This three-credit undergraduate course introduces students to financial applications of R programming. This course demonstrates how to use R for analyzing data and financial modeling. Using practical examples and real world data, students will learn basics of R programming, descriptive data analysis, regression analysis, time series analysis, and portfolio optimization.
This is not a lecture-based class. Instead, we will go through certain examples in each class covering important features of R. You are expected to bring your own computer and follow along in the class. Each week, students will be assigned a mini-project which is due before the class on next Monday. The students are expected to spend at least 6 hours per week outside of class reading, reviewing, and working on course assignments.
FIN 3826 Fundamentals of Asset Management. No prior programming knowledge is assumed.
No required textbook. Free e-books “R Programming for Data Science” and “Exploratory Data Analysis with R” by Roger D. Peng, available at: biostat.jhsph.edu/~rpeng/books.html, are useful references.
You will receive an invite via email to join the class home page in the RStudio Cloud. You will use RStudio Cloud to run all in class programs and submit programming homework assignments.
Overall score in the course will be determined mechanically as the weighted average of the component scores. Overall grade will be determined by where overall score lies in the distribution of all students’ overall scores. The cut-offs in the distribution will be such that roughly 35% of the students receive “A”s, 40% receive “B”s, and 25% receive grades below “B”. The exact curve cut-offs will depend on the level and shape of the score distribution. Although grading is relative, you should get an A if you score above 90%. 80% and above should ensure a B grade.
All relevant University policies (including, but not limited to, policies on academic integrity, attendance, etc.) apply to this course. In the case of any conflict between the policies in this syllabus and University policy, University policy applies. We reserve the right to revise, alter, and/or amend this syllabus as necessary. Students will be notified by email of any such revisions, alterations, and/or amendments.
According to section 10.1 of the LSU Code of Student Conduct, “A student may be charged with Academic Misconduct” for a variety of offenses, including the following: unauthorized copying, collusion, or collaboration; “falsifying” data or citations; “assisting someone in the commission or attempted commission of an offense”; and plagiarism, which is defined in section 10.1.H as a “lack of appropriate citation, or the unacknowledged inclusion of someone else’s words, structure, ideas, or data; failure to identify a source, or the submission of essentially the same work for two assignments without permission of the instructor(s).”
According to the our General Catalogue, “The Office of Disability Services assists students in identifying and developing accommodations and services to help over-come barriers to the achievement of personal and academic goals. Services are provided for students with temporary or permanent disabilities. Accommodations and services are based on the individual student’s disability-based need. Students must provide current documentation of their disabilities. Students should contact the office early so that necessary accommodations can be arranged.”
If you have a documented disability and anticipate needing accommodations in this course, please make sure during the first week of the term that you have registered your disability with the LSU Office of Disability. Once you are registered, please request that an accomodation letter verifying your disability be sent to us. Students with infants or young children that need ongoing care should similarly come and see us. We’ll have to take it on a case-by-case basis, we will do our utmost to accommodate you.