We present FinSentGPT, a financial sentiment prediction model based on a fine-tuned version of the artificial intelligence language model, ChatGPT. To assess the model’s effectiveness, we analyse a sample of US media news and a multi-language dataset of European Central Bank Monetary Policy Decisions. Our findings demonstrate that FinSentGPT’s sentiment classification ability aligns well with a prominent English-language finance sentiment model, surpasses an established alternative machine learning model, and is capable of predicting sentiment across various languages. Consequently, we offer preliminary evidence that advanced large-language AI models can facilitate flexible and contextual financial sentiment determination, transcending language barriers.

中文翻译：

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FinSentGPT：通用金融情绪引擎？

我们提出了 FinSentGPT，这是一种基于人工智能语言模型 ChatGPT 的微调版本的金融情绪预测模型。为了评估该模型的有效性，我们分析了美国媒体新闻样本和欧洲央行货币政策决策的多语言数据集。我们的研究结果表明，FinSentGPT 的情绪分类能力与著名的英语金融情绪模型非常吻合，超越了现有的替代机器学习模型，并且能够预测各种语言的情绪。因此，我们提供的初步证据表明，先进的大语言人工智能模型可以促进灵活的、上下文相关的金融情绪确定，超越语言障碍。