Abstract
Financial ratio analysis is a primary method for resolving one of the industry’s most perplexing problems: picking stocks. The value investing method is based on the premise that undervalued stocks may be found due of the stock market’s inefficiencies. Investment in these underpriced equities might provide additional returns for smart investors. A lack of understanding of the complicated linkages between financial factors and value stocks is a limitation of present research (i.e. statistics and some AI approaches). Therefore, the primary goal of this work is to develop a model that could be a base for knowledge representation with reasoning and confront the unclear and imprecise financial data in order to get intelligible information or implications for value stock selection. This procedure of knowledge representation is elaborated with the help of ontology to find meaningful relations in value stock extraction.
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Bhuyan, B.P., Sastry, H. (2023). Stock Selection Using Ontological Financial Analysis. In: Chakraborty, B., Biswas, A., Chakrabarti, A. (eds) Advances in Data Science and Computing Technologies. ADSC 2022. Lecture Notes in Electrical Engineering, vol 1056. Springer, Singapore. https://doi.org/10.1007/978-981-99-3656-4_19
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DOI: https://doi.org/10.1007/978-981-99-3656-4_19
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