基本素養 Basic Literacy
□ 文化傳承
Culture transition
□ 歷史意識
Historical consciousness
□ 藝術涵養
Artistic literacy
□ 公民素養
Civil literacy
□ 社會關懷
Social concern
■ 經世濟民
Benefit people and the society
■ 國際視野
International Perspective
核心能力 Competence
■ 鞏固系定基礎知識
Consolidate fundamental knowledge in economics
■ 獲得跨領域的多樣化知識
Acquire diversified knowledge from interdisciplinary fields
■ 熟悉經濟分析工具
Be familiar with tools for economic analysis
■ 擴展經濟應用
Expand economic applications
□ 語文與溝通能力
Language proficiency and communication ability
□ 創新與領導能力
Innovative and Leadership Abilities
課程概述 Course Description
本課程介紹財務計算方法和應用於財務模型的數據分析。課程涵蓋R程式語言中的電腦程式編寫和數據分析、計量經濟學（統計分析）、財務經濟學、個體經濟學、數學演算最佳化和機率統計模型。本課程的重點將放在使用實際財務數據，以資產報酬行為的經濟模型為基礎，應用計量經濟學模型進行估算及分析；課程內容結合經濟、財務、數學及統計領域的專業知識並涉及：（1）探索性數據分析；（2）解釋財務數據的計量模型設定；（3）模型估算與評估；（4）測試模型的經濟意義；（5）利用模型進行預測。模型建立過程需要使用經濟理論、矩陣代數、最佳化演算概率模型、統計分析和統計軟體。本課程培養學生在面對大數據及人工智慧浪潮下，將資訊科技與財務結合應用，以擴增學生學習經濟學之應用價值及提升跨領域資料之整合分析能力。This course is an introduction to computational finance and data science applied to finance. The course covers computer programming and data analysis in R, econometrics (statistical analysis), financial economics, microeconomics, mathematical optimization, and probability models. The emphasis of the course will be on making the transition from an economic model of asset return behavior to an econometric model using real data. This involves: (1) exploratory data analysis; (2) specification of models to explain the data; (3) estimation and evaluation of models; (4) testing the economic implications of the model; (5) forecasting from the model. The modeling process requires the use of economic theory, matrix algebra, optimization techniques, probability models, statistical analysis, and statistical software.
課程學習目標 Course Objectives
課程進度 Progress Description
| 進度說明 Progress Description | |
|---|---|
| 1 | Course Introduction, Time-Value of Money and Financial Returns (1) |
| 2 | Time-Value of Money and Financial Returns (1); Univariate Random Variables (2) |
| 3 | Univariate Random Variables (2); Bivariate Random Variables (3) |
| 4 | Introduction to Time-Series (4); Matrix Algebra Review (5) |
| 5 | Descriptive Statistics (6); The Constant Expected Return Model (7) |
| 6 | The Constant Expected Return Model (7) |
| 7 | The Constant Expected Return Model (7); Bootstrapping Methods (8). |
| 8 | The Constant Expected Return Model (7); Bootstrapping Methods (8). |
| 9 | Midterm |
| 10 | Introduction to Modern Portfolio Theory (9) |
| 11 | Introduction to Modern Portfolio Theory (9) |
| 12 | Modern Portfolio Theory and the Markowitz Algorithm (10) |
| 13 | Modern Portfolio Theory and the Markowitz Algorithm (10) |
| 14 | MPT with No Short Sale Constraints (11); Statistical Properties of Efficient Portfolios (12); Portfolio Risk Budgeting (13); |
| 15 | Portfolio Risk Budgeting (13);The Single Index Model (14);Paper Draft Due |
| 16 | The Single Index Model (14); The Capital Asset Pricing Model (15) |
| 17 | The Capital Asset Pricing Model (15) |
| 18 | Final Research Paper Due |
以上每週進度教師可依上課情況做適度調整。The schedule may be subject to change.
課程是否與永續發展目標相關調查
Survey of the conntent relevant to SDGs
本課程與SDGs相關項目如下：
This course is relevant to these items of SDGs as following:
- 就業與經濟成長 (Decent work and Economic growth)
- 責任消費與生產 (Responsible consumption and production)
有關課程其他調查 Other Surveys of Courses
1.本課程是否規劃業界教師參與教學或演講? 否Is there any industry specialist invited in this course? How many times? No
2.本課程是否規劃含校外實習(並非參訪)? 否
Are there any internships involved in the course? How many hours? No
3.本課程是否可歸認為學術倫理課程? 否
Is this course recognized as an academic ethics course? In the course how many hours are regarding academic ethics topics? No
4.本課程是否屬進入社區實踐課程? 否
Is this course recognized as a Community engagement and Service learning course? Which community will be engaged? No