Summarization of Investment Reports Using Pre-trained Model
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909279356715008 |
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| author | Sakaji, Hiroki Kobayashi, Ryotaro Izumi, Kiyoshi Mitsugi, Hiroyuki Kuramoto, Wataru |
| author_facet | Sakaji, Hiroki Kobayashi, Ryotaro Izumi, Kiyoshi Mitsugi, Hiroyuki Kuramoto, Wataru |
| contents | In this paper, we attempt to summarize monthly reports as investment reports. Fund managers have a wide range of tasks, one of which is the preparation of investment reports. In addition to preparing monthly reports on fund management, fund managers prepare management reports that summarize these monthly reports every six months or once a year. The preparation of fund reports is a labor-intensive and time-consuming task. Therefore, in this paper, we tackle investment summarization from monthly reports using transformer-based models. There are two main types of summarization methods: extractive summarization and abstractive summarization, and this study constructs both methods and examines which is more useful in summarizing investment reports. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_01744 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Summarization of Investment Reports Using Pre-trained Model Sakaji, Hiroki Kobayashi, Ryotaro Izumi, Kiyoshi Mitsugi, Hiroyuki Kuramoto, Wataru Computation and Language In this paper, we attempt to summarize monthly reports as investment reports. Fund managers have a wide range of tasks, one of which is the preparation of investment reports. In addition to preparing monthly reports on fund management, fund managers prepare management reports that summarize these monthly reports every six months or once a year. The preparation of fund reports is a labor-intensive and time-consuming task. Therefore, in this paper, we tackle investment summarization from monthly reports using transformer-based models. There are two main types of summarization methods: extractive summarization and abstractive summarization, and this study constructs both methods and examines which is more useful in summarizing investment reports. |
| title | Summarization of Investment Reports Using Pre-trained Model |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2408.01744 |