本課程首先介紹時間序列數據的基本概念，接著深入講解常見的時間序列模型，包括ARIMA模型、GARCH模型以及VAR模型。在進階內容中，課程將講授非線性時間序列模型、高頻資料分析、連續時間隨機模型、VaR、PCA等。
This course begins with an introduction to the fundamental concepts of time series data, followed by an in-depth discussion of common time series models, including the ARIMA model, GARCH model, and VAR model. In the advanced sections, the course will cover nonlinear time series models, high-frequency data analysis,continuous-time stochastic models, Value at Risk (VaR), and Principal Component Analysis (PCA), and so on.
你也可以選修【金融資料分析2】
You can also take [Financial Data Analysis 2].
本課程的教學目標是培養學生對時間序列數據的深入理解與分析能力，使其能夠識別時間序列數據的特性，選擇適當的方法進行處理，並構建模型以解釋數據行為和進行未來預測。
Po–Keng Cheng holds a PhD in Applied Mathematics and Statistics from SUNY-Stony Brook University, U.S.A., a MA in Economics from Northeastern University, U.S.A., and a BA in Economics from National Central University, Taiwan. He has been working on research of interactive agent‐based models investigating traders’behaviors and their trading strategies in financial markets. He currently also involves in studies related to probability, dynamical systems, and game theory.
單元 1:1 Financial Data and Their Properties
單元 2:2 Background for Linear Time Series
單元 3:3 Simple Autoregressive Models
單元 4:4 Simple Moving Average Models
單元 5:5 Simple ARMA Models
單元 6:6 Unit-Root Nonstationarity
本課程共計6週，每週將提供視頻影片，課程架構詳見「課程進度表」
This course consists of 6 weeks. Video lessons will be provided each week. Please refer to the "Course Schedule" for the course structure.
觀看影片：佔總成績100 %
Watching videos:100% of the total grade.
本課程無須背景知識，適合所有對金融資料分析有興趣的學習者修習。
This course does not require any prior knowledge and is suitable for anyone interested in financial data analysis.
Tsay, R. S. (2013). An introduction to analysis of financial data with R. John Wiley & Sons.
Chan, K. S., & Cryer, J. D. (2008). Time series analysis with applications in R. Springer publication.
Tsay, R. S. (2010). Analysis of financial time series (3rd). John Wiley & Sons.
Hamilton, J. D. (2020). Time series analysis. Princeton University Press.
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