Open Programs

Professional Programs

Professor

KIM YOUNGHAN

Learning Period

11-02-2023 ~ 11-03-2025

Course Introduction

  투자자들의 탐욕과 공포 때문에 끝없이 벌어지는 버블과 패닉. 글로벌 금융시장에서 특별한 위치를 점하고 있다고 알려진 유태인들에 대해서 이제 한국인들이 정확하게 이해해야 합니다. 왜냐하면, 가수 싸이도 세계적인 유태인 프로듀서 스쿠터 브라운과 협업을 했고, 이제는 하이브의 방시혁도 그를 미국 지사의 CEO로 임명할 정도로 한국인들이 유태계 비즈니스맨들과 어울릴 일들이 많아졌기 때문입니다. 유태인들에 대한 오해와 이해. 어디까지가 사실이고 어디부터가 거짓인가? 그들에 대한 잘못된 신화가 퍼진다면 언제, 왜 사람들이 퍼 나르고 박해하는 것일까요? 본 과목에서는 유태인 금융가문들의 심리와 투자자들의 군중심리를 행동경제학으로 밝혀냄으로써 유태인에 대한 이해를 바로하고자 합니다. 뿐만 아니라, 이를 통해 아시아나 한국 내부적으로도 금융위기에 보다 유연하게 대처할 인문학적 소양을 키웁니다. 또한, 유태인 및 비유태인으로 유명한 투자자 및 금융가문들의 흥망성쇠를 다룸으로써 일반인들도 보다 재무 금융에 대해서 친근감 있게 배고자하는 마음을 불러일으키고자 합니다.

[SKKU Online] Understanding Jewish Banking History through Behavioral Finance
[SKKU Online] Understanding Jewish Banking History through Behavioral Finance
KIM YOUNGHAN

Professor

KIM KYONG HWAN

Learning Period

11-01-2022 ~ 12-31-2023

Course Introduction

기존의 이론 위주로 다루었던 창업 관련 강좌에서 더 나아가, 실제 창업자들의 경험을 토대로 경험과 노하우를 압축시켜 실무적인 측면에 어려웠던 부분을 함께 공유하여 성공적인 창업으로 이끌 수 있도록 한다. 실제 창업 생태계의 최전선에서 활동 중인 창업가들의 답변을 바탕으로 ‘창업가가 창업을 묻다.’ 주제 하에 테이블 토크형식으로 진행한다. 또한 케이무크의 주 수강층인 일반인 및 학부생들의 궁금증 해결 및 창업이라는 새로운 도전에 도움을 준다.또한 현대 이 시대는 가장 저비용으로 창업을 할 수 있는 시대이다. 창업에는 큰 비용이 들지 않는다. 예로 IT분야는 기술, 제조업은 아웃소싱으로 당장의 큰 자본이 없어도 사업을 실행 할 수 있다. 뿐만 아니라 정보통신의 발달로 멀리 떨어져 있는 우수한 인재와 적은 커뮤니케이션과 적은 비용으로 협업을 진행 할 수 있음은 물론 우리나라의 경우 창업을 하고자하는 예비창업자들에게 지원하는 창업지원프로그램 및 프로세스가 잘 꾸려져 있기에 좋은 아이디어만 있다면 WHY not? 시작하지 않을 이유가 없다.   교수소개 - 김경환 성균관대학교 글로벌창업대학원 교수   강의일정 * 구성: 강의 영상, 읽을거리 및 자유토론* 본 강좌는 짧은 시간 내에 필요한 핵심적인 내용을 들을 수 있는 마이크로 강좌 문의: 성균관대학교 교무처 교육개발선터 (Center for Teaching & Learning)

[K-MOOC] How to start a Start-up Business
[K-MOOC] How to start a Start-up Business
KIM KYONG HWAN

Global Programs

Professor

NIELSEN YOUNGJU LEE

Learning Period

11-01-2022 ~ 12-31-2023

Course Introduction

In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to use various regression methodologies for investment management that you might need to do in your job every day and make you ready for more advanced topics in machine learning. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics and R programming. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. Students are also expected to know of the instructors' 1st course, 'Fundamental of data-driven investment.' The instructor will explain the detail of R programming. It will be an excellent course for you to improve your programming skills but you must have basic knowledge in R. If you are very good at R programming, it will provide you with an excellent opportunity to practice again with finance and investment examples.   영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수  삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드  주 (Week)  학습 내용 (Contents)               Week 1     Understanding the big picture of the algorithm-driven investment    decision-making process using machine learning and review     of regression methodology               Week 2     Regression and beyond   문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)  

