Python Pandas: Filter Time Series Data by Option Expiration & Low Volatility Duration | Part 13 📅
@MattMacarty
🐍 Python Pandas: Filter Time Series Data by Option Expiration & Low Volatility Duration | Part 13
Welcome to *Part 13* of the Python Stock Analysis Course! This video concludes Section 2 on Individual Security Analysis by adding advanced data filtering capabilities to our custom `Stock` class.
You will learn how to create two methods that slice the stock's data, allowing you to focus your analysis only on days relevant to high-impact financial events or market conditions.
🎯 Key Learning Outcomes:
1. *Option Expiration Filter:* Implement logic to create a data mask that isolates the *Third Friday* of every month, which corresponds to the main monthly *Option Expiration* date.
2. *Date Filtering with Pandas:* Utilize *NumPy's `np.where`* and *Pandas' DatetimeIndex properties* (day and weekday) to accurately define the expiration mask.
3. *Low Volatility Duration:* Write a non-vectorized, iterative method to track the number of *consecutive days* since the last **Two Standard Deviation (2-