Calculate the contribution of each stock to the index

You have successfully built the value-weighted index. Let's now explore how it performed over the 2010-2016 period.

Let's also determine how much each stock has contributed to the index return.

This exercise is part of the course

Manipulating Time Series Data in Python

Exercise instructions

We have already imported pandas as pd and matplotlib.pyplot as plt for you. We have also loaded components and the index you worked with in the last exercise.

Divide the last index value by the first, subtract 1 and multiply by 100. Assign the result to index_return and print it.
Select the 'Market Capitalization' column from components.
Calculate the total market cap for all components and assign this to total_market_cap.
Divide the components' market cap by total_market_cap to calculate the component weights, assign it to weights, and print weights with the values sorted in default (ascending) order.
Multiply weights by the index_return to calculate the contribution by component, sort the values in ascending order, and plot the result as a horizontal bar chart.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Calculate and print the index return here
index_return = ____
print(____)

# Select the market capitalization
market_cap = ____

# Calculate the total market cap
total_market_cap = ____

# Calculate the component weights, and print the result
weights = ____
print(____)

# Calculate and plot the contribution by component

Edit and Run Code