Youngju Nielsen

Youngju is an assistant professor of School of Economics, Sungkyunkwan University (SKKU) Seoul Korea. She has been an adviser for Samsung (Asset management), South Korean multinational conglomerate company since July 2015 and an adviser for Korea's Government Employee Pension Service since October 2016. Youngju is also appearing at Wall Street Trends on CNBC Korea and writes bi-weekly column of 'Youngju Nielsen's reading global economy" for Dong-a, a leading Korean media company.

She was a columnist for "Youngju Nielsen's Wall Street Report" at Weekly Chosun, a leading Korean media company for more than three years until 2016 May. She is often invited as a speaker for companies and educational institutions. She is also often engaged with projects of public institutions such as Bank of Korea.

Prior to her recent career change to academia, Youngju had 15 years of experience in the Wall Street jobs, particularly in the field of quantitative and systematic fixed income trading and portfolio management. Prior, she was CIO and partner of systematic trading hedge fund, Quantavium capital management. Before Quantavium, she has run global interest rates portfolios at proprietary trading group of Bear Stearns, J.P. Morgan and Citi in their New York headquarter offices. She built the business, Quantitative Principal Strategy in Fixed Income (QPS FI) from the ground up at Bear Stearns as their managing director and then continued heading the same business at J.P. Morgan. Prior to career as a portfolio manager, she was a research officer at Barclays Global Investors and head of quantitative research at Allianz Dresdner Asset Management.
Youngju received Ph.D. and M.A. in Statistics (Thesis: Statistical computing, artificial intelligence on stock exchange) from University of Pittsburgh, Master in Financial Engineering from University of California, Berkeley and B.A. in economics from Yonsei University, Seoul Korea.
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Machine Learning for Smart Beta (Coursera)

In this 4 week course, you will learn about Smart Beta products. Smart betas products have the characteristics of both passive investment(having predetermined rules) and active investments(allows for factor investment). We will walk through the creation mechanisms behind different smart beta products and recreate some of them using R [...]

Using R for Regression and Machine Learning in Investment (Coursera)

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 [...]

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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 [...]

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Explore how predictive models can help businesses use data to identify risks and discover new opportunities. 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 [...]

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