Lecture 3_powerpoint2007

# Lecture 3_powerpoint2007 - Click to edit Master subtitle...

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Unformatted text preview: Click to edit Master subtitle style 8/5/11 Lecture 3 Moving average and exponential smoothing 8/5/11 Moving Averages A moving average is obtained by calculating the mean for a specified set of values and then using it to forecast the next period. That is, n X X X M n t t t t ) ( 1 1 +-- + ⋅ ⋅ ⋅ + + = (3.1) t t M F = + 1 (3.2) Where Moving average and exponential smoothing t X is the observation at time t n is the number of periods moving window = + 1 t F forecast value for period t +1 made at time t 8/5/11 Example 3-1 Moving average Moving average and exponential smoothing The first moving average at Sep-85 is 248.90 3 ) ( 2 1 1-- + + + = t t t t Y Y Y Y 90 . 248 3 38 . 238 81 . 250 53 . 257 = + + The forecast value at Dec-85 is 248.90 (Assume n = 3), M ic ro soft O ffic e l 9 7 -2 0 0 3 W o rk s 8/5/11 Remarks on Moving Averages • Good for stationary data • Lag-length determined optimally by underlying cycle • Difficult to capture peaks and troughs of the series - fail to deal with non-stationary data • Equal weight Moving average and exponential smoothing 8/5/11 Simple Exponential Smoothing Moving average and exponential smoothing Simple exponential smoothing takes the form of:...
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Lecture 3_powerpoint2007 - Click to edit Master subtitle...

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