Author
Listed:
- Guillaume Leduc
(Department of Mathematics and Statistics, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates)
- Shyam Sanjeewa Nishantha Perera
(Centre for Mathematical Modeling, Department of Mathematics, University of Colombo, Colombo 00700, Sri Lanka)
Abstract
We introduce the Reward–VaR curve, a novel framework for evaluating risk-adjusted investment performance across a range of investor risk preferences. When returns are normally distributed, the Reward–VaR curve yields the same asset ranking as the Sharpe ratio. However, when the third-order modified VaR is used, a new paradigm emerges beyond the simplistic “better/worse” ranking: if no asset dominates at all confidence levels, one becomes preferable for risk-averse investors, while the other is favored by the risk-tolerant. For empirical implementation, we incorporate bootstrapping to separate robust performance patterns from sampling noise. We apply the methodology to compare conventional equity indices and their Islamic counterparts from the S&P Dow Jones Global Index family across nine markets from 2000 to 2024: Asia-Pacific, Canada, Developed, Emerging, Europe, Japan, UK, US, and World. Our empirical results reveal market-condition dependent dominance patterns. During bull markets, conventional indices dominate in most regions, except the European and World markets, where no dominance is observed, and Japan, where the Islamic index outperforms. In bear markets, Islamic indices dominate in most regions, with the exception of Emerging Markets, where dominance is partial, and Japan, where no clear difference is observed. Over the full sample, most markets show no significant long-run dominance, except Canada and Emerging Markets, where conventional indices outperform.
Suggested Citation
Guillaume Leduc & Shyam Sanjeewa Nishantha Perera, 2025.
"Ranking Investment Opportunities Across Risk-Aversion Levels: Application to Islamic and Conventional Indices,"
JRFM, MDPI, vol. 18(11), pages 1-31, November.
Handle:
RePEc:gam:jjrfmx:v:18:y:2025:i:11:p:623-:d:1789620
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:18:y:2025:i:11:p:623-:d:1789620. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.