ACCT451 – Data Analytics in Capital Markets

Open Closing on January 2, 2025
McGill University
Montreal, Quebec, Canada
Julia Ayim She / Her
Industry Liaison
(1)
6
Timeline
  • February 2, 2025
    Experience start
  • February 4, 2025
    Student form teams
  • February 15, 2025
    Student teams review the list of projects and apply based on interest
  • February 18, 2025
    First meeting with the industry partner
  • March 15, 2025
    Second meeting with the industry partner
  • April 26, 2025
    Final report ready
  • April 26, 2025
    Experience end
Experience
1/7 project matches
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries
Categories
Financial services Data analysis Competitive analysis
Skills
capital markets market dynamics financial risk statistical methods financial data data analysis communication bankruptcies
Learner goals and capabilities

Student groups employ statistical methods to analyze quantitative and qualitative financial data, including bank communications, financial news, and bankruptcy reports. Students then draw conclusions about real-world financial implications, such as factors that increase financial risk and how news media might impact market dynamics.

Learners
Undergraduate
Beginner, Intermediate, Advanced levels
30 learners
Project
15 hours per learner
Educators assign learners to projects
Teams of 4
Expected outcomes and deliverables

Students will submit a 12–18-page report on the group project analysis and their recommendations.

Project timeline
  • February 2, 2025
    Experience start
  • February 4, 2025
    Student form teams
  • February 15, 2025
    Student teams review the list of projects and apply based on interest
  • February 18, 2025
    First meeting with the industry partner
  • March 15, 2025
    Second meeting with the industry partner
  • April 26, 2025
    Final report ready
  • April 26, 2025
    Experience end
Project Examples

. In this project, you will provide financial data from your organization and can consult with students and the instructor to identify a research direction. For example, students can compare financial data from your organization with global datasets to assess the likelihood of risk when onboarding a client or launching a product.