Optimal and naive diversification in an emerging market: Evidence from China's A‐shares market
Cheng Yan and
Ji Yan
International Journal of Finance & Economics, 2021, vol. 26, issue 3, 3740-3758
Abstract:
This paper empirically investigates the out‐of‐sample performance of the 1/N naive rule and the Markowitz mean–variance strategies in the largest emerging market (i.e., China's A‐shares market) and provides three new findings. First, we show that some mean–variance optimization strategies can outperform the 1/N rule in China's A‐shares market, while minimum‐variance strategies cannot. Using certainty equivalent return (CER) instead of Sharpe ratios does not change our results qualitatively. Second, we find an obvious advantage of mean–variance optimization when N is large. Third, when transaction costs are taken into account, the profitability of the unconstrained mean–variance optimizations almost vanishes, while the profitability of the mean–variance optimizations with the short‐sale constraint remains. Our results are robust to using a shorter estimation window of about 60 months. These results provide support for the use of optimal diversification strategies in emerging markets.
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1002/ijfe.1984
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:wly:ijfiec:v:26:y:2021:i:3:p:3740-3758
Ordering information: This journal article can be ordered from
http://jws-edcv.wile ... PRINT_ISSN=1076-9307
Access Statistics for this article
International Journal of Finance & Economics is currently edited by Mark P. Taylor, Keith Cuthbertson and Michael P. Dooley
More articles in International Journal of Finance & Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().