Model Uncertainty: A Reverse Approach

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Felix Benedikt Liebrich
  • Marco Maggis
  • Gregor Svindland

Externe Organisationen

  • University of Milano-Bicocca
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)1230-1269
Seitenumfang40
FachzeitschriftSIAM Journal on Financial Mathematics
Jahrgang13
Ausgabenummer3
Frühes Online-Datum22 Sept. 2022
PublikationsstatusVeröffentlicht - 2022

Abstract

In robust finance, Knightian uncertainty is often captured by sets of probability measures on the future states of the world. If these measures are nondominated, this usually comes at the cost of losing tractability, and advanced functional-analytic tools are often not available anymore. This tends to be mitigated by ad hoc assumptions that guarantee a certain degree of tractability, for instance concerning the aggregation of consistent random variables. The present paper instead investigates from a reverse perspective what implications the validity of certain functional-analytic tools has. In this vein, we categorise the Kreps-Yan property, robust variants of the Brannath-Schachermayer Bipolar Theorem and the Grothendieck Lemma, and uncertain volatility models. By doing so, we also uncover connections to robust statistics.

ASJC Scopus Sachgebiete

Zitieren

Model Uncertainty: A Reverse Approach. / Liebrich, Felix Benedikt; Maggis, Marco; Svindland, Gregor.
in: SIAM Journal on Financial Mathematics, Jahrgang 13, Nr. 3, 2022, S. 1230-1269.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Liebrich FB, Maggis M, Svindland G. Model Uncertainty: A Reverse Approach. SIAM Journal on Financial Mathematics. 2022;13(3):1230-1269. Epub 2022 Sep 22. doi: 10.48550/arXiv.2004.06636, 10.1137/21M1425463
Liebrich, Felix Benedikt ; Maggis, Marco ; Svindland, Gregor. / Model Uncertainty : A Reverse Approach. in: SIAM Journal on Financial Mathematics. 2022 ; Jahrgang 13, Nr. 3. S. 1230-1269.
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