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									                                  Quantitative Financial Analysis
                                  2 credits

                                  BU.230.710.xx
                                  Class Day/Time & Start/End Date

                                  Semester
                                  Class Location



Instructor
Full Name

Contact Information
Phone Number: (###)###-####
E-mail Address:

Office Hours
Day/s    Times

Required Text and Learning Materials:
Stochastic Simulation and Applications in Finance with MATLAB Programs, (2008), Huu Tue Huynh, Van
Son Lai, Issouf Soumare (HLS)
                                             th
MATLAB: An Introduction with Applications 4 Edition (2010) or earlier Editions, Amos Gilat (AG)

Software: Matlab, student version (provided by Carey)

Optional Reference Book:
                                         th   th
Options, Futures and Other Derivatives, 7 or 8 Edition, John C. Hull

Blackboard Site
A Blackboard course site is set up for this course. Each student is expected to check the site throughout
the semester as Blackboard will be the primary venue for outside classroom communications between the
instructors and the students. Students can access the course site at https://blackboard.jhu.edu. Support
for Blackboard is available at 1-866-669-6138.

Course Evaluation
As a research and learning community, the Carey Business School is committed to continuous
improvement. Therefore each student must complete the course evaluation as part of the continuous
improvement process. Information on how to complete the evaluation will be provided near the end of the
course.

Disability Services
Johns Hopkins University and the Carey Business School are committed to making all academic
programs, support services, and facilities accessible. To determine eligibility for accommodations, please
contact the Carey Disability Services Office at time of admission and allow least four weeks prior to the
beginning of the first class meeting. Students should contact Rachel Hall in the Disability Services office
by phone at 410-234-9243, by fax at 443-529-1552, or email: carey.disability@jhu.edu.

Important Academic Policies and Services
    Honor Code
    Statement of Diversity and Inclusion
    Tutoring
                                     BU.230.710.xx– Quantitative Financial Analysis – Instructor’s Name – Page 2 of 4



     Carey Writing Center
     Inclement Weather Policy
Students are strongly encouraged to consult the Johns Hopkins Carey Business School Student
Handbook and Academic Catalog and the School website http://carey.jhu.edu/syllabus_policies for
detailed information regarding the above items.

Course Description:
This course is intended to deal with the fundamentals of Monte Carlo simulation techniques and their
applications in finance. Using Matlab as the programming platform, this course will expose students to
hands-on computer exercises on advanced quantitative topics. This course will train students to become
familiar with simulation techniques in modern financial engineering. Matlab is widely used in many
science disciplines and is also emerging as one of the most popular programming platforms in the
financial industry.

Course Overview:
The past financial crisis showed how difficult it is to correctly price financial instruments. In the course,
students will learn how to apply stochastic calculus and simulation techniques to solve financial problems
and also how to develop and/or adapt the existing contingent clam models to support financial
engineering platforms and applications. The coverage of options pricing and interest rate derivatives
builds heavily on what you learned in Derivatives. Course topics are as follows,

       MATLAB
       Monte Carlo Simulations
       Options Pricing
       Interest Rate Derivatives
       Credit Derivatives
       Value at Risk

Student Learning Objectives for This Course
All Carey graduates are expected to demonstrate competence on four Learning Goals,
operationalized in eight Learning Objectives. These learning goals and objectives are supported
by the courses Carey offers. For a complete list of Carey learning goals and objectives, please
refer to the website http://carey.jhu.edu/LearningAtCarey/LGO/index.html.

The learning objectives for this course are:
   1. You should be able to write an efficient Matlab code.
   2. You should be able to perform Monte Carlo Simulations.
   3. You should be able to price options and other derivatives.
   4. You should be able to compute Value at Risk.
   5. You should be able to analyze term structure models.
   6. You should be able to asses credit risk.

Attendance Policy
Attendance and participation are part of your course grade. Students are expected to attend all scheduled
class sessions. Each class will include programming exercises. Failure to attend class will result in an
inability to achieve the objectives of the course. Excessive absence will result in loss of points.

