A PDE approach to risk measures of derivatives
Tak Kuen Siu and
Hailiang Yang
Applied Mathematical Finance, 2000, vol. 7, issue 3, 211-228
Abstract:
This paper proposes a partial differential equation (PDE) approach to calculate coherent risk measures for portfolios of derivatives under the Black-Scholes economy. It enables us to define the risk measures in a dynamic way and to deal with American options in a relatively effective way. Our risk measure is based on the representation form of coherent risk measures. Through the use of some earlier results the PDE satisfied by the risk measures are derived. The PDE resembles the standard Black-Scholes type PDE which can be solved using standard techniques from the mathematical finance literature. Indeed, these results reveal that the PDE approach can provide practitioners with a more applicable and flexible way to implement coherent risk measures for derivatives in the context of the Black-Scholes model.
Keywords: Coherent Risk Measures American Options Physical Probability Measure Subjective Probability Measures Transaction Costs (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/13504860110045741 (text/html)
Access to full text is restricted to subscribers.
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:taf:apmtfi:v:7:y:2000:i:3:p:211-228
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAMF20
DOI: 10.1080/13504860110045741
Access Statistics for this article
Applied Mathematical Finance is currently edited by Professor Ben Hambly and Christoph Reisinger
More articles in Applied Mathematical Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().