Dynamic Mean-Variance Optimisation Problems with Deterministic Information

Martin Schweizer, Danijel Zivoi and Mario Sikic
Additional contact information
Martin Schweizer: ETH Zurich and Swiss Finance Institute
Danijel Zivoi: ETH Zürich
Mario Sikic: University of Zurich

No 17-29, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We solve the problems of mean-variance hedging (MVH) and mean-variance portfolio selection (MVPS) under restricted information. We work in a setting where the underlying price process S is a semimartingale, but not adapted to the filtration G which models the information available for constructing trading strategies. We choose as G = Fdet the zero-information filtration and assume that S is a time-dependent affine transformation of a square-integrable martingale. This class of processes includes in particular arithmetic and exponential Lévy models with suitable integrability. We give explicit solutions to the MVH and MVPS problems in this setting, and we show for the Lévy case how they can be expressed in terms of the Lévy triplet.

Keywords: Mean-Variance Hedging; Mean-Variance Portfolio Selection; Restricted Information; Partial Information; Deterministic Strategies; Quadratic Optimisation Problems; Nancial Markets; Type (A) Semimartingales (search for similar items in EconPapers)
JEL-codes: C60 C61 G11 G13 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2017-10, Revised 2018-02
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3051199 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1729

Access Statistics for this paper

More papers in Swiss Finance Institute Research Paper Series from Swiss Finance Institute Contact information at EDIRC.
Bibliographic data for series maintained by Ridima Mittal ().