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Financial Analytics, MS

Program at a Glance

Program

Financial Analytics, MS

Format

Hybrid, Online

Total Units

30

Requirements

No GMAT or
GRE Required

Summer ’24 Early Application Deadline

March 17

Program Overview

Golden Gate University is located at the nexus of finance and technology in San Francisco’s business district. As the finance industry rapidly invents new paradigms in the face of economic change, GGU prepares students to be leaders in the global business world. The Masters of Science in Financial Analytics degree will equip you with the business analytics skills you need to address the challenges of today’s technology-intensive finance industry.

The MS in Financial Analytics is a specialized, technical program that provides in-depth exposure to principles and practices of corporate finance and business analytics.  You’ll learn programming, data analysis, business valuation and financial modeling. You’ll leave the program with a highly developed and practiced ability to make strategic decisions using the latest tools in technology, data analysis, business and finance.

Our hands-on faculty are leading practitioners in the fields of business, finance, and technology from the Bay Area and beyond. Our current roster of adjunct faculty hold day jobs at Wells Fargo, J.P. Morgan, Facebook, BridgeBio, RGB Spectrum, and B. Riley FBR, Inc.

Admission Requirements

  • Applicants should hold a bachelor’s degree from a regionally accredited US institution or the equivalent from a recognized foreign (outside the US) institution, and provide official transcripts.
  • Applicants whose native language is not English must meet the English Language Proficiency Admission Requirements.
  • Applicants with an undergraduate GPA below 3.00 should submit a statement of purpose and a resume.
    The statement of purpose should address the circumstances that may have led the applicants to poor academic performance, what had changed and why they think they’ll be successful now.

Proficiency Requirements

Math Proficiency

Intermediate Algebra (Math 20); See Graduate Mathematics Proficiency Requirement for more information.

Writing Proficiency

Students are expected to possess proficiency in writing to ensure they can be successful in their course of study. Students may meet this requirement by satisfying one of the screening criteria listed under Graduate Writing Proficiency Requirement.

Curriculum

The Master of Science in Financial Analytics requires completion of 6 units in the foundation program and 30 units of advanced program coursework, with a cumulative grade-point average of 3.00 or better in courses taken at Golden Gate University that are applicable to the program’s requirements. For further information regarding graduation requirements, see Degree Requirements for Graduate Programs. Courses carry three semester units of credit unless otherwise noted.

All course prerequisites must be satisfied prior to enrolling in a given course and are indicated in the the course description for each course. Individual foundation program courses may be waived if students have previously completed comparable courses at a regionally accredited college or university. Students may enroll in advanced program courses before they have completed the entire foundation program (provided they have met any course prerequisites) but must complete the foundation program by the time that they have enrolled in 12 units in the advanced program.

Learning Outcomes

Graduates of the MS in the Financial Analytics degree program will have the knowledge and skills to:

  • Evaluate and explain financial decisions regarding the firm’s investment and long- and short-term financing strategies by applying financial theory, quantitative decision-making tools, and analytical methods.
  • Apply economic analysis to the firm’s decision-making, considering the impact of markets, institutions, and international trends on these decisions.
  • Define and measure business and financial risk. Describe the relationship between risk and return, and distinguish between expected and required returns. Explain how risk affects the valuation of real and financial assets, and describe techniques for managing risk.
  • Interpret and analyze individual business problems using data, selecting the best analytic approach and appropriate tools for extracting value from the data available. Use visual outcomes of analytics to communicate effective messages and recommendations for management teams.
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