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Found 12 papers, 6 papers with code
FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generation
In the fast-paced financial domain, accurate and up-to-date information is critical to addressing ever-evolving market conditions.
The Memorization Problem: Can We Trust LLMs' Economic Forecasts?
Large language models (LLMs) cannot be trusted for economic forecasts during periods covered by their training data.
Can Large Language Models Trade? Testing Financial Theories with LLM Agents in Market Simulations
This paper presents a realistic simulated stock market where large language models (LLMs) act as heterogeneous competing trading agents.
Bridging Language Models and Financial Analysis
The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly within the financial sector.
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Financial LLMs hold promise for advancing financial tasks and domain-specific applications.
No Language is an Island: Unifying Chinese and English in Financial Large Language Models, Instruction Data, and Benchmarks
While the progression of Large Language Models (LLMs) has notably propelled financial analysis, their application has largely been confined to singular language realms, leaving untapped the potential of bilingual Chinese-English capacity.
FinBen: A Holistic Financial Benchmark for Large Language Models
Our evaluation of 15 representative LLMs, including GPT-4, ChatGPT, and the latest Gemini, reveals several key findings: While LLMs excel in IE and textual analysis, they struggle with advanced reasoning and complex tasks like text generation and forecasting.
Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English
We evaluate our model and existing LLMs using FLARE-ES, the first comprehensive bilingual evaluation benchmark with 21 datasets covering 9 tasks.
Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models
We then propose the first Credit and Risk Assessment Large Language Model (CALM) by instruction tuning, tailored to the nuanced demands of various financial risk assessment tasks.
PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
This paper introduces PIXIU, a comprehensive framework including the first financial LLM based on fine-tuning LLaMA with instruction data, the first instruction data with 136K data samples to support the fine-tuning, and an evaluation benchmark with 5 tasks and 9 datasets.
Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models
We document the capability of large language models (LLMs) like ChatGPT to predict stock price movements using news headlines, even without direct financial training.
Does Peer-Reviewed Research Help Predict Stock Returns?
Data mining generates other features of economic research including the rise in returns as original sample periods end and the speed of post-sample decay.
