Dynamic utility-based good deal bounds

Klöppel Susanne and Schweizer Martin

Statistics & Risk Modeling, 2007, vol. 25, issue 4, 285-309

Abstract: We introduce and study no-good-deal valuation bounds defined in terms of expected utility. A utility-based good deal is a payoff whose expected utility is too high in comparison to the utility of its price. Forbidding good deals induces, via duality, restrictions on pricing kernels and thereby gives tighter valuation bounds on payoffs than absence of arbitrage alone. Our approach extends earlier work by Černý (2003) in several directions: We give rigorous results for a general probability space instead of finite Ω; we systematically use duality results to provide a streamlined approach with simple arguments; we do all this rigorously for both static and dynamic situations; and we give a systematic comparison between local and global (conditional) pricing kernel restrictions for the temporally dynamic setting. For the dynamic case, we show in a Lévy framework that defining no-good-deal valuation measures by imposing local conditional restrictions on their instantaneous market prices of risk gives valuation bounds having very good dynamic properties as processes over time. We also show that global restrictions cannot yield such results in general.

Keywords: good deals; valuation bounds; pricing kernel restrictions; utility-based; duality; incomplete markets; dynamic properties; Lévy processes (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1524/stnd.2007.0905 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:strimo:v:25:y:2007:i:4/2007:p:25:n:3

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/strm/html

DOI: 10.1524/stnd.2007.0905

Access Statistics for this article

Statistics & Risk Modeling is currently edited by Robert Stelzer

More articles in Statistics & Risk Modeling from De Gruyter
Bibliographic data for series maintained by Peter Golla ().