Curriculum

                                            Curriculum by Applicant Year

SAMPLE MSQF ELECTIVES (6 CREDIT HOURS)

CYBR 661: Cybersecurity Policy, Issues and Operations (3)

Overview related to U.S. homeland defense and homeland security; includes cyber threats; cyberwar; securing cyberspace in public and private sector; protecting data, systems and networks that are connected to the Internet and the Internet of Things.

FINC 661: Trading Risk Management (3)

Focuses on Mid-office risk management strategies using the energy markets as a focus; develops understanding of commodity market behavior, use of forwards and options for risk management, risk management reporting, Greeks and simulation-based VaR analysis. Classification 6 students may not enroll in this course.

FINC 602: Corporate Finance (3)

Theoretical development of principles of corporate financial management; application of principles to problems faced by financial officers, such as capital budgeting, cost of capital, capital structure, dividend policy, financial distress and corporate valuation.

FINC 689: Quantitative Investing (3)

 

FINC 688: Theory of Finance (3)

Historical development of the conceptual framework of finance theory and practices; analysis of current research and controversial issues in the field.

ISTM 635: Business Information Security (3)

Explores the business, managerial, and technological aspects of information security; analysis, design, and implementation issues surrounding effective information security; authentication, authorization, availability, business continuity planning, confidentiality, disaster recovery, encryption, firewalls, fraud protection, security policy development, integrity, risk management, virus protection, VPNs and wireless security. Classification 6 students may not enroll in this course.

ISTM 645: IT Security Controls (3)

Familiarization with planning, design, and implementation of controls to minimize risks to business information; focus on the importance of managing business information security; introduction to the tools, concepts and theories to safeguard an organization’s information systems and IT assets; understanding of cryptography and application, operations, and physical security.

ISTM 655: Security Management and Compliance (3)

Familiarization with managerial and legal aspects of business information security; focus on importance of managing business information security and theories to help safeguard an organization’s information systems and IT assets; understanding of Security Architecture and Design, Business Continuity and Disaster Recovery Planning, Laws Investigation and Ethics.

MATH 425: The Mathematics of Contingent Claims (3)

The mathematical theory associated with asset price dynamics; binomial pricing models; Black-Scholes analysis; hedging; volatility smile; implied volatility trees; implied binomial trees.

MATH 609: Numerical Analysis (4)

Interpolation, numerical evaluation of definite integrals and solution of ordinary differential equations; stability and convergence of methods and error estimates.

MATH 619: Applied Probability (3)

Measure Theory; Lebesgue integration; random variables; expectation; condition expectation martingales and random walks; designed for beginning graduate students in mathematics, statistics, the sciences and engineering and students in economics and finance with a strong mathematical background.

MATH 625: Applied Stochastic Differential Equations (3)

Stochastic integration, Ito Calculus and applications of stochastic differential equations to finance and engineering.

MATH 647: Mathematical Modeling (3)

The process and techniques of mathematical modeling; covers a variety of application areas and models such as ordinary and partical differential equations, stochastic models, discrete models and problems involving optimization.

MATH 644: Topics in Mathematical Data Science (3)

Problems, methods and recent developments in applied mathematics.

MATH 651: Optimization I (3)

Fundamentals of mathematical analysis underlying theory of constrained optimizations for a finite number of variables, necessary and sufficient conditions for constrained extrema of equality constraint problems, sufficient conditions for fulfillment of constraint qualification, computational methods for concave programming problems and applications.

MATH 677: Mathematical Foundations for Data Science (3)

Linear systems; least squares problems; eigenvalue decomposition; singular value decomposition; Perron–Frobenius theory; dynamic programming; convex optimization; gradient descent; linear programming; semidefinite programming; compressive sensing.

MATH 679: Mathematical Algorithms and their Implementations (3)

Mathematical theory and implementation with Python of modern algorithms; project based.  Prerequisites:  Math 323 and Math 409 or equivalent, or instructor approval.