InFineac

Extracting Financial Insights from Earnings Calls using NLP.

InFineac is a Python package that extracts financial insights from earnings calls by categorizing them into a range of topics using NLP. Earnings calls are a rich source of information for investors, that are held quarterly by publicly traded companies. InFineac heavily uses the spaCy and BERTopic libraries for the NLP tasks.

Documentation

• User Guide
  • Overview
  • Install
  • Quickstart
    • Load the data
    • Create Corpus
    • Extract Topics
  • File structure
• Detailed Description
  • Research question
  • Earnings Calls
  • Data
    • Structure

Package

• API Reference

infineac.compare_results	Compare the results of the different models created by the infineac.pipeline or the infineac.topic_extractor modules.
infineac.constants	Contains constants used in the infineac package.
infineac.file_loader	Imports and structures the earnings calls data from xml files.
infineac.helper	This module contains helper functions for the infineac package.
infineac.pipeline	Entire pipeline to extract topics from a given list of files containing earnings calls transcripts or a list of events.
infineac.process_event	Contains functions to manipulate events and strings and extract the corresponding information for the infineac package.
infineac.process_text	Contains methods to process text data.
infineac.topic_extractor	Extracts topics from a list of documents using BERTopic.

Indices and tables

• Index

• Module Index

• Search Page