Multimodal Financial Data

Data-Centric Approach for Multimodal Financial Data

#### Earnings Conference Calls

[4] [What You Say and How You Say It Matters: Predicting Financial Risk Using Verbal and Vocal Cues](https://aclanthology.org/P19-1038.pdf) ACL 2019. [Data](https://github.com/GeminiLn/EarningsCall_Dataset/tree/master)

[3] [HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction](https://dl.acm.org/doi/pdf/10.1145/3366423.3380128?casa_token=nczNU-7cmJ8AAAAA:f8QGb4OhlRADBCm6eNl2Zvuwd5B7WIWUTtsEkAcWum-ValjGaTGSyn7NoZcQ-MgiXN-SkdoQMNg5sw), WWW 2020. [Code](https://github.com/YangLinyi/HTML-Hierarchical-Transformer-based-Multi-task-Learning-for-Volatility-Prediction).

[2] [MAEC: A Multimodal Aligned Earnings Conference Call Dataset for Financial Risk Prediction](https://dl.acm.org/doi/pdf/10.1145/3340531.3412879), CIKM 2020. [Data](https://github.com/Earnings-Call-Dataset/MAEC-A-Multimodal-Aligned-Earnings-Conference-Call-Dataset-for-Financial-Risk-Prediction)

[1] [ECC Analyzer: Extracting Trading Signal from Earnings Conference Calls using Large Language Model for Stock Volatility Prediction](https://dl.acm.org/doi/pdf/10.1145/3677052.3698689), ICAIF 2024.

#### Monetary Policy Conference [2] [MONOPOLY: Financial Prediction from MONetary POLicY Conference Videos Using Multimodal Cues](https://dl.acm.org/doi/pdf/10.1145/3503161.3548380?casa_token=HGG8_xUXqgYAAAAA:KKB772yfPxxsIo5IhIrZfeEffMkomYa-KYvHt7p7F3awe1bManRzorGFAqrdckPXkjSdMafYLgAdRQ), Multimedia 2022. [Code](https://github.com/monopoly-monitory-policy-calls/MONOPOLY)

[1] [Modal-adaptive Knowledge-enhanced Graph-based Financial Prediction from Monetary Policy Conference Calls with LLM](https://arxiv.org/pdf/2403.16055), FinNLP Workshop 2024. [Code](https://github.com/OuyangKun10/MANAGER)

#### Financial Reports [2] [Attentive statement fraud detection: Distinguishing multimodal financial data with fine-grained attention](https://www.sciencedirect.com/science/article/pii/S0167923622001841?casa_token=H5JWNW5xkkIAAAAA:ieMEzMom76ojHKJGekhrh5uBokT2FtYBAWVhBu406vu46YiO_p3jc8OE9EBa3Q91anUykV9s5x4), Decision Support System 2023.

[1] [XBRL-Agent: Leveraging large language models for financial report analysis](https://dl.acm.org/doi/pdf/10.1145/3677052.3698614?casa_token=eFzOiTLZuGkAAAAA:SNON8hhKqSXmkTASdYeemnJ-6z_QGMufywoaTNEzrqtf8-ylo6sjHIIcvScIafgWdAyq0RUCUx25jQ), ICAIF 2024. [Code](https://github.com/Open-Finance-Lab/Chat_XBRL)

#### Financial News [1] [Analyzing Cascading Outbreak of GameStop Event: A Practical Approach Using Network Analysis and Large Language Models](https://dl.acm.org/doi/pdf/10.1145/3677052.3698636?casa_token=8IWUicpVTmUAAAAA:9RUD7Btk7kf30IAQdRN1GoF0L1_SZNLJ_MgpYl4TD-iM1lzBDW3LT4_EDjis2LoMeWaCHKqBQNKC6A), ICAIF 2024.

#### Market Data [2] [FinRL: A deep reinforcement learning library for automated stock trading in quantitative finance](https://github.com/AI4Finance-Foundation/FinRL), Deep Reinforcement Learning Workshop @ NeurIPS 2020. [Code](https://github.com/AI4Finance-Foundation/FinRL)

[1][FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning](https://proceedings.neurips.cc/paper_files/paper/2022/file/0bf54b80686d2c4dc0808c2e98d430f7-Paper-Datasets_and_Benchmarks.pdf), NeurIPS 2022. [Code](https://github.com/AI4Finance-Foundation/FinRL-Meta)

#### Climate Data for Commodity Trading …

#### Financial Curriculum and Certificates [1] [High-Quality Financial Benchmark (QFinBen): Can LLMs Earn Degrees and Certificates?](), Multimodal Financial Foundation Models Workshop @ ICAIF 2024.