Portfolio optimization using asymmetry robust mean absolute deviation model

Ping Li, Yingwei Han and Yong Xia

Finance Research Letters, 2016, vol. 18, issue C, 353-362

Abstract: In this paper, we construct an asymmetry robust mean absolute deviation (ARMAD) model that takes the asymmetry distribution of returns into consideration. We test different robust strategies using the historical data of Chinese small cap stocks based on the growing and declining market, respectively. Computational experiments show that the ARMAD method can distinguish the high return stocks. Since there is short-run persistence of relative performance of the stocks, the portfolios constructed by the ARMAD model can provide investors with good guidance in the near future.

Keywords: Mean absolute deviation; Robust optimization; Forward and backward deviations; Asymmetry (search for similar items in EconPapers)
JEL-codes: D81 G11 G32 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612316301003
Full text for ScienceDirect subscribers only

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:eee:finlet:v:18:y:2016:i:c:p:353-362

DOI: 10.1016/j.frl.2016.05.014

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().