Second moment: Variance
Just like you estimated the first moment of the returns distribution in the last exercise, you can can also estimate the second moment, or variance of a return distribution using numpy.
In this case, you will first need to calculate the daily standard deviation ( \( \sigma \) ), or volatility of the returns using np.std(). The variance is simply \( \sigma ^ 2 \).
StockPrices from the previous exercise is available in your workspace, and numpy is imported as np.
This exercise is part of the course
Introduction to Portfolio Risk Management in Python
Exercise instructions
- Calculate the daily standard deviation of the
'Returns'column and set it equal tosigma_daily. - Derive the daily variance (second moment, \( \sigma ^ {2} \)) by squaring the standard deviation.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate the standard deviation of daily return of the stock
sigma_daily = ____(StockPrices['Returns'])
print(sigma_daily)
# Calculate the daily variance
variance_daily = ____
print(variance_daily)