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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.

Este exercício faz parte do curso

Introduction to Portfolio Risk Management in Python

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Instruções do exercício

  • Calculate the daily standard deviation of the 'Returns' column and set it equal to sigma_daily.
  • Derive the daily variance (second moment, \( \sigma ^ {2} \)) by squaring the standard deviation.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# 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)
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