Bachelor of Business Administration (B.B.A.) Major in Economics/ Master of Science (M.S.) Major in Quantitative Finance and Economics (Non-thesis Option)

QFE 5199B. Thesis.

This course represents continuing enrollment for students engaged in thesis research within the graduate program. Work focuses on the development, execution, and completion of an original research project under faculty supervision. Activities include refinement of research questions, literature review, data collection and analysis, and preparation of the written thesis. Emphasis is placed on applying appropriate research methods, maintaining academic rigor, and demonstrating independent scholarly inquiry. Enrollment continues until the thesis is completed and approved according to program requirements. Graded on a credit (CR), progress (PR), no-credit (F) basis.

QFE 5299B. Thesis.

This course represents continuing enrollment for students engaged in thesis research within the graduate program. Work focuses on the development, execution, and completion of an original research project under faculty supervision. Activities include refinement of research questions, literature review, data collection and analysis, and preparation of the written thesis. Emphasis is placed on applying appropriate research methods, maintaining academic rigor, and demonstrating independent scholarly inquiry. Enrollment continues until the thesis is completed and approved according to program requirements. Graded on a credit (CR), progress (PR), no-credit (F) basis.

QFE 5310. Microeconomic Theory and Applications.

This course provides a rigorous introduction to the methods of microeconomic theory and quantitative applications. Topics include consumer and producer theory, decision-making under uncertainty, markets and competition, general equilibrium, and game theory. The course also incorporates applications to empirical research through analysis and replication of quantitative results from academic journal articles. Emphasis is placed on linking theoretical models to observable economic behavior and interpreting quantitative findings within a structured analytical framework. Prerequisite: ECO 2314 and ECO 2315 and FIN 3312 and MATH 1329 and QMST 2333 all with grades of "B" or better.

QFE 5315. Macroeconomic Theory and Applications.

This course examines macroeconomic theory and policy at an advanced level, integrating traditional and modern models of income determination, price dynamics, employment, and long-run economic growth. Topics include business cycle theory, dynamic macroeconomic models, and the roles of monetary and fiscal policy in influencing economic stability. Analysis emphasizes the interaction between theoretical frameworks and empirical evidence, using data to evaluate macroeconomic relationships and policy outcomes. The course also considers contemporary macroeconomic issues and the application of models to real-world economic fluctuations and policy debates. Prerequisite: ECO 2314 and ECO 2315 and FIN 3312 and MATH 1329 and QMST 2333 all with grades of "B" or better.

QFE 5320. Econometrics.

This course introduces econometric methods for analyzing economic data at the graduate level. Topics include probability theory, simple and multiple linear regression, hypothesis testing, nonlinear models, binary outcome models, and panel data techniques. Emphasis is placed on linking statistical theory with empirical modeling to support inference, prediction, and evaluation of economic relationships. Students analyze real-world datasets to assess model performance and interpret results within an economic framework. Statistical software is used to estimate models, conduct diagnostics, and present empirical findings. Prerequisite: ECO 2314 and ECO 2315 and FIN 3312 and MATH 1329 and QMST 2333 all with grades of "B" or better.

QFE 5330. Financial Theory and Corporate Policy.

This course examines foundational theories in finance with emphasis on their application to corporate financial policy and decision-making. Topics include utility theory, state-preference frameworks, mean–variance optimization, asset pricing models, and capital structure decisions. The course analyzes how these theoretical models inform firm valuation, investment decisions, and financing strategies. Option pricing concepts are introduced and applied to corporate finance contexts, including risk management and contingent claims analysis. Emphasis is placed on integrating theoretical frameworks with quantitative methods to evaluate corporate financial decisions in uncertain and dynamic economic environments. Prerequisite: ECO 2314 and ECO 2315 and FIN 3312 and MATH 1329 and QMST 2333 all with grades of "B" or better.

QFE 5335. Financial Analytics.

This course examines the use of open-source programming tools in financial analysis and modeling. Topics include implementation of financial models related to investments and corporate finance, data visualization, and analysis of financial datasets. Emphasis is placed on applying computational methods to evaluate financial problems and interpret results. Students work with real-world data to construct models, analyze financial performance, and generate insights relevant to decision-making. Analytical tools are used to support valuation, risk assessment, and financial forecasting in applied settings.

