FinGPT's stock forecasting feature is available throughFinGPT-Forecaster modulerealization, the following is a typical workflow demonstrated through AAPL stock:
- Initialize the predictor::
from fingpt.forecaster import FinGPTForecaster
forecaster = FinGPTForecaster() - Setting space-time parameters::
You need to define the ticker symbol (e.g. "AAPL"), time window (e.g. from "2023-01-01″), news cycle (4 weeks is recommended) and whether to load financial indicators. - Implementation projections::
prediction = forecaster.predict(params)A JSON result containing the following elements will be returned:- Price confidence interval for the next 30 days
- Summary of key events affecting the share price
- Peer-to-peer comparative analysis
Technical Principles: The model will:
1. Grab historical prices from Yahoo Finance
2. Scanning SEC filings for financial data
3. Aggregation of sentiment analysis results from media outlets such as Reuters
Finally, the prediction is generated by a time-series neural network, and the whole process takes about 3-5 minutes (depending on the speed of the network).
This answer comes from the articleFinGPT: Open Source Financial Big Language Modeling Platform for Financial Analytics and PredictionThe
May not be reproduced without permission:AI productivity tools " Can you give an example of how to use FinGPT for stock forecasting?
