title: Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4
    on mock CFA Exams
summary: Large Language Models (LLMs) have demonstrated remarkable performance on a
  wide range of Natural Language Processing (NLP) tasks, often matching or even
  beating state-of-the-art task-specific models. This study aims at assessing the
  financial reasoning capabilities of LLMs. We leverage mock exam questions of
  the Chartered Financial Analyst (CFA) Program to conduct a comprehensive
  evaluation of ChatGPT and GPT-4 in financial analysis, considering Zero-Shot
  (ZS), Chain-of-Thought (CoT), and Few-Shot (FS) scenarios. We present an
  in-depth analysis of the models' performance and limitations, and estimate
  whether they would have a chance at passing the CFA exams. Finally, we outline
  insights into potential strategies and improvements to enhance the
  applicability of LLMs in finance. In this perspective, we hope this work paves
  the way for future studies to continue enhancing LLMs for financial reasoning
  through rigorous evaluation.
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paper_authors.name: Ethan Callanan
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paper_authors.name: Mathieu Sibue
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paper_authors.name: Xiaodan Zhu
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paper_authors.name: Zhiqiang Ma
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paper_authors.fullname: Zhiqiang Ma
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paper_authors.user: zqmaster
paper_authors._id: 652de0de06fab2df13b1da10
paper_authors.name: Xiaomo Liu
paper_authors.status: admin_assigned
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paper_authors._id: 6365131229941f95ad725910
paper_authors.avatarUrl: /avatars/5e709cb8e0f1415aeea38e9904703b25.svg
paper_authors.fullname: liu
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paper_authors.user: xiaomo
paper_authors._id: 652de0de06fab2df13b1da11
paper_authors.name: Sameena Shah
paper_title: Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4
    on mock CFA Exams
paper_summary: Large Language Models (LLMs) have demonstrated remarkable performance on a
  wide range of Natural Language Processing (NLP) tasks, often matching or even
  beating state-of-the-art task-specific models. This study aims at assessing the
  financial reasoning capabilities of LLMs. We leverage mock exam questions of
  the Chartered Financial Analyst (CFA) Program to conduct a comprehensive
  evaluation of ChatGPT and GPT-4 in financial analysis, considering Zero-Shot
  (ZS), Chain-of-Thought (CoT), and Few-Shot (FS) scenarios. We present an
  in-depth analysis of the models' performance and limitations, and estimate
  whether they would have a chance at passing the CFA exams. Finally, we outline
  insights into potential strategies and improvements to enhance the
  applicability of LLMs in finance. In this perspective, we hope this work paves
  the way for future studies to continue enhancing LLMs for financial reasoning
  through rigorous evaluation.
paper_ai_summary: LLMs, evaluated using CFA exam questions, show mixed performance in financial reasoning across different scenarios, highlighting areas for improvement and future research.
paper_ai_keywords: Large Language Models (LLMs) Natural Language Processing (NLP) Chartered Financial Analyst (CFA) Program ChatGPT GPT-4 Zero-Shot (ZS) Chain-of-Thought (CoT) Few-Shot (FS)