6286 - 產業應用分析

Industrial Analysis and Applications

教育目標 Course Target

本課程將運用大數據分析工具,應用於實際產業個案議題分析,透過授課與研討,訓練學生具備建構探究及分析產業數據的工具基礎、學習相關經濟理論及實證模型以及結合經濟理論及數據分析工具以應用於分析產業個案或相關研究之能力。本課程分為兩個部分,前半學期為大數據分析應用於金融產業的基礎觀念、文獻探討與相關研究介紹;後半學期則帶領學生將大數據分析工具應用於實際數據資料,進行消費產業相關議題的研究。金融產業之內容包含探討金融機構風險管理的法規、架構、資本準備要求、以及相關風險模型之基礎觀念與實務架構;銀行放款投資組合相關文獻之探討;將機器學習分析方式應用於借款公司違約預測、銀行放款投資組合多角化與績效之關聯性研究。消費產業方面包括:資料收集、處理與識讀,問題意識與資料呈現,模型設定、估計與結果詮釋。

This course will use big data analysis tools to analyze actual industrial case issues. Through lectures and seminars, students will be trained to have the ability to construct a tool foundation for exploring and analyzing industrial data, learn relevant economic theories and empirical models, and combine economic theory and data analysis tools to analyze industrial cases or related research. This course is divided into two parts. The first half of the semester is about the basic concepts, literature discussion and related research introduction of big data analysis in the financial industry. The second half of the semester leads students to apply big data analysis tools to actual data materials and conduct research on consumer industry-related issues. The content of the financial industry includes the discussion of the regulations, structure, capital preparation requirements of financial institutions' risk management, and the basic concepts and practical framework of related risk models; the discussion of relevant literature on bank lending portfolios; the application of machine learning analysis methods to the prediction of borrower company defaults, and the study of the correlation between bank lending portfolio diversification and performance. The consumer industry includes: data collection, processing and interpretation, problem awareness and data presentation, model setting, estimation and result interpretation.

參考書目 Reference Books

I. 銀行產業相關書籍與參考文獻
1. Eryk Lewinson(2020), "Python for Finance cookbook" ISBN: 9781789618518
2. 相關主題參考期刊論文
Campello, M., & Gao, J. (2017). Customer concentration and loan contract terms. Journal of Financial Economics, 123(1), 108-136.
Tabak, B. M., Fazio, D. M., & Cajueiro, D. O. (2011). The effects of loan portfolio concentration on Brazilian banks’ return and risk. Journal of Banking & Finance, 35(11), 3065-3076.

I. Banking industry related books and references
1. Eryk Lewinson(2020), "Python for Finance cookbook" ISBN: 9781789618518
2. Reference journal articles on related topics
Campello, M., & Gao, J. (2017). Customer concentration and loan contract terms. Journal of Financial Economics, 123(1), 108-136.
Tabak, B. M., Fazio, D. M., & Cajueiro, D. O. (2011). The effects of loan portfolio concentration on Brazilian banks’ return and risk. Journal of Banking & Finance, 35(11), 3065-3076.

評分方式 Grading

評分項目
Grading Method
配分比例
Percentage
說明
Description
金融產業評分
Financial Industry Rating
50 金融產業之評量方式(課堂參與30%、作業30%、研究計畫書40%)
消費產業評分
Consumer Industry Rating
50 消費產業之評量方式(課堂參與討論30%、作業30%、成果報告40%)

授課大綱 Course Plan

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課程資訊 Course Information

基本資料 Basic Information

  • 課程代碼 Course Code: 6286
  • 學分 Credit: 0-3
  • 上課時間 Course Time:
    Wednesday/2,3,4[SS106]
  • 授課教師 Teacher:
    李維倫/傅信豪
  • 修課班級 Class:
    經濟系4,碩1,2
選課狀態 Enrollment Status

目前選課人數 Current Enrollment: 10 人

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