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.
Cet exercice fait partie du cours
Introduction to Portfolio Risk Management in Python
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.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de 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)