An Asset Allocation Model and Its Solving Method
Zhang Qingye () and
Gao Yan ()
Additional contact information
Gao Yan: School of Management, University of Shanghai for Science and Technology, Shanghai, 200093, China
Journal of Systems Science and Information, 2017, vol. 5, issue 2, 163-175
Asset allocation is an important issue in finance, and both risk and return are its fundamental ingredients. Rather than the return, the measure of the risk is complicated and of controversy. In this paper, we propose an appropriate risk measure which is precisely a convex combination of mean semi-deviation and conditional value-at-risk. Based on this risk measure, investors can trade-off flexibly between the volatility and the loss to tackle the incurring risk by choosing different convex coefficients. As the presented risk measure contains nonsmooth term, the asset allocation model based on it is nonsmooth. To employ traditional gradient algorithms, we develop a uniform smooth approximation of the plus function and convert the model into a smooth one. Finally, an illustrative empirical study is given. The results indicate that investors can control risk efficiently by adjusting the convex coefficient and the confidence level simultaneously according to their perceptions. Moreover, the effectiveness of the smoothing function proposed in the paper is verified.
Keywords: portfolio optimization; risk measure; mean semi-deviation; conditional value-at-risk; non-smooth optimization (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
For access to full text, subscription to the journal or payment for the individual article is required.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:5:y:2017:i:2:p:163-175:n:5
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Systems Science and Information is currently edited by Shouyang Wang
More articles in Journal of Systems Science and Information from De Gruyter
Bibliographic data for series maintained by Peter Golla ().