| Autor: |
Do-Guk Kim, Bonggyun Ko |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 7, Pp 133707-133715 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2939414 |
| Popis: |
Investment universe means a pool of selected assets likely to be profitable. In general, assets related to a common theme or concept are selected to form an investment universe. A well organized investment universe has a strong common theme and reduces the risk by diversifying the assets included in the universe. To form or revise an investment universe, human efforts are required by using domain knowledge about the theme, but it is hard to suggest an investment universe that reflects the latest market trends. In this paper, we propose an automated investment universe selection method based on theme keywords. The theme keywords are extracted from the news articles and the business section on the companies which are included in the S&P 500 index. After that, securities are selected to form an investment universe for each theme keywords. We employ a similarity value between the security vector and the theme keyword vector to select the related securities for the certain keywords. Regarding the vector representations, word and document embeddings are carried out using both news articles and the business section on the companies. Stock price movements of the selected securities are similar which means that the investment universes are well organized to suggest the assets tightly associated with the theme. The experimental results show that the proposed method has high future returns on the investment universes with low or high historical stock price returns. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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