Portfolio optimization under shortfall risk constraint. (1st September 2016)
- Record Type:
- Journal Article
- Title:
- Portfolio optimization under shortfall risk constraint. (1st September 2016)
- Main Title:
- Portfolio optimization under shortfall risk constraint
- Authors:
- Janke, Oliver
Li, Qinghua - Abstract:
- Abstract : This paper solves a utility maximization problem under utility-based shortfall risk constraint, by proposing an approach using Lagrange multiplier and convex duality. Under mild conditions on the asymptotic elasticity of the utility function and the loss function, we find an optimal wealth process for the constrained problem and characterize the bi-dual relation between the respective value functions of the constrained problem and its dual. This approach applies to both complete and incomplete markets. Moreover, the extension to more complicated cases is illustrated by solving the problem with a consumption process added. Finally, we give an example of utility and loss functions in the Black–Scholes market where the solutions have explicit forms.
- Is Part Of:
- Optimization. Volume 65:Number 9(2016)
- Journal:
- Optimization
- Issue:
- Volume 65:Number 9(2016)
- Issue Display:
- Volume 65, Issue 9 (2016)
- Year:
- 2016
- Volume:
- 65
- Issue:
- 9
- Issue Sort Value:
- 2016-0065-0009-0000
- Page Start:
- 1733
- Page End:
- 1755
- Publication Date:
- 2016-09-01
- Subjects:
- Portfolio optimization -- utility-based shortfall risk -- convex duality -- Lagrange multiplier -- asymptotic elasticity -- optimal consumption
Mathematical optimization -- Periodicals
519.7 - Journal URLs:
- http://www.tandfonline.com/toc/gopt20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/02331934.2016.1173693 ↗
- Languages:
- English
- ISSNs:
- 0233-1934
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6275.100000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 751.xml