pith:UYRLBPFP
Stochastic integration with respect to a L\'evy basis
Decoupling inequalities for tangent sequences reduce stochastic integration with respect to a Lévy basis to deterministic integration of infinitely divisible measures.
arxiv:2605.16072 v1 · 2026-05-15 · math.PR
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Claims
We develop a stochastic integration theory for predictable integrands with respect to a Lévy basis. Our approach is based on decoupling inequalities for tangent sequences and reduces the construction of the stochastic integral essentially to the deterministic integration theory for infinitely divisible random measures developed by Rajput and Rosiński.
The construction relies on the applicability of decoupling inequalities for tangent sequences to the predictable integrands and the Lévy basis under consideration, as stated in the abstract's description of the approach.
Develops stochastic integration for predictable processes w.r.t. Lévy basis via decoupling inequalities, reducing to Rajput-Rosiński deterministic theory, with characterization via semimartingale characteristics and Musielak-Orlicz structure.
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Receipt and verification
| First computed | 2026-05-20T00:01:51.454150Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
a622b0bcaf921d78eaccc930b8c4674d982495dbffee90e9e98c248b83af54c8
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/UYRLBPFPSIOXR2WMZEYLRRDHJW \
| 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: a622b0bcaf921d78eaccc930b8c4674d982495dbffee90e9e98c248b83af54c8
Canonical record JSON
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