Cumulative return on $1,000 invested in google vs apple II

Apple outperformed Google over the entire period, but this may have been different over various 1-year sub periods, so that switching between the two stocks might have yielded an even better result.

To analyze this, calculate that cumulative return for rolling 1-year periods, and then plot the returns to see when each stock was superior.

Cet exercice fait partie du cours

Manipulating Time Series Data in Python

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Instructions

We have already imported pandas as pd and matplotlib.pyplot as plt. We have also loaded the GOOG and AAPL close prices from the last exercise into data.

Define a multi_period_return() function that returns the cumulative return from an array of period returns.
Calculate daily_returns by applying .pct_change() to data.
Create a '360D' .rolling() window on daily_returns, and .apply() multi_period_returns. Assign the result to rolling_annual_returns.
Plot rolling_annual_returns after multiplying it by 100.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Import numpy
import numpy as np

# Define a multi_period_return function
def multi_period_return(period_returns):
    return ____(____)
    
# Calculate daily returns
daily_returns = ____

# Calculate rolling_annual_returns
rolling_annual_returns = ____

# Plot rolling_annual_returns

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