Finance 651

FINC 651
Financial Analytics: Applications for Data Analysis and Portfolio Construction

1. Catalog Entry

FINC 651
Financial Analytics: Applications for Data Analysis and Portfolio Construction

Credit hours (3)

Applications for Data Analysis and Portfolio Construction, will apply major financial, statistical, and quantitative techniques to analyze big data and construct optimal financial portfolios.  This new course will cover the importance of statistical techniques, advanced econometrics, portfolio theory, and risk/reward interplay to a) understand big data, b) use econometrics to streamline time series, c) develop financial models, and d) analyze and create investment portfolios for individual investors and institutional clients. The course coverage includes use of financial and economic databases, advanced econometrics tools, portfolio theory, SAS and/or Excel and/or SPSS, and research methods in finance.

2. Detailed Description of Course

    1) Databases training: Students will learn how to use existing databases such as Morningstar,
        Bloomberg, The Federal Reserve, and other data sources to download a variety of data that
        will be used for analysis purposes.
    2) Applied econometrics: Students will learn how to use applied statistics such as cleaning of
        data, identification of outliers, streamline a dirty time series of data, data manipulation
        (such as winsorising data, dropping the extreme outliers, converting nonlinear data into
        linear etc.),  regression analysis, and forecasting
    3) Portfolio theory
    4) SAS (and /or Excel and/or SPSS) Training
    5) A Comprehensive Group Research Project (maximum three or four students per group) based
        on databases, portfolio theory, applied econometrics, and software knowledge. The instructor
        will provide research ideas to different groups and also assist groups within the realm of
        instructor support in completing their final projects.

3. Detailed Description of Conduct of Course

It is intended that this course will be first developed as an on campus course, then also offered as a hybrid course and eventually made available entirely online.  

4. Goals and Objectives of the Course

Goal: Students will apply financial analytics techniques for personal and professional investment decisions.  

Objectives:  Students will improve their data analysis skills and use statistical and financial knowledge to develop sound investment decision making approaches.

5. Assessment Measures

Students’ progress will be measured by their performance on assignments, tests and in class presentations of their applications of financial analytics in compliance with Quality Matters Standards.

6. Other Course Information


Review and Approval

May 11, 2015