{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/40422"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/40422","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Industry Based Fundamental Analysis: Using Neural Networks and a Dual-Layered Genetic Algorithm Approach","abstract":"This research tests the ability of artificial learning methodologies to map market returns better than logistic regression. The learning methodologies used are neural networks and dual-layered genetic algorithms. These methodologies are used to develop a trading strategy to generate excess returns. The excess returns are compared to test the trading strategy's effectiveness. Market-adjusted and size-adjusted excess returns are calculated. 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