000097028 001__ 97028
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000097028 0247_ $$2doi$$a10.1016/j.frl.2019.101367
000097028 0248_ $$2sideral$$a115137
000097028 037__ $$aART-2020-115137
000097028 041__ $$aeng
000097028 100__ $$0(orcid)0000-0003-4675-6762$$aGimeno Losilla, Ruth$$uUniversidad de Zaragoza
000097028 245__ $$aA neural approach to the value investing tool F-score
000097028 260__ $$c2020
000097028 5060_ $$aAccess copy available to the general public$$fUnrestricted
000097028 5203_ $$aThis work is the first neural approach to Piotroski’s (2000) F-Score. From the same informative signals, our approach based on network data envelopment analysis allows for 1) overcoming the binary perspective of classification between companies with good/bad fundamentals, and 2) appropriately assessing the existing interaction among a company’s main financial areas. The analysis of a complete sample of the largest listed companies in the Eurozone and in the U.S. market in the period 2006-2017 shows that our neural F-Score significantly improves the portfolio returns obtained by the original F-Score.

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000097028 590__ $$a5.596$$b2020
000097028 591__ $$aBUSINESS, FINANCE$$b6 / 108 = 0.056$$c2020$$dQ1$$eT1
000097028 592__ $$a1.339$$b2020
000097028 593__ $$aFinance$$c2020$$dQ1
000097028 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000097028 700__ $$0(orcid)0000-0002-3528-4715$$aLobán Acero, Lidia$$uUniversidad de Zaragoza
000097028 700__ $$0(orcid)0000-0003-4778-5960$$aVicente Gimeno, Luis Alfonso$$uUniversidad de Zaragoza
000097028 7102_ $$14002$$2230$$aUniversidad de Zaragoza$$bDpto. Contabilidad y Finanzas$$cÁrea Economía Finan. y Contab.
000097028 773__ $$g37, 101367 (2020), [6 pp.]$$pFinance res. lett.$$tFinance Research Letters$$x1544-6123
000097028 8564_ $$s604780$$uhttps://zaguan.unizar.es/record/97028/files/texto_completo.pdf$$yPostprint
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000097028 951__ $$a2022-04-05-14:36:05
000097028 980__ $$aARTICLE