國立中山大學 108學年度第1學期 課程教學大綱

National Sun Yat-sen University 108Academic year1st Semester Course syllabus

中文名稱
Course name(Chinese)

金融投資與程式交易

課號
Course Code

FM617

英文名稱
Course name(English)

FINANCIAL INVESTING AND PROGRAM TRADING

課程類別
Type of the course

講授類

必選修
Required/Selected

選修

系所
Dept./faculty

財務管理學系碩士班

授課教師
Instructor

王昭文    

學分
Credit

3

因應嚴重特殊傳染性肺炎(武漢肺炎),倘若後續需實施遠距授課,授課方式調整如下:Since COVID-19, if distance learning is necessary, the teaching methods would adjust as follows:

         尚未建立傳染性肺炎(武漢肺炎)授課方式調整

因應嚴重特殊傳染性肺炎(武漢肺炎),倘若後續需實施遠距授課,評分方式調整如下:Since COVID-19, if distance learning is necessary, the evaluation would adjust as follows:

         尚未建立傳染性肺炎(武漢肺炎)課程評分方式﹝評分標準及比例﹞

課程大綱 Course syllabus

         本課程教學大綱已提供完整英文資訊(本選項僅供統計使用,未提供完整英文資訊者,得免勾記)【Provide information of course syllabus in English.(This is for statistical use only. For those who do not provide information of course syllabus in English, do not check this field.)】

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 Objectives

         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 Teaching methods

         1. Homework or/and In-class quizs
2. Lecture




評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference

        
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 Reference book/ textbook/ documents
〔請遵守智慧財產權觀念,不可非法影印。教師所提供之教材供學生本人自修學習使用,不得散播及做為商業用途〕
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use

        
序號作者書名出版社出版年出版地ISBN#
No.AutherTitlePublisherYear of
publish
Publisher
place
ISBN#
1陳景祥R軟體應用統計方法東華書局2016台灣978-957-483-626-0
2蔡立耑量化投資以R語言為工具電子工業出版社2015台灣978-7-121-27585-2
3朱家泓抓住K線,獲利無限金尉2013台灣978-986-8734-67-8
4王昭文自編講義(主要)

每週課程內容及預計進度 Weekly scheduled progress

        
週次日期授課內容及主題
WeekDateContent and topic
12019/09/09~2019/09/15R 軟體簡介與操作[R basic]
22019/09/16~2019/09/22R 的變數與資料輸入輸出[R parameters and data manipulation]
32019/09/23~2019/09/29中秋節放假[Mid-autumn Festival]
42019/09/30~2019/10/06R 的資料轉換與處理與自訂函數[R data transpose and create function]
52019/10/07~2019/10/13R for Data Science 1[R for Data Science 1]
62019/10/14~2019/10/20R for Data Science 2[R for Data Science 2]
72019/10/21~2019/10/27R 常用函數與程式技巧[R most used function and skills]
82019/10/28~2019/11/03技術分析概念(指標分析)[Technical analysis]
92019/11/04~2019/11/10技術分析概念(線圖分析)[Technical analysis]
102019/11/11~2019/11/17R技術分析套件運用[R quantmod and tidyquant]
112019/11/18~2019/11/24技術線圖量化條件捕抓之交易策略實作[Technical analysis and trading strategy]
122019/11/25~2019/12/01迴歸套件與五線譜之運用[Regression packages]
132019/12/02~2019/12/08基本分析概念[Fundamental analysis]
142019/12/09~2019/12/15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]
152019/12/16~2019/12/22財務指標(如五力分析)量化選股之交易策略實作[Trading strategy with financial index]
162019/12/23~2019/12/29期末報告初步課堂分享[Final report]
172019/12/30~2020/01/052019元旦彈性放假[New year]
182020/01/06~2020/01/12期末成果報告與繳交[Final report]

課業討論時間 Office hours

         時段1 Time period 1:
時間 Time:星期二14:00~16:00
地點 Office/Laboratory:管4045
時段2 Time period 2:
時間 Time:星期三14:00~16:00
地點 Office/Laboratory:管4045

系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university

        
系所學生專業能力/全校學生基本素養與核心能力
basic disciplines and core capabilities of the department and the university
課堂活動與評量方式
Class activities and evaluation
本課程欲培養之能力與素養 This course enables students to achieve.紙筆考試或測驗 Test.課堂討論︵含個案討論︶ Group discussion (case analysis).個人書面報告、作業、作品、實驗 Indivisual paper report/ assignment/ work or experiment.群組書面報告、作業、作品、實驗 Group paper report/ assignment/ work or experiment.個人口頭報告 Indivisual oral presentation.群組口頭報告 Group oral presentation.課程規劃之校外參訪及實習 Off-campus visit and intership.證照/檢定 License.參與課程規劃之校內外活動及競賽 Participate in off-campus/ on-campus activities and competitions.課外閱讀 Outside reading.
※系所學生專業能力 Basic disciplines and core capabilities of the department
1.財務倫理之能力與社會責任實踐 1. Financial ethics ability.           
2.國際觀之能力 2. Global perspective.V VVVVV    
3.解決財務問題之能力 3. Problem solving ability in Finance.V VVVVV    
4.溝通之能力 4. Communication skill.           
5.財務管理專業知識之能力 5. Expertise in Financial management.V VVVVV    
※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university
1.表達與溝通能力。 1. Articulation and communication skills           
2.探究與批判思考能力。 2. Inquisitive and critical thinking abilities           
3.終身學習能力。 3. Lifelong learningV VVVVV    
4.倫理與社會責任。 4. Ethnics and social responsibility           
5.美感品味。 5. Aesthetic appreciation           
6.創造力。 6. CreativityV VVVVV    
7.全球視野。 7. Global perspective           
8.合作與領導能力。 8. Team work and leadershipV VVVVV    
9.山海胸襟與自然情懷。 9. Broad-mindedness and the embrace of nature            

本課程與SDGs相關項目:The course relates to SDGs items:

         尚未建立SDGS資料

本課程校外實習資訊: This course is relevant to internship:

         本課程無註記包含校外實習

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