Project Description

When you assess whether to invest in an asset, you want to look not only at how much money you could make but also at how much risk you are taking. The Sharpe Ratio, developed by Nobel Prize winner William Sharpe some 50 years ago, does precisely this: it compares the return of an investment to that of an alternative and relates the relative return to the risk of the investment, measured by the standard deviation of returns.

In this project, you will apply the Sharpe ratio to real financial data using pandas. Before starting this project you, should have completed the DataCamp course Importing and Managing Financial Data using Python.

Project Tasks

  • 1 Meet Professor William Sharpe
  • 2 A first glance at the data
  • 3 Plot & summarize daily prices for Amazon and Facebook
  • 4 Visualize & summarize daily values for the S&P 500
  • 5 The inputs for the Sharpe Ratio: Starting with Daily Stock Returns
  • 6 Daily S&P 500 returns
  • 7 Calculating Excess Returns for Amazon and Facebook vs. S&P 500
  • 8 The Sharpe Ratio, Step 1: The Average Difference in Daily Returns Stocks vs S&P 500
  • 9 The Sharpe Ratio, Step 2: Standard Deviation of the Return Difference
  • 10 Putting it all together
  • 11 Conclusion
Stefan Jansen
Stefan Jansen

Founder & Lead Data Scientist at Applied Artificial Intelligence

Stefan has applied data science to business, investment and policy decisions for over 15 years. He has built an early warning system for financial crises, and worked as advisor to Central Banks and the World Bank before moving into fintech. He is founder and lead data scientist at Applied Artificial Intelligence, and instructor at General Assembly.

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  • Python