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FutureLearn

Introduction to Data Analytics for Investment

Sungkyunkwan University via FutureLearn

Overview

Learn how to use data analytics skills and regression to forecast returns

We live in an era where “data is the new oil”. No matter your area of expertise, having strong data analytical skills is becoming increasingly important. This four-week course from Sungkyunkwan University (SKKU) will help you use R or Python programming to apply data analysis to finance and investing.

During the first week of this course, you’ll learn to analyse and understand past return data and make a future return forecasting model using regression.

Discover how to assess risk and gauge and test investment strategies

The second week will guide you through how to gauge your investment strategy using backtesting. You’ll utilise the knowledge gained from the first week’s content, as well as your forecasting model, to determine the validity of your investment strategy.

You’ll also expand your knowledge and understanding of assessing investment risks by using probability and statistics to analyse and calculate investment risk.

Create an investment portfolio with global ETFs and optimise it using R

To give you a hands-on learning experience, you’ll create your own investment portfolio using global Exchange-Traded Funds (ETFs).

Once you’ve created your portfolio, your educators will instruct you in managing and optimising it by employing an optimization algorithm using the R standard library.

Analyse the performance of your portfolio with Sungkyunkwan University

For the final week, you’ll learn about various types of portfolio and how to assess the performance of your portfolio with help from the experts at Sungkyunkwan University.

Once you’ve successfully completed this course, you will be well-equipped to employ real data and programming skills to strengthen your investment portfolio and investment strategies.

This course is designed for students with financial economics knowledge who are interested in learning how to design, analyse, and test investment strategies and portfolio management systems through R or Python programming.

Syllabus

  • Analyzing Past Returns and Forecasting Future Returns
    • Welcome to the course!
    • What is Quantitative Investing?
    • Description of the Stock Price Data.
    • How to Analyze Asset Returns.
    • What Determines Future Investment Returns?
    • Forecasting Investment Returns with Factors.
    • Practice Project Week 1.
  • Understanding Risk Using Factors
    • How to Evaluate Investment Strategies?
    • How to Assess Risk.
    • Analyzing Market Risk Using CAPM.
    • How to Create a 3 Factor Model with the Tidyverse Package.
    • What is Risk Factor Analysis and Idiosyncratic Risk Analysis?
    • Practice Project Week 2.
  • Portfolio Analysis and Optimization
    • Downloading Data to Make a Portfolio of Multiple Assets.
    • Preparing Data for Portfolio Optimization.
    • How to Create an Optimized Portfolio using Historical Data.
    • Practice Project Week 3.
  • Performance Analysis
    • Graphing and Comparing Multiple Portfolios.
    • How to Summarize the Result from Optimization.
    • How to Add Constraints to Portfolio Optimization.
    • Evaluate Asset Performance Using PerformanceAnalytics Package.
    • How to Compare Constrained and Unconstrained Portfolios.
    • Final project.
    • Congratulations on finishing the whole course!

Taught by

Youngju Nielsen

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