A space center is monitoring the weather pattern to schedule a departure time for its latest Martian explorer. An economist is readying his gross domestic product (GDP) forecasts to be used by equity traders, who are eager to know if we had a quarter of growth or another economic contraction. In both cases, they are relying on time series data. In the former instance to forecast a weather event, and in the latter to determine which direction GDP forecasts are headed. So, what do we mean by time series?

A series can be defined as a number of events, objects, or people of a similar or related kind coming one after another; if we add the dimension of time, we get a time series. A time series can be defined as a series of data points in time order. For example, the space center will use data from the last few years to predict the weather pattern. The data collection would have started a few years ago and subsequent data points would have given rise to an order in which data was been collected. Another aspect of the data that we usually observe is periodicity. For example, weather data would usually be collected daily, if not hourly. The periodicity of time series data is a slow-moving dimension as it seldom changes. The periodicity of recording observations is broadly driven by three factors, which are relevance, behavior driven, and purpose. In the case of weather patterns, we probably need to know how the weather will change over the course of the day. The point of sales (POS) data from debit card transactions of an individual will be recorded every time there is usage. GDP data, however, is usually aggregated in a time series format every quarter, as these numbers are usually reported on a quarterly basis by central banks or related institutions.

In this chapter, we will explore the following topics:

• Time series illustration
• The importance of time series
• Forecasting across industries
• Characteristics of time series data
• Challenges in data
• Good versus bad forecasts
• The use of time series in the financial industry