{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/finmultitime-a-four-modal-bilingual-dataset","title":"FinMultiTime: A Four-Modal Bilingual Dataset for Financial Time-Series Analysis","arxiv_id":"2506.05019","date":"2025-06-05","proceeding":null,"authors":["Wenyan Xu","Dawei Xiang","Yue Liu","Xiyu Wang","Yanxiang Ma","Liang Zhang","Shu Hu","Chang Xu","Jiaheng Zhang"],"abstract":"Pure time series forecasting tasks typically focus exclusively on numerical features; however, real-world financial decision-making demands the comparison and analysis of heterogeneous sources of information. Recent advances in deep learning and large scale language models (LLMs) have made significant strides in capturing sentiment and other qualitative signals, thereby enhancing the accuracy of financial time series predictions. Despite these advances, most existing datasets consist solely of price series and news text, are confined to a single market, and remain limited in scale. In this paper, we introduce FinMultiTime, the first large scale, multimodal financial time series dataset. FinMultiTime temporally aligns four distinct modalities financial news, structured financial tables, K-line technical charts, and stock price time series across both the S&P 500 and HS 300 universes. Covering 5,105 stocks from 2009 to 2025 in the United States and China, the dataset totals 112.6 GB and provides minute-level, daily, and quarterly resolutions, thus capturing short, medium, and long term market signals with high fidelity. Our experiments demonstrate that (1) scale and data quality markedly boost prediction accuracy; (2) multimodal fusion yields moderate gains in Transformer models; and (3) a fully reproducible pipeline enables seamless dataset updates.","url_abs":"https://arxiv.org/abs/2506.05019v1","url_pdf":"https://arxiv.org/pdf/2506.05019v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"finmultitime-a-four-modal-bilingual-dataset","repo_url":"https://github.com/marigoldwu/pydgc","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2506.05019","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.05019"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/marigoldwu/pydgc","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":15},"by_repo_kind":{"official":{"samples":15,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"4905baed41d3c5f6","entry":"aux_objective","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dgcluster.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dgcluster.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"4905baed41d3c5f6"}},{"code_sha256_prefix":"4d1191671cba756b","entry":"clustering","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/magi.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/magi.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"4d1191671cba756b"}},{"code_sha256_prefix":"67cedfe88192fd2f","entry":"comprehensive_similarity","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/hsan.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/hsan.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"67cedfe88192fd2f"}},{"code_sha256_prefix":"35b4899c9c2538c7","entry":"convert_scipy_torch_sp","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dgcluster.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dgcluster.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"35b4899c9c2538c7"}},{"code_sha256_prefix":"47733477ce73f39c","entry":"hard_sample_aware_infoNCE","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/hsan.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/hsan.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"47733477ce73f39c"}},{"code_sha256_prefix":"22bf7799b5b320ab","entry":"init_clustering","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/ccgc.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/ccgc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"22bf7799b5b320ab"}},{"code_sha256_prefix":"c5b6b75a2ae78c26","entry":"new_graph","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/agcdrr.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/agcdrr.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c5b6b75a2ae78c26"}},{"code_sha256_prefix":"e16f86b431e93340","entry":"normalize","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/agcdrr.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/agcdrr.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e16f86b431e93340"}},{"code_sha256_prefix":"c4e018bdf71a1f35","entry":"normalize_adj","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dcrn.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dcrn.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c4e018bdf71a1f35"}},{"code_sha256_prefix":"d860dca965128863","entry":"numpy_to_torch","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dcrn.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dcrn.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d860dca965128863"}},{"code_sha256_prefix":"e82410e993da99a0","entry":"regularization","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dgcluster.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dgcluster.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e82410e993da99a0"}},{"code_sha256_prefix":"1a7f3fbaa1bd6d17","entry":"remove_edge","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dcrn.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dcrn.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1a7f3fbaa1bd6d17"}},{"code_sha256_prefix":"410bc97745f4b297","entry":"scale","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/magi.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/magi.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"410bc97745f4b297"}},{"code_sha256_prefix":"143d99fb8b6fb704","entry":"square_euclid_distance","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/hsan.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/hsan.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"143d99fb8b6fb704"}},{"code_sha256_prefix":"d9d1d0c203d5cf1b","entry":"target_distribution","repo":"marigoldwu/pydgc","repo_kind":"official","path":"pydgc/models/dfcn.py","file_url":"https://github.com/marigoldwu/pydgc/blob/HEAD/pydgc/models/dfcn.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d9d1d0c203d5cf1b"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}