QFE 5340. Financial Econometrics.

This course examines econometric methods applied to corporate finance and asset pricing using financial data. Topics include estimation and inference in financial models, principal component and factor analysis, capital asset pricing models, volatility modeling, and risk measurement. The course also analyzes derivative pricing, portfolio allocation and optimization, and simulation of financial systems. Emphasis is placed on applying statistical techniques to model financial relationships, evaluate risk, and interpret empirical results. Analytical software is used to estimate models, analyze datasets, and assess model performance in financial applications. Prerequisite: QFE 5320 with a grade of "C" or better.

QFE 5353. Fixed Income Analysis.

This course examines the valuation and analysis of fixed income securities and their derivatives in modern financial markets. Topics include money-market instruments, government and corporate bonds, repurchase agreements, interest rate swaps, and mortgage-backed securities. The course analyzes pricing frameworks, yield measures, and term structure relationships used in fixed income markets. Emphasis is placed on analytic tools for bond portfolio management, including duration, convexity, and interest rate risk measurement. Additional topics include credit risk assessment, securitization, and the role of fixed income instruments in investment and risk management strategies. Prerequisite: FIN 5322 with a grade of "C" or better.

QFE 5369. Internship.

This course integrates graduate-level academic study with supervised professional experience in a finance- or economics-related setting. Students apply advanced theoretical frameworks and quantitative methods to workplace responsibilities, analyzing how economic and financial concepts inform organizational and policy decisions. Emphasis is placed on reflective analysis, professional development, and the evaluation of real-world problems using data-driven and model-based approaches. Students examine the relationship between theory and practice while developing skills relevant to professional environments in finance, economics, and related fields. Prerequisite: Must have completed 12 graduate hours and other prerequisites may be specified by the employer with the consent of Program Director and department chair and instructor approval.

QFE 5390A. International Economics.

This course examines open economy macroeconomics and monetary issues in international economics. Topics include international financial markets, exchange rate determination, trade policies, and international monetary systems. The course also covers financial crises, contagion effects, and the interaction between macroeconomic policy and global financial conditions. Emphasis is placed on applying theoretical models to empirical data to analyze international macroeconomic and financial behavior. Analytical tools are used to interpret exchange rate movements, capital flows, and cross-border economic activity in a global context. Prerequisite: ECO 2314 and ECO 2315 and FIN 3312 and MATH 1329 and QMST 2333 all with grades of "B" or better or advisor approval.

QFE 5390C. Big Data in Economics and Finance.

This course examines big data techniques for analyzing financial markets and economic phenomena. Topics include Python programming, data acquisition, and machine learning methods such as factor models, regularization, dimensionality reduction, and neural networks. Emphasis is placed on predictive modeling, model validation, and the analysis of complex, high-dimensional datasets. Students implement quantitative models to evaluate financial and economic data and assess their performance in applied settings. Analytical tools are used to support data-driven decision-making in finance and economics. Prerequisite: QFE 5320 with a grade of a "C" or better.

QFE 5392A. Financial Markets and Institutions.

This course focuses on U.S. financial markets and institutions, with additional consideration of international counterparts. Topics include the structure and functions of money and capital markets, equity and debt markets, and the roles of financial intermediaries. Analysis covers interest rate determination, term structure relationships, and the interaction between financial markets and institutions. The course also examines regulatory frameworks, central banking policies, and their influence on market behavior, financial stability, and economic activity. Emphasis is placed on applying analytical tools to evaluate market developments, institutional performance, and policy impacts in a dynamic financial environment. Prerequisite: ECO 2314 and ECO 2315 and FIN 3312 and MATH 1329 and QMST 2333 all with grades of "B" or better or advisor approval.

QFE 5392C. Active Portfolio Management.

This course examines the practical application of modern portfolio theory in active investment management. Topics include signal extraction, return forecasting, portfolio construction, and risk control using quantitative methods. Analysis focuses on identifying and evaluating predictive signals from financial data and transforming them into investment strategies. Economic, econometric, and operations research techniques are used to address complex portfolio allocation and optimization problems. Emphasis is placed on integrating forecasting models with risk management frameworks to guide active portfolio decisions. Students evaluate portfolio performance and assess the effectiveness of investment strategies in dynamic market environments. Prerequisite: QFE 5330 and QFE 5320 both with grades of "C" or better or advisor approval.

