FA-61406 / Options payoff and settlement / Open access
Contract adjustment for splits and special dividends: ordinary dividends also reduce the strike · case 01
Regular dividends trigger contract adjustments.
ROOT CAUSE
The dividend branch accepts ordinary_div as well as special_div.
VERIFIED REPAIR
Adjust only for special dividends.
Unsuccessful approach: Treating every non-split action as a dividend also adjusts ordinary dividends.
Case contract
Inputs strike, contracts, deliverable, action and value. split [new, old]: if new is a multiple of old (ratio r), strike becomes strike/r rounded half-up to cents and contracts become contracts*r; otherwise the deliverable becomes floor(deliverable*new/old) with strike and contracts unchanged. special_div of at least 0.125 per share reduces the strike by the amount (rounded half-up to cents). Other actions, including ordinary_div, change nothing. Return [strike, contracts, deliverable].
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(strike, contracts, deliverable, action, value):
k = round(strike * 100)
if action == 'split':
new, old = value
if new % old == 0:
r = new // old
k = (2 * k + r) // (2 * r)
contracts = contracts * r
else:
deliverable = deliverable * new // old
elif action in ('special_div', 'ordinary_div'):
amt = round(value * 1000)
if amt >= 125:
k = (k * 10 - amt + 5) // 10
return [k / 100, contracts, deliverable]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression ordinary dividend exclusion 1', [12.5, 1, 100, 'ordinary_div', 0.126], [12.5, 1, 100]], ['regression ordinary dividend exclusion 2', [25.25, 3, 150, 'ordinary_div', 0.5], [25.25, 3, 150]], ['partial repair probe 1', [150.05, 1, 150, 'merger', 1.25], [150.05, 1, 150]], ['partial repair probe 2', [87.75, 3, 100, 'merger', 0.125], [87.75, 3, 100]], ['boundary control 1', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['boundary control 2', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['normal control 1', [87.75, 3, 100, 'split', [6, 3]], [43.88, 6, 100]], ['normal control 2', [150.05, 1, 100, 'split', [3, 2]], [150.05, 1, 150]]], [['regression ordinary dividend exclusion 1', [47.5, 10, 100, 'ordinary_div', 2.375], [47.5, 10, 100]], ['regression ordinary dividend exclusion 2', [47.5, 10, 150, 'ordinary_div', 1.25], [47.5, 10, 150]], ['partial repair probe 1', [101.01, 10, 100, 'merger', 2.375], [101.01, 10, 100]], ['partial repair probe 2', [150.05, 10, 100, 'merger', 2.375], [150.05, 10, 100]], ['boundary control 1', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['boundary control 2', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['normal control 1', [12.5, 3, 100, 'special_div', 0.1], [12.5, 3, 100]], ['normal control 2', [25.25, 10, 150, 'special_div', 0.125], [25.13, 10, 150]]], [['regression ordinary dividend exclusion 1', [33.33, 3, 100, 'ordinary_div', 0.5], [33.33, 3, 100]], ['regression ordinary dividend exclusion 2', [150.05, 3, 150, 'ordinary_div', 2.375], [150.05, 3, 150]], ['partial repair probe 1', [87.75, 3, 150, 'merger', 1.25], [87.75, 3, 150]], ['partial repair probe 2', [33.33, 1, 150, 'merger', 0.5], [33.33, 1, 150]], ['boundary control 1', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['boundary control 2', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['normal control 1', [40, 3, 100, 'split', [1, 2]], [40.0, 3, 50]], ['normal control 2', [40, 3, 100, 'special_div', 2.375], [37.63, 3, 100]]], [['regression ordinary dividend exclusion 1', [25.25, 3, 150, 'ordinary_div', 1.25], [25.25, 3, 150]], ['regression ordinary dividend exclusion 2', [40, 1, 100, 'ordinary_div', 0.5], [40.0, 1, 100]], ['partial repair probe 