FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model

PyTorch implementation for [WWW'2024] "FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model"

Example Reports

Obtaining Factors

There are two ways to get the factors:

First Way

The first way relies on the stockstats library, which is a wrapper for pandas dataframes.

pip install stockstats

Commonly you can input a pandas dataframe with the following columns: ['date', 'open', 'close', 'high', 'low', 'volume']to use the wrap function to get the factors.

import pandas as pd
from stockstats import wrap

data = pd.read_csv('stock.csv')
df = wrap(data)

Check the documentation for stockstats for more details. More details and examples can also be found in src/Tech_Indicators.py.

Second Way

The second way to obtain the factors is to API from platforms like IFind, which provides a variety of factors. We recommend using this method to obtain more factors more esaily.

Codes are available in src/IFind_Indicators.py. You can run it after filling the access_token in Line 10, customizing necessary parameters of form_data in Line 14.