Assignments
There will be six homework assignments, each worth 7%. Please see their assigning and due dates in the
course calendar. All programming assignments should be emailed to TA, and the names of your files
should always start with “DC_” and end with “_your last name” (example: DC_HW1_StuUrban ).

        Homework #1: MATLAB computation and programming

        Homework #2: MATLAB computation and programming
                                    BU.230.710.xx– Quantitative Financial Analysis – Instructor’s Name – Page 3 of 4




        Homework #3: Probability, MATLAB computation and programming

        Homework #4: Monte Carlo simulation

        Homework #5: Valuing options

        Homework #6: Interest rate and credit derivatives


Evaluation and Grading
 Assignment                                                   Learning Outcome            Weight
 Attendance and participation*                                1, 2, 3, 4, 5, 6            10%
 Homework**                                                   1, 2, 3, 4, 5, 6            42%
 Final Exam***                                                1, 2, 3, 4, 5, 6            48%
 Total                                                                                    100%
*Programming exercises during classes will not be graded, but should always be emailed to TA to show
your attendance and effort.
**Each student has to write their Matlab codes independently, although discussions of assignments
among students are encouraged.
***Final Exam will be given at the last class, and it will cover all course topics.

Important notes about grading policy:
The grade for good performance in a course will be a B+/B. The grade of A- will only be awarded for
excellent performance. The grade of A will be reserved for the select few who demonstrate
extraordinarily excellent performance. *The grades of D+, D, and D- are not awarded at the graduate
level. Grade appeals will ONLY be considered in the case of a documented clerical error.

Tentative Course Calendar*
*The instructors reserve the right to alter course content and/or adjust the pace to accommodate class
progress.

 Week        Date                   Content                            Reading                Assignments

                        Programming in Matlab:
                                                               AG: Chapters 1, 2, 3,
   1                    mathematical expression, script                                      HW#1 Assigned
                                                                     and 4
                        files, and arrays
                        Programming in Matlab:
                                                                 AG: Chapters 5, 6,          HW#2 Assigned
   2                    conditional statements, loops,
                                                                      and 7                    HW#1 Due
                        plot, and user-defined functions
                        Probability, Statistics, and
                        Simulations: probability
                        theorems, random number
                                                                HLS: Chapters 1, 2,          HW#3 Assigned
   3                    generators, correlated normal
                                                                     3, and 4                  HW#2 Due
                        random numbers, and
                        applications in Gaussian copula
                        model and operational risk
                        Monte Carlo: estimating π,
                        geometric Brownian motion, and                                       HW#4 Assigned
   4                                                               HLS: Chapter 5
                        pricing European Options with                                          HW#3 Due
                        Monte Carlo
                        Option Pricing: Delta hedging,
                        pricing Asian options with Monte        HLS: Chapters 9 and          HW#5 Assigned
   5
                        Carlo, and pricing American                     10                     HW#4 Due
                        options with binomial trees
                                   BU.230.710.xx– Quantitative Financial Analysis – Instructor’s Name – Page 4 of 4



                        Interest Rate Derivatives and
                        Credit Derivatives: modeling
                        interest rate, pricing bond             HLS: Chapters 11            HW#6 Assigned
   6
                        options and interest rate caps,              and 12                   HW#5 Due
                        pricing credit default swaps and
                        other credit derivatives
                        Market Risk: Value at Risk, and
                        its estimation with historical
   7                                                             HLS: Chapter 14               HW#6 Due
                        simulation, parametric
                        approaches, and Monte Carlo

   8                               Final Exam




Copyright Statement

Unless explicitly allowed by the instructor, course materials, class discussions, and examinations are
created for and expected to be used by class participants only. The recording and rebroadcasting of such
material, by any means, is forbidden. Violations are subject to sanctions under the Honor Code.

								
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