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A white noise process has the following characteristics: a. Zero mean: This is true. A white noise process has a constant mean that is equal to zero. b. Finite variance: This is true. The variance of a white noise process is constant and finite. c. Independent and identically distributed (iid): This is true. The observations in a white noise process are independent and identically distributed. d. Volatility clustering: This is false. In a white noise process, there is no volatility clustering. Volatility clustering refers to the phenomenon where periods of high volatility are followed by periods of high volatility and periods of low volatility are followed by periods of low volatility. This does not occur in a white noise process. ####

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A white noise process has the following characteristics:

a. Zero mean: This is true. A white noise process has a constant mean that is equal to zero.

b. Finite variance: This is true. The variance of a white noise process is constant and finite.

c. Independent and identically distributed (iid): This is true. The observations in a white noise process are independent and identically distributed.

d. Volatility clustering: This is false. In a white noise process, there is no volatility clustering. Volatility clustering refers to the phenomenon where periods of high volatility are followed by periods of high volatility and periods of low volatility are followed by periods of low volatility. This does not occur in a white noise process. ####

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