Computing the Substantial-Gain–Loss-Ratio

Jan Voelzke () and Sebastian Mentemeier ()
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Jan Voelzke: University of Muenster
Sebastian Mentemeier: Universität Kassel

Computational Economics, 2019, vol. 54, issue 2, No 6, 613-624

Abstract: Abstract The Substantial-Gain–Loss-Ratio (SGLR) was developed to overcome some drawbacks of the Gain–Loss-Ratio (GLR) as proposed by Bernardo and Ledoit (J Polit Econ 108(1):144–172, 2000). This is achieved by slightly changing the condition for a good-deal, i.e. on the most extreme but at the same time very small part of the state space. As an empirical performance measure the SGLR can naturally handle outliers and is not easily manipulated. Additionally, the robustness of performance is illuminated via so-called $$\beta $$ β -diagrams. In the present paper we propose an algorithm for the computation of the SGLR in empirical applications and discuss its potential usage for theoretical models as well. Finally, we present two exemplary applications of an SGLR-analysis on historic returns.

Keywords: Substantial-Gain–Loss-Ratio; Gain–Loss-Ratio; Performance measure (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10614-018-9845-2

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