Performance evaluation of volatility estimation methods for Exabel

{\O}yvind Grotmol, Martin Jullum, Kjersti Aas and Michael Scheuerer

Papers from arXiv.org

Abstract: Quantifying both historic and future volatility is key in portfolio risk management. This note presents and compares estimation strategies for volatility estimation in an estimation universe consisting on 28 629 unique companies from February 2010 to April 2021, with 858 different portfolios. The estimation methods are compared in terms of how they rank the volatility of the different subsets of portfolios. The overall best performing approach estimates volatility from direct entity returns using a GARCH model for variance estimation.

Date: 2022-03
New Economics Papers: this item is included in nep-rmg
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