Learn basics of financial economics and try its real life application using financial data and programming. 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.
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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 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.
What topics will you cover?
- Securities analysis
- Capital allocation
- Understanding market risk
- Securities valuation (CAPM, APM)
- Optimal investment portfolio construction
What will you achieve?
- Calculate the return and risk of an investment.
- Evaluate the portfolio return and risk, and understand how covariance affects the overall portfolio risk.
- Demonstrate the ability to code the optimal portfolio construction process using R.
- Identify the mean-variance optimal portfolio both conceptually and empirically.
- Develop a single/multiple factor model and calculate the expected return of an investment.
