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Impact of News on the Commodity Market: Dataset and Results

arXiv 2009.04202 ↗First posted 9 Sep 2020cs.CLcited by 80

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Abstract (arXiv)

Over the last few years, machine learning based methods have been applied to extract information from news flow in the financial domain. However, this information has mostly been in the form of the financial sentiments contained in the news headlines, primarily for the stock prices. In our current work, we propose that various other dimensions of information can be extracted from news headlines, which will be of interest to investors, policy-makers and other practitioners. We propose a framework that extracts information such as past movements and expected directionality in prices, asset comparison and other general information that the news is referring to. We apply this framework to the commodity "Gold" and train the machine learning models using a dataset of 11,412 human-annotated news headlines (released with this study), collected from the period 2000-2019. We experiment to validate the causal effect of news flow on gold prices and observe that the information produced from our framework significantly impacts the future gold price.

Key facts. Cited by 80 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Sep 2020.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 16; 2024: 34; 2025: 19; 2026: 8.

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  3. 2023PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Financecited by 217
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  8. 2024A Survey of Large Language Models in Finance (FinLLMs)cited by 77
  9. 2023FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasetscited by 68
  10. 2024Instruction Pre-Training: Language Models are Supervised Multitask Learnerscited by 63
  11. 2023Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Taskscited by 59
  12. 2023Adapting Large Language Models to Domains via Reading Comprehensioncited by 48
38 more
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  4. 2024MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuningcited by 31
  5. 2024AI for social science and social science of AI: A Surveycited by 29
  6. 2024A Survey of Useful LLM Evaluationcited by 28
  7. 2024OmniEval: An Omnidirectional and Automatic RAG Evaluation Benchmark in Financial Domaincited by 28
  8. 2024STEER: Assessing the Economic Rationality of Large Language Modelscited by 26
  9. 2025Demystifying Domain-adaptive Post-training for Financial LLMscited by 24
  10. 2024Benchmarking Large Language Models on CFLUE -- A Chinese Financial Language Understanding Evaluation Datasetcited by 23
  11. 2023SEntFiN 1.0: Entity-Aware Sentiment Analysis for Financial Newscited by 18
  12. 2024Large Language Model Adaptation for Financial Sentiment Analysiscited by 18
  13. 2025FinMTEB: Finance Massive Text Embedding Benchmarkcited by 18
  14. 2024SEC-QA: A Systematic Evaluation Corpus for Financial QAcited by 17
  15. 2024Agreement-Based Cascading for Efficient Inferencecited by 16
  16. 2024Mixing It Up: The Cocktail Effect of Multi-Task Fine-Tuning on LLM Performance -- A Case Study in Financecited by 15
  17. 2023FinEntity: Entity-level Sentiment Classification for Financial Textscited by 14
  18. 2024OptLLM: Optimal Assignment of Queries to Large Language Modelscited by 14
  19. 2025MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Applicationcited by 14
  20. 2025FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMscited by 14
  21. 2024Do We Need Domain-Specific Embedding Models? An Empirical Investigationcited by 12
  22. 2021Context-NER : Contextual Phrase Generation at Scalecited by 11
  23. 2023CFGPT: Chinese Financial Assistant with Large Language Modelcited by 11
  24. 2023Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processingcited by 11
  25. 2025FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasetscited by 11
  26. 2024Improving Domain Adaptation through Extended-Text Reading Comprehensioncited by 10
  27. 2025MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generationcited by 10
  28. 2024EconNLI: Evaluating Large Language Models on Economics Reasoningcited by 8
  29. 2024SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysiscited by 8
  30. 2024A Comparative Analysis of Instruction Fine-Tuning LLMs for Financial Text Classificationcited by 8
  31. 2024No Language is an Island: Unifying Chinese and English in Financial Large Language Models, Instruction Data, and Benchmarkscited by 7
  32. 2023Self-Specialization: Uncovering Latent Expertise within Large Language Modelscited by 5
  33. 2024D'olares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and Englishcited by 5
  34. 2024Enterprise Benchmarks for Large Language Model Evaluationcited by 5
  35. 2023BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Modelscited by 4
  36. 2023Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervisioncited by 4
  37. 2024'Finance Wizard' at the FinLLM Challenge Task: Financial Text Summarizationcited by 4
  38. 2024Golden Touchstone: A Comprehensive Bilingual Benchmark for Evaluating Financial Large Language Modelscited by 4

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