QFE 5392D. Financial Derivatives with Python.

This course examines the theoretical foundations and computational methods used in the pricing and risk management of financial derivatives. Topics include arbitrage pricing, replication, binomial and lattice models, stochastic processes, Itô calculus, risk-neutral valuation, and the Black–Scholes framework. Numerical techniques such as Monte Carlo simulation and finite-difference methods are applied to derivative valuation and portfolio risk analysis. Emphasis is placed on implementing quantitative models in Python to analyze volatility, estimate Value at Risk (VaR), and conduct scenario-based risk assessments. Analytical tools, including AI-assisted coding support, are evaluated for their effectiveness and limitations in quantitative finance applications. Prerequisite: QFE 5330 and QFE 5320 both with grades of "C" or better or instructor approval.

QFE 5392E. Artificial Intelligence in Finance.

This course examines the application of artificial intelligence and machine learning in finance. Topics include data organization, feature engineering, predictive modeling, and evaluation of algorithmic performance in financial contexts. Methods such as supervised and unsupervised learning, deep learning, and large language models are applied to problems in capital markets, credit risk modeling, and real estate analysis. Emphasis is placed on using advanced computational techniques to extract insights from financial data and support decision-making. Students analyze real-world datasets and assess the effectiveness and limitations of AI-based approaches in financial applications. Prerequisite: QFE 5335 with a grade of "C" or better.

QFE 5395. Independent Study.

This course allows graduate students to engage in independent, faculty-guided study of a selected topic or applied area in quantitative finance and economics. Emphasis is placed on advanced analytical inquiry, development of specialized knowledge, and application of theoretical and quantitative methods to complex problems. Students conduct focused research or applied projects using relevant data sources, modeling techniques, and computational tools. The course supports exploration of topics beyond regularly offered coursework and promotes independent scholarship and professional skill development. This course may be repeated once for credit with different emphasis. Prerequisite: instructor and program director.

QFE 5399A. Thesis.

This course represents continuing enrollment for students engaged in thesis research within the graduate program. Work focuses on the development, execution, and completion of an original research project under faculty supervision. Activities include refinement of research questions, literature review, data collection and analysis, and preparation of the written thesis. Emphasis is placed on applying appropriate research methods, maintaining academic rigor, and demonstrating independent scholarly inquiry. Enrollment continues until the thesis is completed and approved according to program requirements. Graded on a credit (CR), progress (PR), no-credit (F) basis.

QFE 5399B. Thesis.

This course represents continuing enrollment for students engaged in thesis research within the graduate program. Work focuses on the development, execution, and completion of an original research project under faculty supervision. Activities include refinement of research questions, literature review, data collection and analysis, and preparation of the written thesis. Emphasis is placed on applying appropriate research methods, maintaining academic rigor, and demonstrating independent scholarly inquiry. Enrollment continues until the thesis is completed and approved according to program requirements. Graded on a credit (CR), progress (PR), no-credit (F) basis.

QFE 5599B. Thesis.

This course represents continuing enrollment for students engaged in thesis research within the graduate program. Work focuses on the development, execution, and completion of an original research project under faculty supervision. Activities include refinement of research questions, literature review, data collection and analysis, and preparation of the written thesis. Emphasis is placed on applying appropriate research methods, maintaining academic rigor, and demonstrating independent scholarly inquiry. Enrollment continues until the thesis is completed and approved according to program requirements. Graded on a credit (CR), progress (PR), no-credit (F) basis.

QFE 5999B. Thesis.

This course represents continuing enrollment for students engaged in thesis research within the graduate program. Work focuses on the development, execution, and completion of an original research project under faculty supervision. Activities include refinement of research questions, literature review, data collection and analysis, and preparation of the written thesis. Emphasis is placed on applying appropriate research methods, maintaining academic rigor, and demonstrating independent scholarly inquiry. Enrollment continues until the thesis is completed and approved according to program requirements. Graded on a credit (CR), progress (PR), no-credit (F) basis.