PREDIKCIJA CENE FINANSIJSKE AKTIVE ANALIZOM SENTIMENTA FINANSIJSKIH TVITOVA
Ključne reči:
sentiment analiza, NLP, transfer učenja, DistilBERT, predikcija cena, LSTM, fintech
Apstrakt
U ovom radu predstavljen je sistem za predikciju cena finansijske aktive analizom sentimenta finansijskih tvitova i vesti. Cilj razvijenog sistema je ispitivanje sledeće hipoteze: postoji korelacija između sentimenta finansijskih tvitova i cene finansijske aktive. To jest, proveramo da li će rezultati sentiment analize doprineti boljim rezultatima predikcije. Razvijeni sistem se sastoji od dva podsistema. Prvi podsistem je zadužen za sentiment analizu, dok je drugi podsistem zadužen za predikciju cena finansijske aktive. Studija slučaja izvršena je na primeru tvitova i akcija Apple korporacije u vremenskom periodu od januara 2010. godine do decembra 2020. godine. Predloženi su koraci za poboljšanje i dalji razvoj sistema.
Reference
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[2] Ao, S. (2018, July). Sentiment analysis based on financial tweets and market information. In 2018 International Conference on Audio, Language and Image Processing (ICALIP) (pp. 321-326). IEEE.
[3] Loughran, T., & McDonald, B. (2011). When is a liability not a liability? Textual analysis, dictionaries, and 10‐Ks. The Journal of finance, 66(1), 35-65.
[4] Darwich, M., Mohd, S. A., Omar, N., & Osman, N. A. (2019). Corpus-Based Techniques for Sentiment Lexicon Generation: A Review. J. Digit. Inf. Manag., 17(5), 296.
[5] Smailović, J., Grčar, M., Lavrač, N., & Žnidaršič, M. (2013, July). Predictive sentiment analysis of tweets: A stock market application. In International workshop on human-computer interaction and knowledge discovery in complex, unstructured, big data (pp. 77-88). Springer, Berlin, Heidelberg.
[6] Kordonis, J., Symeonidis, S., & Arampatzis, A. (2016, November). Stock price forecasting via sentiment analysis on Twitter. In Proceedings of the 20th Pan-Hellenic Conference on Informatics (pp. 1-6).
[7] Chen, C. C., Huang, H. H., & Chen, H. H. (2018, April). Fine-grained analysis of financial Tweets. In Companion Proceedings of the The Web Conference 2018 (pp. 1943-1949).
[8] Mishev, K., Gjorgjevikj, A., Vodenska, I., Chitkushev, L. T., & Trajanov, D. (2020). Evaluation of sentiment analysis in finance: from lexicons to transformers. IEEE Access, 8, 131662-131682.
[9] Dogra, V., Singh, A., Verma, S., Jhanjhi, N. Z., & Talib, M. N. (2021). Analyzing DistilBERT for Sentiment Classification of Banking Financial News. In Intelligent Computing and Innovation on Data Science (pp. 501-510). Springer, Singapore.
[10] Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
[2] Ao, S. (2018, July). Sentiment analysis based on financial tweets and market information. In 2018 International Conference on Audio, Language and Image Processing (ICALIP) (pp. 321-326). IEEE.
[3] Loughran, T., & McDonald, B. (2011). When is a liability not a liability? Textual analysis, dictionaries, and 10‐Ks. The Journal of finance, 66(1), 35-65.
[4] Darwich, M., Mohd, S. A., Omar, N., & Osman, N. A. (2019). Corpus-Based Techniques for Sentiment Lexicon Generation: A Review. J. Digit. Inf. Manag., 17(5), 296.
[5] Smailović, J., Grčar, M., Lavrač, N., & Žnidaršič, M. (2013, July). Predictive sentiment analysis of tweets: A stock market application. In International workshop on human-computer interaction and knowledge discovery in complex, unstructured, big data (pp. 77-88). Springer, Berlin, Heidelberg.
[6] Kordonis, J., Symeonidis, S., & Arampatzis, A. (2016, November). Stock price forecasting via sentiment analysis on Twitter. In Proceedings of the 20th Pan-Hellenic Conference on Informatics (pp. 1-6).
[7] Chen, C. C., Huang, H. H., & Chen, H. H. (2018, April). Fine-grained analysis of financial Tweets. In Companion Proceedings of the The Web Conference 2018 (pp. 1943-1949).
[8] Mishev, K., Gjorgjevikj, A., Vodenska, I., Chitkushev, L. T., & Trajanov, D. (2020). Evaluation of sentiment analysis in finance: from lexicons to transformers. IEEE Access, 8, 131662-131682.
[9] Dogra, V., Singh, A., Verma, S., Jhanjhi, N. Z., & Talib, M. N. (2021). Analyzing DistilBERT for Sentiment Classification of Banking Financial News. In Intelligent Computing and Innovation on Data Science (pp. 501-510). Springer, Singapore.
[10] Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
Objavljeno
2022-07-07
Sekcija
Elektrotehničko i računarsko inženjerstvo
