Deconstructing the Gerber statistic

Emlyn Flint and Daniel Polakow

Finance Research Letters, 2023, vol. 56, issue C

Abstract: The Gerber Statistic is a recently proposed co-movement measure. The measure is a conditional statistic and due to conditioning bias, will naturally differ from full-sample measures. This contribution makes use of an intuitive two-asset simulation framework to better elucidate the statistical behaviour of the Gerber Statistic, across its three proposed forms. Using graphical correlation profiles, we explore the measure's behaviour across return conditioning threshold, sample size and market distribution, detailing its mechanisms of performance but also demonstrating several caveats around its understanding and use. We conclude that while interesting, the Gerber Statistic is best viewed as an imperfect conditional dependence metric.

Keywords: Conditional correlation; Conditioning bias; Shrinkage; Mean-variance optimization; Diversification (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323005160

DOI: 10.1016/j.frl.2023.104144

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