Financial Risk Manager Part 1
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An analyst is analyzing the sales and fitting time series model and found that sales are periodically spiked in autocorrelations as they gradually decay. Such behavior is most likely indicative of:
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NNikitesh
A
Seasonality in sales data
B
A regime change structural sales data series
C
A structural shift in sales data series
D
A differencing lag
Explanation:
In the presence of significant seasonality, the autocorrelation plot should show spikes at lags equal to the period. For monthly data, for instance, a seasonality effect would yield significant peaks at lag 12, 24, 36, 48, and so forth. The periodic spikes in autocorrelations that gradually decay are characteristic of seasonality patterns in time series data.
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