Skill Introduction

In this course we focus on data analytics in finance. First, we introduce modern portfolio theory. This theory attempts to analyze the interrelationship between different investments and identify the mix of assets that will maximize the expected returns for a given level of risk.

We will also introduce you to algorithmic trading, which is basically a set of rules that are given to a computer using trend analysis techniques. This type of trading strategy can be useful because it removes emotional responses from individuals. It’s also useful because of the speed at which it can be implemented.

We will show you how to use R to get stock data and perform useful calculations related to modern portfolio theory. Finally, we will illustrate how to use R to identify when to change positions using a trend-following strategy, and how you can backtest that strategy to evaluate its profitability.

Learning Outcomes

Upon successful completion, you will be able to:

  • Explain the benefits of diversification

  • Backtest an algorithmic trading strategy in R

  • Recognize four algorithmic trading strategies

  • Understand modern portfolio measurements: expected return, risk and volatility, and the Sharpe Ratio

  • Identify opportunities for making investment opportunities through identifying risks and returns and through visualizing efficient frontiers

Course curriculum

  • 1


    • Jose Rodriguez - Portfolios in Practice

    • Introduction to the Skill

    • Glossary

  • 2

    Content and Activities

    • Portfolio Theory - Introduction

    • Portfolio Theory - Expected Returns

    • Knowledge Check 1

    • Portfolio Theory - Risk of a Security

    • Portfolio Theory - Risk/Return Tradeoff

    • Knowledge Check 2

    • Portfolio Theory - Weights and Efficient Frontier

    • Portfolio Theory - Capital Allocation

    • Portfolio Theory - Diversification

    • Knowledge Check 3

    • Introduction to Algorithmic Trading

    • Introduction to Algorithmic Trading - Trend Following Strategy

    • Introduction to Algorithmic Trading - Backtesting

    • Introduction to Algorithmic Trading - R Example

    • Knowledge Check 4

  • 3

    Application Exercise

    • Instructions

    • Exercise Files

    • Debriefing

  • 4


    • Conclusion

    • Final Quiz

    • Survey Instructions

    • Feedback Survey

    • Survey Verification

    • Next Steps

Begin your learning today.