Using R for Regression and Machine Learning in Investment
Using R for Regression and Machine Learning in Investment
NIELSEN YOUNGJU LEE

Professor

NIELSEN YOUNGJU LEE

Learning Period

11-01-2022 ~ 12-31-2023

Course Introduction

In this course, the instructor will discuss the fundamental analysis of investment using R programming. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to do the elemental analysis for investment management that you might need to do in your job every day. Additionally, the study note to do using Python programming will be provided. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. The instructor will explain the detail of R programming for beginners. It will be an excellent course for you to improve your programming skills. If you are very good at R programming, it will provide you an excellent opportunity to practice again with finance and investment examples. Professor Youngju Nielsen creates the course with the assistants of Keonwoo Lim and Jeeun Yuen. =========================================================================================== Coursera Course recommendations before this course for those who are not familiar with basic R programming: https://www.coursera.org/projects/getting-started-with-r https://www.coursera.org/learn/business-analytics-r https://www.coursera.org/specializations/statistics-with-python   영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수  삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드  주 (Week)  학습 내용 (Contents)               Week 1      Analyzing Past Returns and Forecasting Future Returns               Week 2      Understanding the Risk Using Factors               Week 3      Portfolio Analysis and Optimization               Week 4      Performance Analysis   문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)

The Fundamental of data-driven investment
The Fundamental of data-driven investment
NIELSEN YOUNGJU LEE

Professor

NIELSEN YOUNGJU LEE

Learning Period

11-01-2022 ~ 12-31-2023

Course Introduction

- Discover how predictive analytics could transform your business As businesses accrue more and more data about their customers – from their behavioural history to their transactions – being able to use ‘Big Data’ is becoming increasingly key to low-term business success. - Learn how predictive analytics helps business Predictive analytics encompasses a variety of statistical techniques in big data analysis and machine learning. Alongside data science experts at Sungkyunkwan University (SKKU), you’ll get foundational training in the concepts and principles that underlie data science and statistical modelling techniques. - See how data science can boost business performance The course will take you through a series of real-world business problems, solving each by using key predictive analytics methods. These include statistical methodologies and algorithms such as artificial neural networks, clustering, text mining, decision trees, and natural language processing. - Explore the relationship between predictive analysis and machine learning You’ll discover the essentials of machine learning, which can be a vital tool in analysing and making use of data. Discover the difference between supervised machine learning – where you can collect data based on previous experience – and unsupervised machine learning – where you can find new data patterns. - Gain practical big data skills Along the way, you’ll learn how to use predictive tools to extract knowledge from data, connect actual business problems with data science solutions, and lead a data science-orientated team.     - 영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수  삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드    문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)

Artificial Intelligence and Machine Learning for Business
Artificial Intelligence and Machine Learning for Business
NIELSEN YOUNGJU LEE

Professor

NIELSEN YOUNGJU LEE

Learning Period

11-01-2022 ~ 11-01-2022

Course Introduction

Financial markets have become increasingly complex - it’s not easy to know where to start when it comes to investing. In today’s world the demand of accurate data-driven quantitative analysis across the world is steadily rising: it’s become crucial to understand and be able to use statistical and mathematical information accurately and promptly. This course will teach you the essentials of modern investment theory and help you learn to apply them in real life using financial data and programming. ##Understand modern investment theory On the course you’ll start by learning about key concepts in modern investment theory and quantitative investing like return, risk and portfolio optimisation. ##Get used to statistical techniques and practice using programming language R Once you’ve learnt basic investment concepts we’ll look at applying them using statistics and programming using open source language R will be introduced. You’ll practice by doing assignments every week using actual securities data from Yahoo Finance. ##Discover how to construct an investment portfolio Using your new knowledge of quantitative investing and your ability to analyse investment characteristics using programming, you’ll be able to build your own diversified investment portfolio based on return analysis. ##Learn from an expert in the field Through the course you’ll be taught by an educator who has worked in quantitative finance for more than 15 years in Wall Street global investment banks, before she joined [SKKU](https://www.futurelearn.com/partners/sungkyunkwan-university) in 2015. She was Chief Investment Officer at a hedge fund and head of systematic trading groups at global banks such as Citi and J.P. Morgan.   - 영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수  삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드   문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)

Introduction to Quantitative Investing
Introduction to Quantitative Investing
NIELSEN YOUNGJU LEE