Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2019	259416	Financial Optimization and Cryptocurrency Portfolio Diversification	1	3.0	3	★	You-Jin Park	IMBA GIFM IMFI	0	0	電腦教室 科研735

Course Plan：

Instructor	You-Jin Park
Email	eugenepark993@gmail.com
Last Updated	2019-01-08 13:34:46
Course Objective	This course concerns making financial decisions in an uncertain world. Increasingly, financial decision-makers are depending on optimization techniques to guide them in their decisions. We will survey the use of such methods in financial decision-making processes. The optimization techniques to be covered will include linear and nonlinear programming, integer programming, dynamic programming, and nonlinear programming. As a supporting theme, the course will also emphasize effective modeling, the use of modeling languages, such as R for solving financial optimization problems. Also, financial topics to be covered will include also blockchain, cryptocurrency, and portfolio optimization. Blockchain technology enables the execution of collaborative business processes involving untrusted parties without requiring a central authority. A cryptocurrency is a digital or virtual currency designed to work as a medium of exchange. In a decentralized system like cryptocurrency, each and every member needs to carry out this activity. This is done by means of the blockchain. In this course, we learn basic concepts of cryptocurrencies and blockchain technology. Then, we will discuss promising financial optimization issues such as cryptocurrency portfolio diversification.
Course Schedule	Week 1 Introduction to financial optimization Week 2 Linear programming – Simplex method Week 3 Linear programming – Post-optimal analysis Week 4 Integer programming Week 5 Dynamic programming Week 6 Quadratic programming Week 7 Stochastic programming Week 8 Project presentation Week 9 Midterm Exam (In-Class, 1 Cheat Sheet, Calculator) Week 10 Nonlinear programming Week 11 Decision making theory Week 12 Game theory Week 13 Heuristic algorithms Week 14 Artificial neural network (ANN) Week 15 Introduction to blockchain and cryptocurrency Week 16 Application of optimization methods to cryptocurrency portfolio diversification Week 17 Project presentation Week 18 Final Exam (In-Class, 1 Cheat sheet, Calculator) Not covers all parts of the course, but covers only what has been discussed after the second midterm.
Evaluation and grading policy	1. Midterm exam: 30 points – Test of covered topics 2. Final exam: 30 points – Test of covered topics (Exams: The days and general contents of each of the two exams will be announced at least one week prior to the exams. The schedule of exams is given in tentative schedule table. If you have an emergency or conflict, please notify me ASAP. Also, all works must be shown to receive full or partial credit. A missed exam or homework or quiz will be assigned a grade of zero, unless a student has a university-approved excuse.) 3. Quiz: 10 points (Quizzes: Short, announced or non-announced in-class quizzes will be given at the beginning of some classes, to check your basic understanding of class material. No makeup quizzes will be given.) 4. Individual projects and presentations: 25 points (Individual projects: Throughout the semester, I will assign two individual projects to be completed and turned in. Each individual project will have a specific due date. Tentatively, individual project will be due the 8th and 17th class weeks at the beginning of class. You are encouraged to do your individual project by yourselves and must ultimately (and neatly!) write up your own solutions. Please turn in your individual project on time. I reserve the right to penalize or to not accept late individual project. Also, you are expected to present the individual project results on the 8th and 17th class weeks.) 5. Attendance: 5 points (Attendance: You are expected to be present each class period except when special hardships occur, e.g. illness or emergency. For any medical issues please see the NTUT website for university policies. If there is an appropriate reason to miss class it is expected that the individual will email or discuss in person with the instructor at least one week in advance. And, students need to provide evidence for missing class (doctor’s note). If evidence is provided, the missed class is considered as an excused class. If no evidence is provided, the missed class is counted as an absence. Regular attendance is essential to the successful completion of this course and missing class can cause you to fall behind, which you definitely do not want to. If you miss a class, be sure to get the notes from another student and kindly provide me with an explanation for your absence. Attendance and class participation also affect your learning of the material as well as performance on assignments, quizzes, and exams. I expect you to arrive to class on time, pay close attention and take notes, and actively participate. An important part of class participation is asking questions if you are unsure about anything. Do not hesitate to ask me questions if you have them. I reserve the right to lower your course grade by half a letter grade (5%) if you have more than 3 absences. More than 5 absences will mean an attendance point zero.)
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Optimization Methods in Finance (Mathematics, Finance and Risk) (1st Edition, Cambridge) by Gerard Cornuejols, Reha Tutuncu (ISBN:978-0521861700)
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