Pith Number
pith:ELQPQNJL
pith:2019:ELQPQNJLL7X7C7UJHVUJJEITC5
not attested
not anchored
not stored
refs pending
Improving Regression-based Event Study Analysis Using a Topological Machine-learning Method
arxiv:1905.06536 v1 · 2019-05-16 · econ.GN · q-fin.EC · q-fin.ST
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ELQPQNJLL7X7C7UJHVUJJEITC5}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
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4
Citations
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Replications
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Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-05-17T23:46:01.992736Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
22e0f8352b5feff17e893d689491131743d4e1c69fd8a53b15229514943a4111
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ELQPQNJLL7X7C7UJHVUJJEITC5 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 22e0f8352b5feff17e893d689491131743d4e1c69fd8a53b15229514943a4111
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "2184a211f37964d33d6a949947c5b47eac6769c66c7fafc9ed69d71a4df54a04",
"cross_cats_sorted": [
"q-fin.EC",
"q-fin.ST"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "econ.GN",
"submitted_at": "2019-05-16T05:44:07Z",
"title_canon_sha256": "4e425f34adc83018b2d626aca3237738c16ff0ea4ec01acfd169f062e7eac827"
},
"schema_version": "1.0",
"source": {
"id": "1905.06536",
"kind": "arxiv",
"version": 1
}
}