| Academic Year |
2024Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA221001 |
Subject Classification |
Specialized Education |
| Subject Name |
時系列分析 |
Subject Name
（Katakana） |
ジケイレツブンセキ |
Subject Name in
English |
Time Series Analysis |
| Instructor |
KATO RYUTA,YAMADA HIROSHI |
Instructor
(Katakana) |
カトウ リュウタ,ヤマダ ヒロシ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
3rd-Year, Second Semester, 3Term |
| Days, Periods, and Classrooms |
(3T) Fri1-4 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Online lecture. |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
B
:
Japanese／English |
| Course Level |
3
:
Undergraduate High-Intermediate
|
| Course Area（Area） |
24
:
Social Sciences |
| Course Area（Discipline） |
03
:
Economics |
| Eligible Students |
|
| Keywords |
|
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(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
（Abilities and Skills）
・D2. Ability to take charge of organizational strategy and planning based on statistical evidence by making full use of a wide range of knowledge and techniques in data science.
Intelligence Science Program
（Abilities and Skills）
・D2. Information processing ability and data analysis ability to contribute to the application and development of artificial intelligence and IoT. |
|---|
Class Objectives
/Class Outline |
Lecture of time series analysis |
| Class Schedule |
1. Introduction
2. Stationary Processes
3. ARMA Models 1
4. ARMA Models 2
5. Forcasting
6. VAR model
7. VAR model 2
8. VAR model 3
9. Review of the first half lecture
10. Unit root process 1
11. Unit root process 2
12. Financial Time Series 1
13. Financial Time Series 2
14. Economic applications
15. Review of the second half lecture
|
Text/Reference
Books,etc. |
Handouts |
PC or AV used in
Class,etc. |
|
| (More Details) |
Online lecture. |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Spend enough time on reading the course materials. |
| Requirements |
|
| Grading Method |
Take home exam. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
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. |