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| ファイル | 記述 | サイズ | フォーマット | |
|---|---|---|---|---|
| DP1103.pdf | 1.77 MB | Adobe PDF | 見る/開く |
完全メタデータレコード
| DCフィールド | 値 | 言語 |
|---|---|---|
| dc.contributor.author | Hens, Thorsten | en |
| dc.contributor.author | Nordlie, Trine | en |
| dc.date.accessioned | 2024-06-12T05:30:31Z | - |
| dc.date.available | 2024-06-12T05:30:31Z | - |
| dc.date.issued | 2024-04 | - |
| dc.identifier.uri | http://hdl.handle.net/2433/287830 | - |
| dc.description.abstract | This study compares OpenAI's ChatGPT-4 and Google's Bard with bank experts in determining investors' risk profiles. We find that for half of the client cases used, there are no statistically significant differences in the risk profiles. Moreover, the economic relevance of the differences is small. | en |
| dc.description.tableofcontents | Online Appendices [9] | en |
| dc.language.iso | eng | - |
| dc.publisher | Institute of Economic Research, Kyoto University | en |
| dc.publisher.alternative | 京都大学経済研究所 | ja |
| dc.subject | Large Language Models | en |
| dc.subject | ChatGPT | en |
| dc.subject | Bard | en |
| dc.subject | Risk Profiling | en |
| dc.subject.ndc | 330 | - |
| dc.title | How good are LLMs in risk profiling? | en |
| dc.type | research report | - |
| dc.type.niitype | Research Paper | - |
| dc.identifier.jtitle | KIER Discussion Paper | en |
| dc.identifier.volume | 1103 | - |
| dc.identifier.spage | 1 | - |
| dc.identifier.epage | 16 | - |
| dc.textversion | author | - |
| dc.sortkey | 01103 | - |
| dc.address | Department of Finance, University of Zurich ; Department of Finance, Norwegian School of Economics; Institute of Economic Research, Kyoto University | en |
| dc.address | Department of Finance, Norwegian School of Economics | en |
| dc.relation.url | https://www.kier.kyoto-u.ac.jp/publication/?cat=en | - |
| dcterms.accessRights | open access | - |
| 出現コレクション: | KIER Discussion Paper (英文版) | |
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