Explanation:
A time series process that exhibits serial independence, is serially uncorrelated, and is normally distributed is referred to as normal (Gaussian) white noise. A time series process that exhibits both a lack of serial correlation and serial independence is referred to as independent white noise (or strong white noise). A time series process with no mean, constant variance, and no serial correlation is referred to as white noise (or zero-mean white noise).
(Book 2, Module 21.1, LO 21.c)
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Question 82
A hedge fund manager is analyzing a time series process of copper returns in order to identify historical patterns that may be useful in forecasting future copper price movements. Her analysis of the time series indicates that it exhibits serial independence, is serially uncorrelated, and is normally distributed. Which white noise process is most likely associated with this time series?
A
Independent white noise.
B
Zero-mean white noise.
C
Gaussian white noise.
D
Strong white noise.
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