• 4 Marks

QT – May 2019 – L1 – Q5a – Forecasting

Explain the concepts of moving averages and exponential smoothing in time series forecasting.

The objective of smoothing methods is to smooth out the random variations due to irregular components of the time series and provide an overall impression of the pattern of movement in the data over time.

Required:
Explain the following smoothing methods:

i) Moving averages (2 marks)
ii) Exponential smoothing (2 marks)

i) Moving Averages: This method involves averaging the observations within a specific period and using it as an estimate of the mid-point of the period. It helps in smoothing the fluctuations in the time series by balancing the highs and lows over time.

(2 marks)

ii) Exponential Smoothing: In this method, greater weights are assigned to more recent data points compared to older data points. The most recent observation is given the highest weight, making it more responsive to changes in the data while still smoothing out random variations.

(2 marks)

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