Computing the Substantial-Gain–Loss-Ratio

Autor:	Jan Voelzke, Sebastian Mentemeier
Rok vydání:	2018
Předmět:	Engineering 050208 finance business.industry Computation 05 social sciences Economics Econometrics and Finance (miscellaneous) Theoretical models Computer Science Applications Robustness (computer science) 0502 economics and business Outlier 050207 economics business Algorithm Simulation
Zdroj:	Computational Economics. 54:613-624
ISSN:	1572-9974 0927-7099
DOI:	10.1007/s10614-018-9845-2
Popis:	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 $$\beta $$ -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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4bdbdc7d45cbaae65a59ff553d0b84b7 https://doi.org/10.1007/s10614-018-9845-2 Zobrazit plný text záznamu Full text from SpringerLink