| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| 本課程目標在於使修習同學具有實證分析財務金融資料的能力，包含條件平均數與變異數的模型的建立及估計，使能進行財務金融商品預期報酬率及風險的預測，進而具有選擇最佳資產配置的能力。本課程強調R電腦語言程式實證分析能力的培養。 |
| 1.Critical Thinking |
| 6. Independent problem solving |
|
|
| Exercises |
| Discussion |
| Lecturing |
| topic Discussion / Production |
|
| Written Presentation |
| Attendance |
| Oral Presentation |
| Quiz |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
1. 課程內容及大綱介紹
2. 隨機過程、函數型資料、追蹤資料及時間序列 |
| Week 2 |
1. 恆定與非恆定隨機過程之定義
2. 時間序列單根及恆定性檢定基礎與方法 |
| Week 3 |
時間序列平均數變動之檢定邏輯與方法 |
| Week 4 |
單變量ARIMA模型（一） |
| Week 5 |
單變量ARIMA模型（二） |
| Week 6 |
1. 單變量ARIMA模型之預測與比較
2. 財務金融實證分析案例 |
| Week 7 |
單變量時間序列模型之R語言程式 |
| Week 8 |
期中考試 |
| Week 9 |
1. 期中考試檢討
2. 單變量線性ARCH及GARCH模型 |
| Week 10 |
單變量非線性ARCH及GARCH模型 |
| Week 11 |
1. 金融商品報酬率風險之預測及其應用 |
| Week 12 |
1. 多變量時間序列VAR及VECM模型
2. 共積關係檢定 |
| Week 13 |
單變量函數型資料分析：函數資料重建與FPCA |
| Week 14 |
單變量函數型資料恆定性分析 |
| Week 15 |
多變量函數型資料之迴歸分析 |
| Week 16 |
財務金融實證分析
自主學習：Gapminder視覺化統計分析線上影片教學
自主學習：Rmarkdown程式撰寫的線上影片教學 |
self-directed
learning |
|
|
| Evaluation |
| 課堂參與: 10% 課堂討論：20% 家庭作業：20% 期中考試：20% 期末書面報告：30% |
| Textbook & other References |
1. Shumway, R.H. and D.S. Stoffer (2017), Time Series Analysis and its Applications: with R Examples,
Springer (eBook).
2. Tsay, Ruey S. (2013), An Introduction to Analysis of Financial Data with R, Wiley.
3. Woodward, W.A., H.L. Gray, and A.C. Elliott (2017), Applied Time Series Analysis with R,
Chapman & Hall.
4. Horváth, L. andd P. Kokoszka (2012), Inference for Functional Data with Applications,
Springer (eBook). |
| Teaching Aids & Teacher's Website |
| iLearning |
| Office Hours |
| 15:00~17:00，星期一 |
| Sustainable Development Goals, SDGs(Link URL) |
| include experience courses：N |
|