MASTER OF SCIENCE IN FINANCIAL ANALYTICS

Program Overview

This STEM-designated program in Financial Analytics combines finance, data science, and technology to equip graduates with the skills to analyze financial data, build optimized portfolios, and forecast future financial scenarios. The curriculum includes courses in financial strategy, computational finance, portfolio management, fixed income analytics, and data analysis. Graduates are well-prepared for careers in financial analysis, portfolio management, and data science.

Program Outline

Outline:

Curriculum:

• FIN 5303 Financial Strategy and Decision Making:
• Covers fundamental concepts like time value of money and risk-return relationships.
• Analyzes financial decisions of modern businesses using financial theories.
• Includes topics like capital budgeting, long-term financing, dividend policy, etc.
• FIN 5113 Computational Finance & Financial Modeling:
• Introduces students to Excel VBA, Monte Carlo simulation, efficient frontier, etc.
• Covers topics like portfolio optimization, asset pricing models, capital budgeting decisions, yield curves, etc.
• FIN 5213 Portfolio & Risk Management:
• Integrates programming and data analytics to calculate portfolio performance parameters and build optimized portfolios.
• Covers security fundamental analysis with ratios and uses the Index Model.
• Discusses risk measures like Value at Risk (VaR), Conditional Tail Expectations (CTE), and Lower Partial Standard Deviation (LPSD).
• Also covers risk management strategies through hedging.
• FIN 5313 Fixed Income Analytics:
• Introduces fixed income products and markets.
• Covers topics like duration/convexity and price approximation, term structure of interest rates, various types of bonds, federal funds and LIBOR products, etc.
• FIN 5413 Applications in FinTech:
• Explores the disruptive impact of new technologies like AI, deep learning, blockchain, and open APIs on the financial services industry.
• Includes topics like payments, credit, trading, and risk management.
• ECON 5313 Data Analysis for Business Decisions:
• Covers topics like data description, confidence intervals, hypothesis testing, regression analysis, predictive modeling, etc.
• Uses spreadsheet, statistical, and simulation software.
• Teaches programming fundamentals for data science and analytics solutions development.
• May include software platforms like Python or R.
• IT 5313 Data Visualization:
• Teaches communication of data science results using visualization software like Tableau, PowerBI, etc.
• IT 5213 Data Engineering:
• Covers systems for collecting, storing, and retrieving data with a focus on relational databases.
• May include Snowflake, SQL SERVER, MySQL.
• IT 5413 Forecasting:
• Includes time series analysis and forecasting, and application of these techniques to support business decision-makers.

Prerequisites:

None

Application Requirements:

• Applicants must demonstrate basic understanding of analytical techniques and strong communication skills.

Other:

Campus:

• Located minutes from downtown Oklahoma City.
• Meinders School of Business contains cutting-edge technology in teaching rooms, executive classrooms, conference rooms, computer labs (including Bloomberg Finance Lab), breakout rooms, and a 250-seat auditorium.
• The program is designated as STEM.
• Graduates are well-prepared to think critically, apply analytic tools, answer specific business questions, and forecast future financial scenarios for organizations.