Hiroshima University Syllabus

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Academic Year 2024Year School/Graduate School School of Informatics and Data Science
Lecture Code KA225001 Subject Classification Specialized Education
Subject Name ファイナンス工学
Subject Name
Subject Name in
Financial Engineering
Instructor TING HIAN ANN
ティン ヒェン アン
Campus Higashi-Hiroshima Semester/Term 3rd-Year,  Second Semester,  4Term
Days, Periods, and Classrooms (4T) Weds3-4,Fri3-4:ENG 102
Lesson Style Lecture Lesson Style
(More Details)
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 3 : Undergraduate High-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
(Applicable only to targeted subjects for undergraduate students)
Criterion referenced
(Applicable only to targeted subjects for undergraduate students)
Computer Science Program
(Abilities and Skills)
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.

Data Science Program
(Comprehensive Abilities)
・D3. Ability to overlook social needs and issues that are intertwined in a complex manner and to solve issues with quantitative and logical thinking based on data, a multifaceted perspective, and advanced information analysis ability.

Intelligence Science Program
(Comprehensive Abilities)
・D3. Ability to grasp complexly intertwined social needs and issues from a bird's-eye view and solve issues with a multifaceted perspective and analytical ability based on a wide range of knowledge in intelligent science. 
Class Objectives
/Class Outline
In this course, students will learn how technologies such as data science and AI informatics are changing and reshaping the world of banking and finance. In order to effectively apply these technologies, students must be well versed in the areas of application. Therefore, we will elucidate the essential concepts and frameworks of quantitative finance so that students can navigate the vast "universe" of financial products. Students will also learn about areas where data scientists play an important role, such as robo-advisors and algorithmic trading services, under the name of fintech. 
Class Schedule lesson1 Introduction
lesson2 Four Major Asset Classes
lesson3 Three Principles of Quantitative Finance
lesson4 Commodity and Futures
lesson5 Real-World Data Collection and Analysis
lesson6 Yield Curves Modeling
lesson7 Mid-term Summary
lesson8 Mid-term Test
lesson9 Roles and Mechanism of Finance
lesson10 Electronic Orders
lesson11 Capital Asset Pricing Model
lesson12 Risk Premium
lesson13 Models of Price Fluctuations and Derivatives
lesson14 Summary
lesson15 Final Exam

The exam will be an open-book exam.

Mid-term test and final exam

Using Python, students will also learn practical exercises (data collection). 
1. 木島著『日経文庫:金融工学』(日本経済新聞社)
2. 木島・鈴木・後藤著『ファイナンス理論入門 – 金融工学へのプロローグ』(朝倉書店)
3. 木島・青沼著『 Excel & VBA で学ぶファイナンスの数理』(金融財政事情研究会)
Reference books are used for self-study (standard in financial institutions)
Materials distributed in lectures 
PC or AV used in
(More Details)  
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review of each lecture is recommended if you do not understand the contents. 
Grading Method A. Comprehensive evaluation will be made by exercises submitted, mid-term tests, assignment reports
B. Final examination

60% or more is required to pass. 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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