Linear filters play a fundamental role in signal processing. With a linear filter, one can extract meaningful information from a digital signal.
In this recipe, we will show two examples using stock market data (the NASDAQ stock exchange). First, we will smooth out a very noisy signal with a low-pass filter to extract its slow variations. We will also apply a high-pass filter on the original time series to extract the fast variations. These are just two common examples among a wide variety of applications of linear filters.
Download the Nasdaq dataset from the book's GitHub repository at https://github.com/ipython-books/cookbook-data and extract it in the current directory.
The data has been ...