Sentiment Analysis of Financial News in Python - 3 Ways using Dictionary, FinBert and LLMs
In this video, we'll see 3 different methods to perform sentiment analysis of financial news in python:
A dictionary.-based approach using the Loughran and McDonald dictionary
FinBert, a Bert model fine-tuned for sentiment analysis of financial text using the transformers library from Hugging Face
Using large langage models with the langchain library.
The code is available here: https://github.com/Vincent-Codes-Fina...
A written version of the tutorial is available here: https://vincent.codes.finance/posts/s...
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🔖 Chapters:
00:00 Intro
00:36 Text Data
02:51 Dictionary-Based Approach
10:40 FinBert
17:24 Large Language Models
29:40 End results
🍺 Homebrew installation commands:
brew install ollama
⚙ Other commands
ollama pull mixtral
ollama pull llama2
🔗 Video links:
Loughran-McDonald Dictionary: https://sraf.nd.edu/loughranmcdonald-...
FinBert: https://huggingface.co/ProsusAI/finbert
Bert: https://huggingface.co/docs/transform...
Transformers: https://huggingface.co/docs/transform...
Ollama: https://ollama.com/
LangChain: https://python.langchain.com/docs/get...
NLTK: https://www.nltk.org/
📝 Papers:
FinBert: https://arxiv.org/abs/1908.10063
Bert: https://arxiv.org/abs/1810.04805
Loughran and McDonald: https://papers.ssrn.com/sol3/papers.c...
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