GenAI in Financial analysis
- get 5 tickets of industry
- use GenAI to summarize the stocks by analyst's grading, Sentiment of news, Industry industry_analysis
- use GenAI to Rank the stocks based on their investment summaries generated by Step2
llm4Fin.py demo link: https://llm4fin.streamlit.app
The selected code block contains code related to financial analysis using machine learning models. Here's a brief overview:
It imports necessary libraries like yfinance for fetching stock data, streamlit for building a web app interface, asyncio and aiohttp for asynchronous requests. It defines a llm_gemini function that takes user input and sends it to the Gemini conversational model to generate a response. This uses rate limiting to restrict requests to the model. There are functions to fetch stock data using yfinance, compare companies, perform sentiment analysis on news, get analyst ratings and industry analysis. It caches frequently fetched data like article text and analyst ratings to improve performance. At the end it defines a get_final_analysis function that would take all the previous analyses and generate an investment recommendation. So in summary, this code is building a financial analysis application that interacts with users, fetches relevant stock data, runs ML models for tasks like comparison and sentiment analysis, and aims to provide a final investment analysis based on all the inputs.
