The Art of Reading Financial Statements - Textual analysis

Advanced Course: In-Depth Analysis of 113,000 Financial Reports Over 20 Years

What you'll learn

• Advanced reading & understanding of financial statements
• Detecting value destruction for shareholders
• Capture financial statement red flags
• Detecting potential earnings manipulations

Requirements

• Have a good understanding of financial reports
• Have a good understanding of corporate finance
• Have a good understanding of corporate governance
• Be fluent in stock markets and investing

Description

Unlock the hidden insights within financial reports with Textual Analysis of Financial Reports, the second course in The Art of Reading Financial Statements series. Dive into a unique approach to financial analysis that goes beyond numbers, focusing on the tone, complexity, and language of corporate reports. This course explores how key textual elements within annual and quarterly filings might correlate with company stock performance, providing an innovative edge to your investment analysis.

Drawing on a comprehensive dataset of 113,612 reports from 1,025 companies—sourced directly from the SEC EDGAR database, including 10-K, 10-Q, and 20-F filings—spanning two decades from 2004 to 2024, this course offers a comprehensive look at:

• Sentiment Polarity: Determining the overall positive or negative sentiment within reports.
• Sentiment Subjectivity: Gauging the objective versus subjective tone of a company’s language.
• Sentiment Dictionary Score: Leveraging sentiment scores from a curated financial lexicon.
• Complexity Score: Analyzing report readability to assess transparency and clarity.
• Red Flags Keyword Matching: Identifying potentially concerning language or red flags.

In this course we will also specifically analyse the 3 sentiment metrics, complexity and red flags for the following companies : 23andme, AIG, 3M, Boeing, Intel, Goldman Sachs, Apple, Abercrombie & Fitch, Caterpillar, Mondelez International, Coca-Cola, Northrop Grumman, Wells Fargo, Kraft Heinz, Nike, Alibaba & Ambev.

All analytical data points are available in VingeGPT, enabling you to explore and visualize correlations (or lack thereof) between textual elements and stock price performance. This course is designed for those who seek a deeper understanding of how language in financial documents can inform investment decisions.

Get ready to enhance the way you read financial statements and upgrade your analytical toolkit!

with thanks

Candi and the VingeGPT team

Who this course is for:

• Value investors
• Investors interested in complemeting their investment journey with supplemental metrics
• Corporate finance students