Statistical methods in estimating and testing economic models; single and simultaneous equation estimation, identification, forecasting, and problems caused by violating classical regression model assumptions.

Units: 3
Usually offered: Fall, Spring
Grading: Regular Grading
May be convened with: ECON 518

Forecasting techniques used in business and government; assembly, interpretation and use of economic data; analysis of business conditions; examination of related environmental factors; construction of actual sales or revenue forecasts.

Units: 3
Usually offered: Fall
Grading: Regular Grading

This course expands on and applies key methods and tools introduced in FIN 301 Principles of Financial Management, with an additional emphasis on analysis and applications in Microsoft Excel. This course challenges you to apply your expanded learning to the subject company for more detailed analysis. More advanced methods will be introduced for solving time value of money problems, analyzing financial statements, and valuing stocks and bonds. Additionally, we cover the following key topics in corporate finance: capital budgeting, short-term financial planning, working capital management, and international finance.

Units: 3
Usually offered: Summer
Grading: Regular Grading

This course is only available to Finance/Business Analytics double-majors, as the prerquisites of FIN 412 and 421 are enforced. 

The primary objective of this course is to "marry" corporate finance theory with practice. You should develop the ability to use finance concepts to solve practical finance problems. In particular, we will focus on the use of a spreadsheet (e.g., Microsoft Excel) to develop models that can be used in the financial decision-making process. Therefore, in addition to learning and applying finance concepts, you will also improve and refine your computer skills. You will use Excel to build capital budgeting and financial planning models, examine capital structure issues and risk/return tradeoffs, and perform financial statement (ratio) analysis. Available only to Finance majors.

Units: 3
Prerequisite(s): FIN 412 (grade of C or better), FIN 421 (grade of C or better)
Usually offered: Fall, Spring
Grading: Regular Grades

Business intelligence and analytics and the related field of big data analytics have become increasingly important in both the academic and the business communities over the past two decades. The IBM Tech Trends Report identified business analytics as one of the four major technology trends in the 2010s and beyond. A report by the McKinsey Global Institute predicted that by 2018, the United States alone will face a shortage of 140,000 to 190,000 people with deep data analytical skills, as well as a shortfall of 1.5 million data-savvy managers with the know-how to analyze big data to make effective decisions. Big data and data science have begun to transform different facets of the society, from e-commerce and global logistics, to smart health and cyber security.

This undergraduate senior level course (elective) will cover the important concepts and techniques relating to data analytics, including: statistical foundation, data mining methods, data visualization, and web mining techniques that are applicable to emerging e-commerce, government, health and security applications. The course contains lectures, readings, lab sessions, and hands-on projects. Most business school seniors are welcome. The course will require some basic computing and database background. The course will prepare students to become a data scientist or a data-savvy manager for different businesses.

Units: 3
Usually offered: Spring
Grading: Regular Grades

Decision Support Systems can be defined as 'computer based systems that use data and quantitative models to solve problems and to help managers make decisions.' This is a course on making quantitative decisions. The course introduces the student to optimization methods (linear, integer, nonlinear programming and network models) used in business, decision support via Monte Carlo simulation, and decision making under uncertainty/risk. These concepts are studied in the context of applications in strategic planning, operations/supply chain management, information systems, and other areas of business. Spreadsheets are intuitive and user-friendly platforms for organizing information. Hence, spreadsheets have become indispensable tools of modern business analysis. This course focuses on structuring, analyzing, and solving managerial decision problems using Excel spreadsheets. Specifically, we address problems from operations management (e.g., resource allocation, revenue management, transportation and logistics, outsourcing production) and information systems (e.g., advertising response, media selection model), along with and several other business problems from finance and marketing. In each area, we consider specific managerial decision problems, model them on Excel spreadsheets, analyze and solve the models, and then interpret the solutions obtained. As an added benefit of this course, we will learn to use advanced features of Excel. This includes some of the built-in functions, named ranges, pivot tables, charts, conditional formatting, and some simple macros.

Units: 3
Usually offered: Spring