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A genetic algorithm approach to detecting temporal patterns indicative of financial statement fraud

HoogsBethany et al.

Intelligent Systems in Accounting, Finance and Management: An International Journal2007https://doi.org/10.5555/1285225.1285228article
ABDC B
Weight
0.26

Abstract

This study presents a genetic algorithm approach to detecting financial statement fraud. The study uses a sample comprising a target class of 51 companies accused by the Securities and Exchange Com...

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https://doi.org/https://doi.org/10.5555/1285225.1285228

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@article{hoogsbethany2007,
  title        = {{A genetic algorithm approach to detecting temporal patterns indicative of financial statement fraud}},
  author       = {HoogsBethany et al.},
  journal      = {Intelligent Systems in Accounting, Finance and Management: An International Journal},
  year         = {2007},
  doi          = {https://doi.org/https://doi.org/10.5555/1285225.1285228},
}

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A genetic algorithm approach to detecting temporal patterns indicative of financial statement fraud

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Evidence weight

0.26

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.00 × 0.4 = 0.00
M · momentum0.20 × 0.15 = 0.03
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.