Analysis of Financial Data

Chapter 2. Basic data handling

This chapter introduces the basics of data handling. It focuses on four important areas:

1. The types of financial data that are commonly used.

2. A brief discussion of the sources from which data can be obtained.^[1]

3. An illustration of the types of graphs that are commonly used to present information in a data set.

4. A discussion of simple numerical measures, or descriptive statistics, often presented to summarize key aspects of a data set.

Types of financial data

This section introduces common types of data and defines the terminology associated with their use.

Time series data

Financial researchers are often interested in phenomena such as stock prices, interest rates, exchange rates, etc. This data is collected at specific points in time. In all of these examples, the data are ordered by time and are referred to as time series data. The underlying phenomenon which we are measuring (e.g. stock prices, interest rates, etc.) is referred to as a variable. Time series data can be observed at many frequentcies. Commonly used frequencies are: annual (i.e. a variable is observed every year), quarterly (i.e. four times a year), monthly, weekly or daily.^[2]

In this book, we will use the notation Y_t to indicate an observation on variable Y (e.g. an exchange rate) at time t. A series of data runs from period t = 1 to t = T. "T" is used to indicate the total number of time periods covered in a data set. To give an example, if we were to use monthly time series data from January ...