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time series

Forums › Ask ACCA Tutor Forums › Ask the Tutor ACCA MA – FIA FMA › time series

  • This topic has 1 reply, 2 voices, and was last updated 1 year ago by John Moffat.
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  • December 27, 2021 at 9:27 am #644893
    AlinaaF
    Member
    • Topics: 21
    • Replies: 9
    • ☆

    You explained variations in your lecture but I needed some explanation.

    Types of variations:

    1) Trend:
    It is a historic data pattern of sales & costs over time for the future forecasting which refers to the direction in which the trend is moving towards. It is used for making future predictions and it is useful for budgeting.

    2) Cyclical variations:
    It is a historic data pattern of sales & costs taken over time for the future forecasting usually for a long-term. The shape of the graph is wave-like appearance taken number of years. The cyclical variations is used for long-term variations.

    3) Seasonal variations:
    It is a historic data pattern of sales & costs rise and fall taken over short period of time for the future forecasting. For example, ice cream sales are likely to be higher than average in winters and lower than average in summers. We are expected to identify the underlying pattern to find out the trend for forecasting in future with seasonal variation (ups and downs in sales due to seasonal demand). It is used for short-term variations.

    4) Random (residual) variations:
    These are other unpredictable variations.

    Please say if it is all correct and please tell me more about random variations in (4) what it is?

    December 27, 2021 at 1:18 pm #644901
    John Moffat
    Keymaster
    • Topics: 56
    • Replies: 51582
    • ☆☆☆☆☆

    It is all correct.

    Random variations are referring to the fact that no forecasting is ever going to be perfect. Think about correlation and regression – even if (for example) the total cost of something each month varies with the amount purchased, it is unlikely to be a perfect linear relationship and might be a little higher or a little lower – this happens at random and cannot be forecast.

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