The Earning Analysis project assists financial analysts with investment decision making post a company’s earnings call. Most CFOs/CEOs share important details of the company’s performance during the recent quarter in the call, including successes, challenges and growth opportunities for each business line. This information is a critical component for analysts to value the respective company and aid in their investment decision making process.
How
- User enters a YouTube link with the call or an audio file
- OpenAI’s Whisper model coverts the speech to text
- FinBert-Tone (ONNX version) splits the text into sentences and generates sentiment labels across 3 tags, ‘Positive’, ‘Negative’ and Neutral
- Sentiment Plotly graphs are generated to allow visualization of sentiment across sentences
- FaceBook Bart model is used to give a summary of the Earnings call
- Semantic Search is enabled using sentence transformers for the analyst to search or ask specific questions or concerns that might have been addressed in the call.
Deliverables
- Analysis of any earnings call which can be used as part of the financial analysis toolkit.
- Build knowledge graph to display the relationship between entities
Squad
Nick Muchi
Fixed Income and FX Trader at Vanguard
Twitter: https://twitter.com/nickmuchi
Hugging Face Space link: Earnings Call Analysis Whisperer - a Hugging Face Space by nickmuchi