FA800 Project in Financial Analytics



Course Catalog Description

Campus Fall Spring Summer
On Campus
Web Campus

Instructors

Professor Email Office
Ionut Florescu
ifloresc@stevens.edu Babbio 544

Instructions

Instructions for enrollment

To enroll in this class the student needs to submit a request via workday to override pre-requisites for FA/FE 800. Proceed as follows: Please log in to workday and type in the search bar “pre-requisite course override”. Fill all of the information required, select FA 800, and then answer the questions in this questionnaire. Please type in the comment box “completing requirements for FA program”. Once submitted, the form will be routed to the faculty member teaching the class. The faculty knows and once the approval is received the student will be notified that approval is received. Once this email is received the student NEEDS TO GO BACK and register for the course. The system still requires you to actively select the class and register.


More Information

Course Objective

This course is designed for FA students undertaking a research or analytical project either individually or as a group. The project may be suggested either by faculty members or industry senior managers associated with your internship, as well as any internship that a student may receive through this course. The goal of this course is to train students' ability to work on a research-oriented project in a group environment, and also train their professional presentation and scientific writing skills.

Project Types

The projects covered by this course are typically one of the following three types:

  1. Research projects are typically oriented toward the field of Mathematical Financial Engineering. Some examples include:

    • Statistical Modeling of Trading Strategies
    • Credit Derivative Arbitrage
    • Dynamic Portfolio Allocation Methods
    • Optimal Hedging Monte Carlo
    • Regulatory Research (Basel III, CVA, etc.)
    • Stochastic Volatility modeling
    • Volatility trading strategies

  2. Analytics projects typically involve Software Design and Implementation. Some examples include:

    • High Frequency Market and client implementation
    • News Analytics
    • Rare events automated discovery
    • Regulatory (Basel III, CVA) Software Design and Implementation

  3. Industry projects are geared toward solving problems arising in industry and are generally proposed by our industry partners. Some examples include:

    • UBS project on Credit Rating
    • Machine learning Projects from Bank of America

Project Approval

The project chosen and developed throughout the semester must be:

  1. A project proposed by a faculty member,
  2. A project proposed by an industry supervisor and approved by the course instructors, or
  3. A project proposed by a student and approved by the course instructors.

Web Section

The Web section students are encouraged to attend the class at the same time as the on campus students. If there is a conflict with work, then the students can check the recording of the lectures. Note that we do the oral presentations (weekly updates, phase 1&2 presentations) during class time. The students will be given the opportunity to present through the Zoom. In the occasion that the student can not present during the class time, please contact the instructor and TA beforehand to arrange for the presentation through other means.


Grading

Grading Policies

The final grade will be assigned according to the scheme in Table 1.

Table 1: Grading Scheme
Item Due Date Grade
Abstract, Schematics, and Literature Review Week 4 10%
Phase One Presentations Week 8 15%
Phase Two Presentations Week 12 15%
Final Written Report Due During finals week 30%
Final Oral Presentation TBD during finals week 20%
Attendance Throughout semester 10%

Additionally, you will be required to give a status and progress report about the project in a presentation format every week of the semester, unless that class time is reserved for the phase 1 or phase 2 presentations. The weekly updates are not graded but the comments received will help guide you in your development of the project.

Late submissions will strictly not be accepted without prior notice and permission of the instructor. If outside circumstances are affecting your ability to perform in the course, you must contact the professor before you fall behind.