FAILURE MAP
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FA-61781 / Options payoff and settlement / Open access

Early call exercise before an ex-dividend date: out-of-the-money calls can be exercised · case 01

Holders exercise worthless calls to capture a dividend they cannot receive profitably.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The intrinsic == 0 guard is missing.

THE FAILURE

The intrinsic == 0 guard is missing.

Unsuccessful approach: Guarding on negative intrinsic never triggers because intrinsic is floored at zero.

Case contract

Inputs call price, spot, strike, dividend and whether today is the last cum-dividend day. Exercise only on the last cum-dividend day, only if the call is in the money, and only if the dividend is strictly greater than the call's extrinsic value (price - intrinsic). Amounts compared exactly in cents. Return true/false.

Why this case matters

Option expiry, exercise and settlement engines move cash and shares; a wrong branch misstates obligations.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(call_price, S, K, dividend, last_cum_day):
    c = round(call_price * 100)
    intrinsic = max(round(S * 100) - round(K * 100), 0)
    if not last_cum_day:
        return False
    extrinsic = c - intrinsic
    return round(dividend * 100) > extrinsic
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression in-the-money guard 1', [0.25, 105.0, 110.0, 1.0, True], False], ['regression in-the-money guard 2', [1.0, 98.0, 110.0, 1.01, True], False], ['partial repair probe 1', [0.05, 98.0, 110.0, 0.060000000000000005, True], False], ['partial repair probe 2', [0.05, 98.0, 100.0, 0.25, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.5, True], False], ['boundary control 2', [10.5, 110.0, 100.0, 0.51, True], True], ['normal control 1', [1.0, 98.0, 100.0, 1.0, True], False], ['normal control 2', [1.5, 105.0, 110.0, 1.5, False], False]], [['regression in-the-money guard 1', [0.5, 100.0, 100.0, 0.51, True], False], ['regression in-the-money guard 2', [1.5, 98.0, 110.0, 1.51, True], False], ['partial repair probe 1', [0.05, 105.0, 110.0, 1.0, True], False], ['partial repair probe 2', [0.25, 100.0, 110.0, 1.0, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.51, True], True], ['boundary control 2', [10.5, 110.0, 100.0, 0.5, True], False], ['normal control 1', [1.5, 100.0, 110.0, 1.5, False], False], ['normal control 2', [10.5, 120.0, 110.0, 0.25, True], False]], [['regression in-the-money guard 1', [1.0, 98.0, 110.0, 1.01, True], False], ['regression in-the-money guard 2', [0.05, 100.0, 110.0, 0.25, True], False], ['partial repair probe 1', [1.0, 100.0, 100.0, 1.01, True], False], ['partial repair probe 2', [0.25, 100.0, 100.0, 0.26, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.5, True], False], ['boundary control 2', [10.5, 110.0, 100.0, 0.51, True], True], ['normal control 1', [1.0, 98.0, 100.0, 1.0, True], False], ['normal control 2', [5.05, 105.0, 100.0, 0.25, False], False]], [['regression in-the-money guard 1', [0.5, 98.0, 110.0, 1.0, True], False], ['regression in-the-money guard 2', [1.0, 100.0, 110.0, 1.01, True], False], ['partial repair probe 1', [0.05, 98.0, 100.0, 0.060000000000000005, True], False], ['partial repair probe 2', [1.0, 105.0, 110.0, 1.01, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.51, True], True], ['boundary control 2', [10.5, 110.0, 100.0, 0.5, True], False], ['normal control 1', [20.5, 120.0, 100.0, 0.25, False], False], ['normal control 2', [8.25, 98.0, 90.0, 0.25, False], False]], [['regression in-the-money guard 1', [0.5, 100.0, 110.0, 0.51, True], False], ['regression in-the-money guard 2', [1.0, 98.0, 100.0, 1.01, True], False], ['partial repair probe 1', [0.25, 98.0, 110.0, 0.26, True], False], ['partial repair probe 2', [0.5, 98.0, 100.0, 1.0, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.51, True], True], ['boundary control 2', [10.5, 110.0, 100.0, 0.5, True], False], ['normal control 1', [10.05, 120.0, 110.0, 0.05, False], False], ['normal control 2', [16.5, 105.0, 90.0, 1.0, True], False]]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression in-the-money guard 1TrueFalseFailed
regression in-the-money guard 2TrueFalseFailed
partial repair probe 1TrueFalseFailed
partial repair probe 2TrueFalseFailed
boundary control 1FalseFalsePassed
boundary control 2TrueTruePassed
normal control 1FalseFalsePassed
normal control 2FalseFalsePassed

