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QMB3250 Final Exam with correct answers
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QMB3250 Final Exam with correct answers
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QMB3250 Final Exam with correctanswers
Seasonal Component - ANSWER: ➡ Fluctuation is the same magnitude at the same time each
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year
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deseasonalized - ANSWER: ➡ seasonal component removed o o oo o o o
period - ANSWER: ➡ time between 2 peaks
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smoothing methods advantages and disadvantages - ANSWER: ➡ Advantage: No assumptions
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must be made about a trend or about a seasonal component.
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Disadvantage: Predictions are limited - can only predict in the very short term. These are
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usually only used for one period beyond the data recorded.
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the smooth point before is the - ANSWER: ➡ predicted point at the next time
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Disadvantages of moving averages - ANSWER: ➡ The moving average values can be affected
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by outliers (sharp peaks or falls).
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Doesn't work well when there are strong seasonal, trend or cyclical components.
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Smaller alpha in simple exponential smoothing - ANSWER: ➡ smoother
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alpha close to 0.5 - ANSWER: ➡ the most recent value and historic values are weighted the
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same
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alpha is close to 1 - ANSWER: ➡ the most recent value is given more weight
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, You want to use this if you want the series to react more quickly to irregular components.
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alpha close to 0 - ANSWER: ➡ the most recent value is given less weight than historic values.
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You want to use this if you want the series to react more slowly, creating a more stable series
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disadvantages of simple exponential smoothing - ANSWER: ➡ Doesn't usually work well
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when seasonal components are present
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Also misses peaks
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simple exponential smoothing forecast error - ANSWER: ➡ real - predicted
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autoregressive model - ANSWER: ➡ uses regression methods to determine the weights for
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previous terms
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best for quarterly trends
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its the model that uses lags
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advantages of multiple regression model - ANSWER: ➡ Better at fitting series that have trend,
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cyclical, and seasonal components
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Allow us to predict more than just the next point
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Allow us to investigate each of the components separately
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additive and multiplicative o o
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