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Improving Portfolio Performance via Natural Language Processing Methods
Journal of Financial Data Science ; 4(2):37-49, 2022.
Article in English | Scopus | ID: covidwho-1911790
ABSTRACT
Recent natural language processing (NLP) breakthroughs have proven effective for addressing many language-directed tasks, such as completing sentences and addressing search queries. This technology has been successfully implemented by tech firms including Google and others. An important element consists of language embeddings linked to pretraining systems. This ar ticle describes NLP concepts and their application to por tfolio models via a modern version of sentiment analysis. The authors demonstrate the advantages of employing information from Twitter along with the NLP for constructing a portfolio of stocks, especially during unusual events such as the COVID-19 pandemic. © 2022 With Intelligence Ltd.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Journal of Financial Data Science Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Journal of Financial Data Science Year: 2022 Document Type: Article