1', [40, 1, 100, 'merger', 2.375], [40.0, 1, 100]], ['partial repair probe 2', [12.5, 1, 150, 'merger', 1.25], [12.5, 1, 150]], ['boundary control 1', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['boundary control 2', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['normal control 1', [87.75, 1, 100, 'split', [4, 2]], [43.88, 2, 100]], ['normal control 2', [150.05, 10, 150, 'split', [3, 2]], [150.05, 10, 225]]], [['regression ordinary dividend exclusion 1', [12.5, 10, 100, 'ordinary_div', 0.125], [12.5, 10, 100]], ['regression ordinary dividend exclusion 2', [47.5, 3, 150, 'ordinary_div', 0.126], [47.5, 3, 150]], ['partial repair probe 1', [150.05, 10, 100, 'merger', 0.5], [150.05, 10, 100]], ['partial repair probe 2', [87.75, 10, 150, 'merger', 1.25], [87.75, 10, 150]], ['boundary control 1', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['boundary control 2', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['normal control 1', [33.33, 1, 150, 'special_div', 0.124], [33.33, 1, 150]], ['normal control 2', [47.5, 1, 100, 'special_div', 0.125], [47.38, 1, 100]]]]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression ordinary dividend exclusion 1 | [12.37, 1, 100] | [12.5, 1, 100] | Failed |
| regression ordinary dividend exclusion 2 | [24.75, 3, 150] | [25.25, 3, 150] | Failed |
| partial repair probe 1 | [150.05, 1, 150] | [150.05, 1, 150] | Passed |
| partial repair probe 2 | [87.75, 3, 100] | [87.75, 3, 100] | Passed |
| boundary control 1 | [40.0, 1, 150] | [40.0, 1, 150] | Passed |
| boundary control 2 | [12.63, 2, 100] | [12.63, 2, 100] | Passed |
| normal control 1 | [43.88, 6, 100] | [43.88, 6, 100] | Passed |
| normal control 2 | [150.05, 1, 150] | [150.05, 1, 150] | Passed |
SHA-256 / b551a4c481643493560410004066c7c2e2de1ed5f17ed78a088e2be4648e0738
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(strike, contracts, deliverable, action, value):
k = round(strike * 100)
if action == 'split':
new, old = value
if new % old == 0:
r = new // old
k = (2 * k + r) // (2 * r)
contracts = contracts * r
else:
deliverable = deliverable * new // old
elif action != 'split':
amt = round(value * 1000)
if amt >= 125:
k = (k * 10 - amt + 5) // 10
return [k / 100, contracts, deliverable]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression ordinary dividend exclusion 1', [12.5, 1, 100, 'ordinary_div', 0.126], [12.5, 1, 100]], ['regression ordinary dividend exclusion 2', [25.25, 3, 150, 'ordinary_div', 0.5], [25.25, 3, 150]], ['partial repair probe 1', [150.05, 1, 150, 'merger', 1.25], [150.05, 1, 150]], ['partial repair probe 2', [87.75, 3, 100, 'merger', 0.125], [87.75, 3, 100]], ['boundary control 1', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['boundary control 2', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['normal control 1', [87.75, 3, 100, 'split', [6, 3]], [43.88, 6, 100]], ['normal control 2', [150.05, 1, 100, 'split', [3, 2]], [150.05, 1, 150]]], [['regression ordinary dividend exclusion 1', [47.5, 10, 100, 'ordinary_div', 2.375], [47.5, 10, 100]], ['regression ordinary dividend exclusion 2', [47.5, 10, 150, 'ordinary_div', 1.25], [47.5, 10, 150]], ['partial repair probe 1', [101.01, 10, 100, 'merger', 2.375], [101.01, 10, 100]], ['partial repair probe 2', [150.05, 10, 100, 'merger', 2.375], [150.05, 10, 100]], ['boundary control 1', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['boundary control 2', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['normal control 1', [12.5, 3, 100, 'special_div', 0.1], [12.5, 3, 100]], ['normal control 2', [25.25, 10, 150, 'special_div', 0.125], [25.13, 10, 150]]], [['regression ordinary dividend exclusion 