B8026-001: Applied Fundamental Analysis with Alternative Data
R - B Term, 02:00PM to 05:15PM
Credit hours: 1.5
Location: URI 330
Method of Instruction: Hyflex/Hybrid
Instructor: Matthew Dell Orfano
Fundamental analysis requires the assembly of information to acquire a firm understanding of a business and its investment value. Accounting information is essential, but not sufficient. It is imperative to go beyond the numbers in financial statements with alternative data and information. Together they forecast the future earnings and cash flows that are the basis for valuation. This course guides the student in acquiring alternative data, extracting insight from it for both macro and micro applications, and combining the data with accounting information to evaluate the fundamental underlying investment value.
In investment analysis, there are many decisions to be made in achieving a fundamental understanding of a company or opportunity. Finding the ground truth regarding a company's positioning, operations, and prospects is not a trivial task. In this course, we will learn to accept that there is no predefined formula to identify, quantify, and project the challenges and opportunities that exist in a complex organization operating in a constantly evolving global environment.
The student will work with real datasets and will benefit from direct advice, experience, and practical insights of portfolio managers, research analysts, and former government officials to derive value from the world of information in front of them.
Modern alternative data resources and techniques will be shared and applied. Students will master the ability to:
- use rigorous thought processes to optimize available information,
- justify their selection of relevant data,
- make conscious choices to go deeper or not into the data based on its application,
- uphold appropriate ethics and identify the consequences of using data that is available, and
- avoid pitfalls of blindly following data when presented with an associated compelling narrative.
The student will leave with the ability to apply the practical macro, micro, and alternative data to their analysis, no matter the variant circumstances requiring their newfound skills.
