When do you say that a Time Series is white noise?Answer choicesSelect only one optionREVISITWhen it has a constant mean of zero, a constant variance and there is a correlation between its values at different timesWhen it has a constant mean of zero, a constant variance and no correlation between its values at different timesWhen it has a constant mean of one, a constant variance of zero and no correlation between its values at different timesNone of the above

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. ####

Which of the following is false for a white noise process?a. zero meanb. finite variancec. independent and identically distributed (iid)d. volatility clustering

Which of the following is not true of a stationary time series?  The process generating the data has a constant mean.  The time series plot is a straight line.  The statistical properties are independent of time.  The variability is constant over time.

1. Suppose that the simple return of a stock follows the modelrt = 0.1 + at − 0.5at−2,where {at}Tt=1 follows a white noise process with mean zero and variance σ2a = 0.04. Pleasecompute the following:(a). What is the mean of rt?(b). What is the variance of rt?

Trend-stationarity implies that while a time series may have time-varying mean, its variance and covariances remain constant over time. True or False