Time Series Analysis

Criteria

Base Mark

Graded Mark

Comments

Explain Time Series

10 marks

Demonstrate the application of Time Series

70 marks

Limitations

10 marks

Referencing, presentation

10 marks

Total

100 marks

1.0 Introduction3

2.0 Time Series Components3

2.1 Secular Trend3

2.2 Cyclic Variation4

2.3 Seasonal Variation4

2.3.1 Seasonal movements or Seasonal Variations4

2.4 Irregular Variations5

3.0 Decomposition of a Time Series6

3.1 Seasonality6

3.2 Trend6

3.3 Cycle6

4.0 Time Series for Forecasting7

4.1 Using Time Series for Forecasting10

5.0 Time Series Analysis and Business Management of Retail Store10

Conclusion12

References13

Appendices14

Annex A14

Annex B14

Annex C16

Annex D16

Annex E17

Time Series Analysis

1.0 Introduction

A time series is a set of sequential measurements that cater to different types of business and economic datsa is examined on the variable at very close to points in time. This is the tool that many businesses can be benfitted from. The way its conducted is discussed in this study. This report will also analyse the graphical representation of the statistical tool.

2.0 Time Series Components

The component of Time series is of four types. We will discuss these types starting with The Trend then explain cyclical variation and will conclude by reviewing seasonal and irregular variations.

2.1 Secular Trend

The secular time series represent the data which depicts long term trends such as sales in our case of retail management. The data can also of employment figures, share prices, and other trade or economic series data. Many macroeconomic variables such as gross national product (GNP), employment and production industry is dominated by a strong trend. The property of a time series is in the representation of growth or decrease in series over a extended period in the long term. The basic forces help explain the trend of a series are population growth, price inflation, the exchange of technology and increases in productivity. That is, secular movements contain long-term smooth movements, which are dominated primarily by economic factors.

2.2 Cyclic Variation

The second most important component of a time series is the Cyclic Variation; rise and fall of a number of times in greater than one year. The illustration of cyclical component is shown in the waveform variation around the trend, usually affected by general economic conditions. It is common for cyclical fluctuations to be influenced by changes in economy expansion/contraction and contraction, which is commonly termed as the business cycle.

Cyclic movements or variations refer to the long-term oscillations about the trend curve, which be periodic that follow paths similar in equal time intervals (Hamilton, 1989, p.367). They are characterized by periods of expansion and contraction. In general, cyclic movements considered only if it occurs at an interval of time longer than a year.

2.3 Seasonal Variation

Seasonal variations can be described as patterns of change in a number of times in one year (Brockwell & Davis, 2009, p.466). Such patterns tend to recur every year. In the case of the monthly series, the seasonal variability measured series of January, February, etc. In the quarterly series we divide the timeline into four seasonal parts, one for each quarter. The seasonal variation may reflect conditions of weather, holidays or the length of calendar months.

2.3.1 Seasonal movements or Seasonal Variations

Seasonal movements refer to the periodic fluctuations observed ...