Time series analysis

Time series is another very important form of data. It is more widely used in stock markets, market analysis, and signal processing. The data has a time dimension, which makes it look like a signal. So, in most cases, signal analysis techniques and formulae are applicable for time series data, such as autocorrelation, crosscorrelation, and so on, which we have already dealt with in the previous chapters. In this recipe, we will deal with methods to get around and work with datasets with the time series format.

Getting ready

To get ready for the recipe, the TimeSeries and MarketData libraries have to be installed and imported. We install them using the Pkg.add() function, as follows:

Pkg.add("TimeSeries")
Pkg.add("MarketData")

Then the package has to be imported for use in the session. It can be imported through the using ... command, as follows:

using TimeSeries
using MarketData

How to do it...

1. The TimeArray format from the TimeSeries package makes it easy to interpret...