5 papers
When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis
Hoyoung Lee, Suhwan Park, Seunghan Lee +15
Financial decision-makers face more information than they can directly inspect, making context compression necessary. Yet when large language models (LLMs) compress financial sourc…
From Text to Alpha: Can LLMs Track Evolving Signals in Corporate Disclosures?
Chanyeol Choi, Yoon Kim, Yu Yu +10
Natural language processing (NLP) has been widely used in quantitative finance, but traditional methods often struggle to capture rich narratives in corporate disclosures, leaving…
LLM as a Risk Manager: LLM Semantic Filtering for Lead-Lag Trading in Prediction Markets
Sumin Kim, Minjae Kim, Jihoon Kwon +7
Prediction markets provide a unique setting where event-level time series are directly tied to natural-language descriptions, yet discovering robust lead-lag relationships remains…
FinAgentBench: A Benchmark Dataset for Agentic Retrieval in Financial Question Answering
Chanyeol Choi, Jihoon Kwon, Alejandro Lopez-Lira +8
Accurate information retrieval (IR) is critical in the financial domain, where investors must identify relevant information from large collections of documents. Traditional IR meth…
Structuring the Unstructured: A Multi-Agent System for Extracting and Querying Financial KPIs and Guidance
Chanyeol Choi, Alejandro Lopez-Lira, Yongjae Lee +8
Extracting structured and quantitative insights from unstructured financial filings is essential in investment research, yet remains time-consuming and resource-intensive. Conventi…