金融數據分析(112-1)

課程大綱

FinTech的賦權投資人(Empowered Investor)概念,將導引未來金融市場朝向CS(Computer Science)與金融商品操作的整合發展上。因此,全方位個人理財人才的培養,不僅要瞭解市面上的金融工具外,更必須具備一定程度的資料處理與分析能力,以因應未來FinTech趨勢下的市場競爭。本課程的目標是以資料科學(Data Science)為主,透過R語言程式設計能力,培養全方位理財人才,從巨量的量化財務信息分析出合適的個人理財交易策略。

FinTech’s Empowered Investor concept will guide the future development of financial markets towards the integration of CS (Computer Science) and financial commodity operations. Therefore, the cultivation of all-round personal financial management talents must not only understand the financial instruments on the market, but also must have a certain degree of data processing and analysis capabilities in order to cope with the market competition under the trend of FinTech in the future. The goal of this course is to focus on Data Science, to develop a full range of financial management talents through R language programming skills, and to analyze appropriate personal financial trading strategies from a huge amount of quantitative financial information.

課程目標

因應未來FinTech趨勢,本課程的教學目標就是從資料科學(Data Science)角度出發,透過R語言程式教學,培養學生運用R程式能力,從量化財務信息分析出合適的個人理財交易策略,達到全方位理財能力。本課程前半段將專注在R語言教學,後半段專注在運用R語言分析相關交易策略之可行性。

Cultivate the students have the ability of data science. Teach students R language and programing. Focus on R programing at the beginning, and use R to create trading strategy after that. Finally, cultivate students to be FinTech talents.

授課方式

  1. Homework or/and In-class quizs
  2. Lecture
    已選課學生請於以下連結進入: https://meet.google.com/cvf-grme-auq
    進入會議室,統一名稱為:科系+年級+學號+姓名。
    非選課學生擬旁聽者,請於前述連結登入,並於留言區留下科系+年級+學號+姓名,以做為異常處理之參考。本課程將與企業進行產學合作,每組皆須完成課程專案(專案僅提供需求規劃,包含介面/架構或雛型系統,不包含執行與分析)。

評分方式

  1. 點名[Class participation]:20%
  2. 課堂作業[Homework]:10%
  3. 期中考[Midterm]:35%
  4. 期末分組報告[Final group report]:35%

參考書/教科書/閱讀文獻

陳景祥,2016. R 軟體應用統計方法,東華書局
蔡立耑,2015. 量化投資以R語言為工具 ,電子工業出版社
朱家泓,2013. 抓住K線,獲利無限,金尉
王昭文,自編講義(主要)

課程內容及進度

Week Syllabus
1 R 軟體簡介與操作[R basic]
2 R 的變數與資料輸入輸出[R parameters and data manipulation]
3 R 的資料轉換與處理與自訂函數[R data transpose and create function]
4 R 的資料轉換與處理與自訂函數[R data transpose and create function]
5 R for Data Science 1[R for Data Science 1]
6 R for Data Science 2[R for Data Science 2]
7 R 常用函數與程式技巧[R most used function and skills]
8 技術分析概念(指標分析)[Technical analysis]
9 技術分析概念(線圖分析)[Technical analysis]
10 R技術分析套件運用[R quantmod and tidyquant]
11 R技術分析套件運用[R quantmod and tidyquant]
12 技術線圖量化條件捕抓之交易策略實作[Technical analysis and trading strategy]
13 迴歸套件與五線譜之運用[Regression packages]
14 基本分析概念[Fundamental analysis]
15 財務指標(如五力分析)量化選股之交易策略介紹[Trading strategy with financial index]
16 期末報告初步課堂分享[Final report]
17 期末成果報告與繳交[Final report]
18 彈性學習[Alternative Curriculum]