FE630 Portfolio Theory and Applications

From Hanlon Financial Systems Lab Web Encyclopedia
Jump to: navigation, search



Course Catalog Description

Introduction

This course introduces the modern portfolio theory and optimal portfolio selection using optimization techniques such as linear programming. Topics include contingent investment decisions, deferral options, combination options and mergers and acquisitions. The course introduces various concepts of nancial risk measures.
Campus Fall Spring Summer
On Campus X X
Web Campus X X

Instructors

Professor Email Office
Papa Ndiaye
Papa.Ndiaye@stevens.edu



More Information

Course Description

This course is an introduction to quantitative portfolio theory, practice, optimization, and management. It addresses investor choice, market opportunities, and optimal portfolio selection. It examines security covariance and return models, performance analysis, and return attribution. It provides also an introduction to some basic methods for robust portfolio construction. The course will also include a computational component in which students will construct optimal portfolios, track their behavior, and analyze their performance.

This course will be taught in a hybrid manner including lectures and Socratic method discussions. Each week, there will be assigned readings. Students must do the readings before class. I will call on on-campus students frequently to explain concepts from the readings. Students’ answers will count toward their grade. Web-campus students who cannot attend classes in real-time will be given small written assignments in lieu of in-class answers. There will be also a number of quizzes that may be taken in class during lecture or remotedely.



Course Resources

Textbook

The following books are recommended (reading assignments may come from below):

  • Francis and Kim, Modern Portfolio Theory, Wiley, 2013. ISBN: 111837052X.
  • Grinold and Kahn, Active Portfolio Management, 2e, McGraw Hill, 1999. ISBN:0070248826
  • Hubert, Essential mathematics for Market Risk Management, 2e, Wiley, 2012. ISBN 9781119979524 An electronic copy of Francis and Kim is available from the library. Both of the other two books are on reserve in the library
  • Prigent, Portfolio Optimization and Performance Analysis, Chapman & Hall/CRC Fiancial Mathematics Seues, , ISBN 1-58488-578-5




Grading

Grading Policies

Attendance and Participation

Attendance is mandatory. The class will be interactive. Students are required to participate and answer questions on the reading assignments.

Homework / Quizzes / Project(s) / Exams

Grades will be based on a combination of quizzes, exams, homework, a project, attendance, and participation.

  • Quizzes. There will be four 15-minute multiple choice quizzes. Additional quizzes may be given
  • Exams. There will be a 3-hour midterm exam or midterm project, and a Final Project.
  • Homework. There will be homework assignments in which students will be tested on both the theory and the application and will have to write programs for portfolio management in both matlab and R. Be prepared for about 4 assignments starting from Week 2. Reading assignments will be given and additional home assignments may be given throughout the semester.
  • Project. Students will form groups of three or less, and each group will be required to manage a hypothetical portfolio for the duration of the course or to build and backtest a portfolio for the final project. Management of the portfolio in accordance with methods taught in class will count toward students’ grades.
  • Attendance and Participation. Attendance is mandatory. The class will be interactive. Students are required to participate and answer questions on the reading assignments.

Grades will be based on:

Class Participation (5%)

Homework (20%)

Quizzes (15%)

Midterm Project or Exam (25%)

Final Project (35%)


Lecture Outline

Topic Reading
Week 1 One-Period Utility Analysis
Week 2 One-Period Utility Analysis & Computational Tools
Week 3 Computational Tools & Optimization Review
Week 4 Optimization Review
Week 5 The Opportunity Set
Week 6 Efficient Frontiers
Week 7 Midterm Exam
Week 8 CAPM, APT, Return Models
Week 9 Robust Allocation
Week 10 Active Portfolios
Week 11 Bond Portfolios
Week 12 Dynamic Portfolio Allocation
Week 13 Analysis
Week 14 Review & Catch-up, Final Projects Presentation