The Financial Mathematics major, which is interdisciplinary among the Mathematics, Computer Science, and Economics/Finance programs, prepares students for careers in the financial services and actuarial industries. Possible rewarding careers resulting from this major include financial planner, private wealth manager, investment manager (for a mutual fund, pension plan, or endowment), and actuary.
There is currently a serious shortage of individuals who have sufficient training in mathematics and statistics as well as an understanding of business and finance/economics. Companies that employ operations research analysts or actuaries cannot fill their positions. Mathematical Finance and related areas have often been referred to as engineering for the service sector or “financial engineering.” With the ever-increasing importance of the service section in the current economy, this mathematical finance degree will prove to be a valuable asset. The program will give the student an opportunity to study a fascinating collection of ideas and will provide the student with highly marketable skills.
Mth 211: Calculus I
In-depth coverage of calculus appropriate for study in mathematics, science, engineering, or other quantitative disciplines. Covers functions, limits, derivatives, applications of derivatives, and foundations of integral calculus.
Eco 201: Economic Concepts I (Macroeconomics)
An introduction to the functions of an economic system with an emphasis on income determination and government policy.
CS110: Programming I
This is an entry-level programming course (no prior programming experience needed) that introduces programming using a high-level language such as C++. Students will be taught how to design, code, debug, and document programs using structured techniques and good programming styles. Students will be able to sit the C Programming Language Certified Associate (CLA) certification exam.
Acc 201: Principles of Accounting I
An introduction to financial accounting that explains the accounting principles and procedures used to record and report economic events of a business entity. Financial accounting focuses on the preparation of accounting information for users outside the business entity.
Acc 202: Principles of Accounting II
A continuation of the introduction to financial accounting principles and an introduction to managerial accounting. Managerial accounting focuses on the preparation and use of accounting information by management.
Fin 308: Financial Principles
An introduction to the basic principles, concepts, and analytical techniques of finance. Major topics include financial analysis and planning, working capital management, capital budgeting, cost of capital, and sources of capital.
Fin 314: Managerial Finance
This course uses cases to reinforce finance principles and to develop further areas such as financial analysis and planning, working capital management, capital budgeting, and capital structure.
Fin 401: Investments and Derivatives
This course is designed to introduce the students to the general investment media, the analysis of these alternative investments, both individually and in a portfolio context, and the operations of the securities markets.
Fin 415: Advanced Financial Topics
The path-breaking advances in finance theory and practice over the past decades have profoundly changed the financial world. This is an advanced course in financial theory. The objective of the course is to increase the student’s knowledge and understanding of security analysis and portfolio management. The course is lecture based but includes class discussion. Lectures will cover both theory and examples. Homework assignments will focus on applying the material from lectures. Major topics covered include bond prices and yields, management of bond portfolios, macroeconomics and industry analysis, equity valuation, options markets and valuation, future markets and risk management, and performance evaluation and active portfolio management. REQUIRED Capstone Course for Financial Mathematics Majors; Major Subject Elective for Business and Finance Majors.
Eco 202: Economic Concepts II (Microeconomics)
An introduction to the functions of an economic system with an emphasis on decision-making by individuals and firms in a market economy.
Eco 418: Mathematical Methods in Economics
A survey course designed to develop those mathematical results and methods that find frequent use in economic analysis.
BAd 318: Business Statistics
Fundamental concepts and methods of statistics covering frequency distributions, measures of central tendency and dispersion, probability, probability distributions, sampling, estimation, statistical quality control, quantitative decision making, hypothesis testing, correlation analysis, regression analysis, and non-parametric statistics.
Mth 313: Probability and Statistics
Probability axioms, discrete and continuous distributions, expectation, multivariate distributions, estimation, hypothesis testing, regression analysis, and analysis of variance.
Mth 212: Calculus II
In-depth coverage of calculus appropriate for study in mathematics, science, engineering, or other quantitative disciplines. Covers integration techniques, applications of integration, sequences and series, and polar coordinates.
Mth 213: Calculus III
In-depth coverage of calculus appropriate for study in mathematics, science, engineering, or other quantitative disciplines. Covers 3-dimensional geometry and extends ideas of calculus into higher dimensional settings.
Mth 305: Differential Equations
A study of the techniques, history, and applications of ordinary and partial differential equations. Topics included are linear equations, infinite series solutions, systems of linear equations, numerical techniques, and partial differential equations.
Mth 308: Linear Algebra
Geometric vectors, vector spaces, inner products, linear transformations, matrices with applications to solutions of systems of equations, linear transformations, and determinates.
Mth 340: Numerical Analysis
Numerical representation, solution of single non-linear equations, linear equations, interpolation and approximations of numerical methods of integration.
CS 330: Theory of Computation
This course addresses questions like What kind of problems can be algorithmically solved? and What are the limits of what a computer can compute? Students are introduced to a variety of issues in the mathematical development of computer science theory, particularly finite representations for languages and machines and Turing Machines. They also learn to determine the complexity and computability of algorithms, thereby obtaining insights into the capabilities and limitations of the computing machines.
Mth 415: Operations Research
Applications of the scientific method to the optimal management of human-nature-machine systems. Topics included are linear programming, sensitivity analysis, networks, inventory models, queues, integer, and nonlinear programming.
CS 351: Computer Modeling
The course introduces the basic concepts of computation through modeling and simulation that are increasingly being used to shorten design cycles, innovate new products, and evaluate designs and simulate the impacts of alternative approaches. Students learn different modeling methods and conduct a detailed examination of four problem-solving aspects: finding and gathering necessary information, envisioning an appropriate model to address desired goals, implementing the model using appropriate software tools (spreadsheets, statistical packages, symbolic manipulators, simulation packages, programming languages), and testing/analyzing the model.
CS 111: Programming II
This course introduces the principles and practices of Object Oriented Programming, using at least two OOP languages such as C++ and JAVA. The course also continues to build on the students’ experience with control structures (i.e., selection, iteration, and recursion), data types (e.g. arrays, strings, pointers, and dynamic structures), and fundamental algorithms for operations such as sorting and searching. Students will be able to sit the C++ Certified Associate Programmer (CPA) exam.
CS 210: Data Structures and Algorithms
This course investigates the development and use of basic data structures and algorithms, which are used as tools in designing computer solutions to problems. It covers topics such as arrays, stacks, queues, trees, sorting, searching, and graphs. Students will become familiar with the specification, usage, implementation, and analysis of these data structures and algorithms.
