Time Series

Question 1

What is a time series

Answer 1

A time series is a series of figures recorded over time, e.g. unemployment over the last 5 years, output over the last 5 months, etc.

Question 2

What is a time series used for

Answer 2

• Identify whether there is any underlying historical trend and if there is, measure it.
• Use this analysis of the historical trend to forecast the trend into the future.
• Identify whether there are any seasonal variations around the trend, and if there is measure them.
• Apply estimated seasonal variations to a trend line forecast in order to prepare a forecast season by season.
  In other words, a trend over time, established from historical data, and adjusted for seasonal variations, can then be used to make predictions for the future.

Question 3

What is a trend

Answer 3

It is a long term movment whether it be upwards, downwards ot sideways

Question 4

What is a seasonal variation

Answer 4

Seasonal variations are short-term fluctuations in value due to different circumstances which occur at different times of the year, on different days of the week, different times of the day, etc. Some examples might be

• Ice cream sales are higher in summer
• Sales of groceries are highest on Saturdays
• Traffic is greatest in the morning and evening rush hours
• If there is a straight-line trend in the time series, seasonal variations must cancel each other out. The total of the seasonal variations over each cycle should be zero
• Seasonal variations can be measured
• In units or in money values, or
• As a percentage value or index value in relation to the underlying trend

Question 5

• What are the three main methods of finding the underlying trend of data

Answer 5

(1) Inspection. The trend line can be drawn by eye with the aim of plotting the line so that it lies in the middle of the data
(2) Least squares regression analysis. The X axis represents time and periods of time are numbers, e.g. January is 1, February is 2, March is 3 etc.
(3) Moving averages. This method attempts to remove seasonal or cyclical variations by a process of averaging.

Question 6

What are the advantages and disadvantages of time series analysis

Answer 6

Advantages

• Reflects the underlying pattern
• Simple and cheap method of forecasting
• Can be developed to a more complex model

Disadvantages

• Assumes all changes are time related
• Equal weight is given to all figures regardless of how old they are
• Past data is not always reliable and extrapolation is inherently risky