07. Skewness in Finance Demo

PRDTM2-786 AI Trading C3 L2 5 Skewness Demo V3

Calculating & Annualizing Volatility in Python

Learn how to calculate and annualize the volatility of S&P 500 futures using Python by following these steps:

  1. Setup Essentials:

    • Ensure access to yfinance library for data download.
    • Install using pip install yfinance or conda install yfinance.

  2. Download Data:

    • Use yfinance to fetch S&P 500 futures data with ticker "ES=F", ensuring coverage from the first to the latest available dates.

  3. Calculate Daily Returns:

    • Focus on the "adjusted close" prices. Employ the percentage change method to compute daily returns.

  4. Compute Daily Volatility:

    • Utilize the standard deviation function to find daily volatility.
    • For clarity, round the result to four decimal places, e.g., 1.23%.

  5. Annualize Volatility:

    • Convert daily volatility to annualized terms by multiplying with the square root of 252 (average trading days in a year).
    • Example outcome: Annualized volatility could be 19.5%.

Appropriate for assessing financial data risks, these techniques are invaluable for investors. Understanding skewness enhances insights into potential unusual gains or losses.

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