1', [33.33, 3, 100, 'ordinary_div', 0.5], [33.33, 3, 100]], ['regression ordinary dividend exclusion 2', [150.05, 3, 150, 'ordinary_div', 2.375], [150.05, 3, 150]], ['partial repair probe 1', [87.75, 3, 150, 'merger', 1.25], [87.75, 3, 150]], ['partial repair probe 2', [33.33, 1, 150, 'merger', 0.5], [33.33, 1, 150]], ['boundary control 1', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['boundary control 2', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['normal control 1', [40, 3, 100, 'split', [1, 2]], [40.0, 3, 50]], ['normal control 2', [40, 3, 100, 'special_div', 2.375], [37.63, 3, 100]]], [['regression ordinary dividend exclusion 1', [25.25, 3, 150, 'ordinary_div', 1.25], [25.25, 3, 150]], ['regression ordinary dividend exclusion 2', [40, 1, 100, 'ordinary_div', 0.5], [40.0, 1, 100]], ['partial repair probe 1', [40, 1, 100, 'merger', 2.375], [40.0, 1, 100]], ['partial repair probe 2', [12.5, 1, 150, 'merger', 1.25], [12.5, 1, 150]], ['boundary control 1', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['boundary control 2', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['normal control 1', [87.75, 1, 100, 'split', [4, 2]], [43.88, 2, 100]], ['normal control 2', [150.05, 10, 150, 'split', [3, 2]], [150.05, 10, 225]]], [['regression ordinary dividend exclusion 1', [12.5, 10, 100, 'ordinary_div', 0.125], [12.5, 10, 100]], ['regression ordinary dividend exclusion 2', [47.5, 3, 150, 'ordinary_div', 0.126], [47.5, 3, 150]], ['partial repair probe 1', [150.05, 10, 100, 'merger', 0.5], [150.05, 10, 100]], ['partial repair probe 2', [87.75, 10, 150, 'merger', 1.25], [87.75, 10, 150]], ['boundary control 1', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['boundary control 2', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['normal control 1', [33.33, 1, 150, 'special_div', 0.124], [33.33, 1, 150]], ['normal control 2', [47.5, 1, 100, 'special_div', 0.125], [47.38, 1, 100]]]]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression ordinary dividend exclusion 1 | [12.37, 1, 100] | [12.5, 1, 100] | Failed |
| regression ordinary dividend exclusion 2 | [24.75, 3, 150] | [25.25, 3, 150] | Failed |
| partial repair probe 1 | [148.8, 1, 150] | [150.05, 1, 150] | Failed |
| partial repair probe 2 | [87.63, 3, 100] | [87.75, 3, 100] | Failed |
| boundary control 1 | [40.0, 1, 150] | [40.0, 1, 150] | Passed |
| boundary control 2 | [12.63, 2, 100] | [12.63, 2, 100] | Passed |
| normal control 1 | [43.88, 6, 100] | [43.88, 6, 100] | Passed |
| normal control 2 | [150.05, 1, 150] | [150.05, 1, 150] | Passed |
SHA-256 / 14237e4a01f3388a5aa99b16c90a3b448b6ffbd42e7ad5745c2467e18bb555d1
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(strike, contracts, deliverable, action, value):
k = round(strike * 100)
if action == 'split':
new, old = value
if new % old == 0:
r = new // old
k = (2 * k + r) // (2 * r)
contracts = contracts * r
else:
deliverable = deliverable * new // old
elif action == 'special_div':
amt = round(value * 1000)
if amt >= 125:
k = (k * 10 - amt + 5) // 10
return [k / 100, contracts, deliverable]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression ordinary dividend exclusion 1', [12.5, 1, 100, 'ordinary_div', 0.126], [12.5, 1, 100]], ['regression ordinary dividend exclusion 2', [25.25, 3, 150, 'ordinary_div', 0.5], [25.25, 3, 150]], ['partial repair probe 1', [150.05, 1, 150, 'merger', 1.25], [150.05, 1, 150]], ['partial repair probe 2', [87.75, 3, 100, 'merger', 0.125], [87.75, 3, 100]], ['boundary control 1', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['boundary control 2', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['normal control 