Economics at your fingertips  

Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy

Claudiu Vinte and Marcel Ausloos

Papers from

Abstract: Selecting stock portfolios and assessing their relative volatility risk compared to the market as a whole, market indices, or other portfolios is of great importance to professional fund managers and individual investors alike. Our research uses the cross-sectional intrinsic entropy (CSIE) model to estimate the cross-sectional volatility of the stock groups that can be considered together as portfolio constituents. In our study, we benchmark portfolio volatility risks against the volatility of the entire market provided by the CSIE and the volatility of market indices computed using longitudinal data. This article introduces CSIE-based betas to characterise the relative volatility risk of the portfolio against market indices and the market as a whole. We empirically prove that, through CSIE-based betas, multiple sets of symbols that outperform the market indices in terms of rate of return while maintaining the same level of risk or even lower than the one exhibited by the market index can be discovered, for any given time interval. These sets of symbols can be used as constituent stock portfolios and, in connection with the perspective provided by the CSIE volatility estimates, to hierarchically assess their relative volatility risk within the broader context of the overall volatility of the stock market.

Date: 2023-03
New Economics Papers: this item is included in nep-des, nep-fmk and nep-rmg
References: View references in EconPapers View complete reference list from CitEc

Published in Journal of Risk Financial Management 2023, 16(2), 114

Downloads: (external link) Latest version (application/pdf)

Related works:
Journal Article: Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy (2023) Downloads
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:

Access Statistics for this paper

More papers in Papers from
Bibliographic data for series maintained by arXiv administrators ().

Page updated 2024-05-07
Handle: RePEc:arx:papers:2303.09330