S&P500 Sharpe ratio
In this exercise, you're going to calculate the Sharpe ratio of the S&P500, starting with pricing data only. In the next exercise, you'll do the same for the portfolio data, such that you can compare the Sharpe ratios of the two.
Available for you is the price data from the S&P500 under sp500_value. The risk-free rate is available under rfr, which is conveniently set to zero. Let's give it a try!
This exercise is part of the course
Introduction to Portfolio Analysis in Python
Exercise instructions
- Calculate the total return of the S&P500 pricing data
sp500_valueusing indexing and annualize the total return number; the data spans 4 years. - Calculate the daily returns from the S&P500 pricing data, you'll need this for the volatility calculation.
- Calculate the standard deviation from the returns data and annualize the number using 250 trading days.
- Finally, calculate the Sharpe ratio using the annualized return and the annualized volatility and print the results.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate total return and annualized return from price data
total_return = (sp500_value[____] - ____[____]) / ____[____]
# Annualize the total return over 4 year
annualized_return = ((____ + ____)**(____/____))-1
# Create the returns data
returns_sp500 = ____.____()
# Calculate annualized volatility from the standard deviation
vol_sp500 = ____.____() * np.sqrt(____)
# Calculate the Sharpe ratio
sharpe_ratio = ((____ - rfr) / ____)
print (sharpe_ratio)