1', [87.75, 3, 100, 'split', [6, 3]], [43.88, 6, 100]], ['normal control 2', [150.05, 1, 100, 'split', [3, 2]], [150.05, 1, 150]]], [['regression ordinary dividend exclusion 1', [47.5, 10, 100, 'ordinary_div', 2.375], [47.5, 10, 100]], ['regression ordinary dividend exclusion 2', [47.5, 10, 150, 'ordinary_div', 1.25], [47.5, 10, 150]], ['partial repair probe 1', [101.01, 10, 100, 'merger', 2.375], [101.01, 10, 100]], ['partial repair probe 2', [150.05, 10, 100, 'merger', 2.375], [150.05, 10, 100]], ['boundary control 1', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['boundary control 2', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['normal control 1', [12.5, 3, 100, 'special_div', 0.1], [12.5, 3, 100]], ['normal control 2', [25.25, 10, 150, 'special_div', 0.125], [25.13, 10, 150]]], [['regression ordinary dividend exclusion 1', [33.33, 3, 100, 'ordinary_div', 0.5], [33.33, 3, 100]], ['regression ordinary dividend exclusion 2', [150.05, 3, 150, 'ordinary_div', 2.375], [150.05, 3, 150]], ['partial repair probe 1', [87.75, 3, 150, 'merger', 1.25], [87.75, 3, 150]], ['partial repair probe 2', [33.33, 1, 150, 'merger', 0.5], [33.33, 1, 150]], ['boundary control 1', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['boundary control 2', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['normal control 1', [40, 3, 100, 'split', [1, 2]], [40.0, 3, 50]], ['normal control 2', [40, 3, 100, 'special_div', 2.375], [37.63, 3, 100]]], [['regression ordinary dividend exclusion 1', [25.25, 3, 150, 'ordinary_div', 1.25], [25.25, 3, 150]], ['regression ordinary dividend exclusion 2', [40, 1, 100, 'ordinary_div', 0.5], [40.0, 1, 100]], ['partial repair probe 1', [40, 1, 100, 'merger', 2.375], [40.0, 1, 100]], ['partial repair probe 2', [12.5, 1, 150, 'merger', 1.25], [12.5, 1, 150]], ['boundary control 1', [25.25, 1, 100, 'split', [2, 1]], [12.63, 2, 100]], ['boundary control 2', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['normal control 1', [87.75, 1, 100, 'split', [4, 2]], [43.88, 2, 100]], ['normal control 2', [150.05, 10, 150, 'split', [3, 2]], [150.05, 10, 225]]], [['regression ordinary dividend exclusion 1', [12.5, 10, 100, 'ordinary_div', 0.125], [12.5, 10, 100]], ['regression ordinary dividend exclusion 2', [47.5, 3, 150, 'ordinary_div', 0.126], [47.5, 3, 150]], ['partial repair probe 1', [150.05, 10, 100, 'merger', 0.5], [150.05, 10, 100]], ['partial repair probe 2', [87.75, 10, 150, 'merger', 1.25], [87.75, 10, 150]], ['boundary control 1', [40, 1, 100, 'split', [3, 2]], [40.0, 1, 150]], ['boundary control 2', [40, 1, 100, 'special_div', 0.125], [39.88, 1, 100]], ['normal control 1', [33.33, 1, 150, 'special_div', 0.124], [33.33, 1, 150]], ['normal control 2', [47.5, 1, 100, 'special_div', 0.125], [47.38, 1, 100]]]]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression ordinary dividend exclusion 1 | [12.5, 1, 100] | [12.5, 1, 100] | Passed |
| regression ordinary dividend exclusion 2 | [25.25, 3, 150] | [25.25, 3, 150] | Passed |
| partial repair probe 1 | [150.05, 1, 150] | [150.05, 1, 150] | Passed |
| partial repair probe 2 | [87.75, 3, 100] | [87.75, 3, 100] | Passed |
| boundary control 1 | [40.0, 1, 150] | [40.0, 1, 150] | Passed |
| boundary control 2 | [12.63, 2, 100] | [12.63, 2, 100] | Passed |
| normal control 1 | [43.88, 6, 100] | [43.88, 6, 100] | Passed |
| normal control 2 | [150.05, 1, 150] | [150.05, 1, 150] | Passed |
SHA-256 / 6ad57bc6c4be46c74769c892a98b48bf29cabbe02fc2a92b55635c706c41ffb6
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 2026-09-29T14:46:54.896419+00:00.
Case digest / e10e8cc5f90b4b155e9f6b4922bc6e80c81c970e90f993245d349c113a420a38