SHA-256 / 8de42cbe4fcd2f643c8a24d6797686fc6ac70475aaefb60cd64903be04679cfa

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(call_price, S, K, dividend, last_cum_day):
    c = round(call_price * 100)
    intrinsic = max(round(S * 100) - round(K * 100), 0)
    if not last_cum_day or intrinsic < 0:
        return False
    extrinsic = c - intrinsic
    return round(dividend * 100) > extrinsic
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression in-the-money guard 1', [0.25, 105.0, 110.0, 1.0, True], False], ['regression in-the-money guard 2', [1.0, 98.0, 110.0, 1.01, True], False], ['partial repair probe 1', [0.05, 98.0, 110.0, 0.060000000000000005, True], False], ['partial repair probe 2', [0.05, 98.0, 100.0, 0.25, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.5, True], False], ['boundary control 2', [10.5, 110.0, 100.0, 0.51, True], True], ['normal control 1', [1.0, 98.0, 100.0, 1.0, True], False], ['normal control 2', [1.5, 105.0, 110.0, 1.5, False], False]], [['regression in-the-money guard 1', [0.5, 100.0, 100.0, 0.51, True], False], ['regression in-the-money guard 2', [1.5, 98.0, 110.0, 1.51, True], False], ['partial repair probe 1', [0.05, 105.0, 110.0, 1.0, True], False], ['partial repair probe 2', [0.25, 100.0, 110.0, 1.0, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.51, True], True], ['boundary control 2', [10.5, 110.0, 100.0, 0.5, True], False], ['normal control 1', [1.5, 100.0, 110.0, 1.5, False], False], ['normal control 2', [10.5, 120.0, 110.0, 0.25, True], False]], [['regression in-the-money guard 1', [1.0, 98.0, 110.0, 1.01, True], False], ['regression in-the-money guard 2', [0.05, 100.0, 110.0, 0.25, True], False], ['partial repair probe 1', [1.0, 100.0, 100.0, 1.01, True], False], ['partial repair probe 2', [0.25, 100.0, 100.0, 0.26, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.5, True], False], ['boundary control 2', [10.5, 110.0, 100.0, 0.51, True], True], ['normal control 1', [1.0, 98.0, 100.0, 1.0, True], False], ['normal control 2', [5.05, 105.0, 100.0, 0.25, False], False]], [['regression in-the-money guard 1', [0.5, 98.0, 110.0, 1.0, True], False], ['regression in-the-money guard 2', [1.0, 100.0, 110.0, 1.01, True], False], ['partial repair probe 1', [0.05, 98.0, 100.0, 0.060000000000000005, True], False], ['partial repair probe 2', [1.0, 105.0, 110.0, 1.01, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.51, True], True], ['boundary control 2', [10.5, 110.0, 100.0, 0.5, True], False], ['normal control 1', [20.5, 120.0, 100.0, 0.25, False], False], ['normal control 2', [8.25, 98.0, 90.0, 0.25, False], False]], [['regression in-the-money guard 1', [0.5, 100.0, 110.0, 0.51, True], False], ['regression in-the-money guard 2', [1.0, 98.0, 100.0, 1.01, True], False], ['partial repair probe 1', [0.25, 98.0, 110.0, 0.26, True], False], ['partial repair probe 2', [0.5, 98.0, 100.0, 1.0, True], False], ['boundary control 1', [10.5, 110.0, 100.0, 0.51, True], True], ['boundary control 2', [10.5, 110.0, 100.0, 0.5, True], False], ['normal control 1', [10.05, 120.0, 110.0, 0.05, False], False], ['normal control 2', [16.5, 105.0, 90.0, 1.0, True], False]]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression in-the-money guard 1TrueFalseFailed
regression in-the-money guard 2TrueFalseFailed
partial repair probe 1TrueFalseFailed
partial repair probe 2TrueFalseFailed
boundary control 1FalseFalsePassed
boundary control 2TrueTruePassed
normal control 1FalseFalsePassed
normal control 2FalseFalsePassed

SHA-256 / e9f43f6578d04fb8747731f9969642c76e0c770336139274888e883eeb4e68b0

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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Verification & scope

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.

Observations recorded using Python 3.12.14 at 2026-09-29T14:46:58.451127+00:00.

Case digest / 21a4c4c1afb507b6ca16ae984fa765590232eb7e1eb34fcfe9f4ece7e65a26d6