 2', ['C', 80.0, 95, 0.5, 1, 10], 85.0], ['partial repair probe 1', ['P', 100.0, 95, 0.5, 10, 100], 15500.0], ['partial repair probe 2', ['P', 104.25, 95, 8.0, 2, 100], 3920.0], ['boundary control 1', ['C', 100.0, 100, 2.0, 1, 100], 2200.0], ['boundary control 2', ['P', 80.0, 100, 20.5, 1, 100], 3650.0], ['normal control 1', ['C', 120.0, 110, 0.5, 10, 100], 24500.0], ['normal control 2', ['P', 92.5, 110, 1.25, 2, 100], 3950.0]]]\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-otm-reduction-placement","generated_at":"2026-09-29T14:46:57.041314+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":"Subtract OTM inside the first branch before comparing with the minimum.","root_cause":"The OTM amount is subtracted outside the max() that enforces the minimum.","sha256":"8eb3eafdf17b32a37998e3e15ea1239ffe6c037b6b53ec8f193c82d8a6ae30e2","title":"Uncovered short option margin requirement: the OTM reduction is subtracted after the minimum test · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":44.792,"exit_code":1,"observations":[{"actual":16000.0,"check":"regression otm reduction placement 1","expected":16000.0,"passed":true},{"actual":2900.0,"check":"regression otm reduction placement 2","expected":2100.0,"passed":false},{"actual":301.0,"check":"partial repair probe 1","expected":251.0,"passed":false},{"actual":6765.0,"check":"partial repair probe 2","expected":6340.0,"passed":false},{"actual":2200.0,"check":"boundary control 1","expected":2200.0,"passed":true},{"actual":3650.0,"check":"boundary control 2","expected":3650.0,"passed":true},{"actual":2050.0,"check":"normal control 1","expected":2050.0,"passed":true},{"actual":2425.0,"check":"normal control 2","expected":2425.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression otm reduction placement 1\", \"actual\": 16000.0, \"expected\": 16000.0, \"passed\": true}, {\"check\": \"regression otm reduction placement 2\", \"actual\": 2900.0, \"expected\": 2100.0, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 301.0, \"expected\": 251.0, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 6765.0, \"expected\": 6340.0, \"passed\": false}, {\"check\": \"boundary control 1\", \"actual\": 2200.0, \"expected\": 2200.0, \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": 3650.0, \"expected\": 3650.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 2050.0, \"expected\": 2050.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 2425.0, \"expected\": 2425.0, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":40.762,"exit_code":1,"observations":[{"actual":-6000.0,"check":"regression otm reduction placement 1","expected":16000.0,"passed":false},{"actual":900.0,"check":"regression otm reduction placement 2","expected":2100.0,"passed":false},{"actual":251.0,"check":"partial repair probe 1","expected":251.0,"passed":true},{"actual":6340.0,"check":"partial repair probe 2","expected":6340.0,"passed":true},{"actual":2200.0,"check":"boundary control 1","expected":2200.0,"passed":true},{"actual":3650.0,"check":"boundary control 2","expected":3650.0,"passed":true},{"actual":2050.0,"check":"normal control 1","expected":2050.0,"passed":true},{"actual":2425.0,"check":"normal control 2","expected":2425.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression otm reduction placement 1\", \"actual\": -6000.0, \"expected\": 16000.0, \"passed\": false}, {\"check\": \"regression otm reduction placement 2\", \"actual\": 900.0, \"expected\": 2100.0, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 251.0, \"expected\": 251.0, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 6340.0, \"expected\": 6340.0, \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": 2200.0, \"expected\": 2200.0, \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": 3650.0, \"expected\": 3650.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 2050.0, \"expected\": 2050.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 2425.0, \"expected\": 2425.0, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":46.237,"exit_code":0,"observations":[{"actual":16000.0,"check":"regression otm reduction placement 1","expected":16000.0,"passed":true},{"actual":2100.0,"check":"regression otm reduction placement 2","expected":2100.0,"passed":true},{"actual":251.0,"check":"partial repair probe 1","expected":251.0,"passed":true},{"actual":6340.0,"check":"partial repair probe 2","expected":6340.0,"passed":true},{"actual":2200.0,"check":"boundary control 1","expected":2200.0,"passed":true},{"actual":3650.0,"check":"boundary control 2","expected":3650.0,"passed":true},{"actual":2050.0,"check":"normal control 1","expected":2050.0,"passed":true},{"actual":2425.0,"check":"normal control 2","expected":2425.0,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression otm reduction placement 1\", \"actual\": 16000.0, \"expected\": 16000.0, \"passed\": true}, {\"check\": \"regression otm reduction placement 2\", \"actual\": 2100.0, \"expected\": 2100.0, \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": 251.0, \"expected\": 251.0, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 6340.0, \"expected\": 6340.0, \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": 2200.0, \"expected\": 2200.0, \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": 3650.0, \"expected\": 3650.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 2050.0, \"expected\": 2050.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 2425.0, \"expected\": 2425.0, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}