TOPIC Financial Time SeriesStatisticsSolutionFrom a form.pdf

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TOPIC: Financial Time Series/Statistics Solution From a formal point of view, white noise is defined in relation to the time as a random variable whose mean is a constant at time t where the covariance for each of the variables is zero for all i, j within the time series. It then states that a series is stationary with respect to time when its main parameters (mean, variance and covariance between pairs of data) are constant in relation to it, therefore, we can not conclude that the waste is a \"white noise\" . For most of the data over two autoregressive parameters or two moving-average parameters in the ARMA model are required..

TOPIC: Financial Time Series/Statistics
Solution
From a formal point of view, white noise is defined in relation to the time as a random variable
whose mean is a constant at time t where the covariance for each of the variables is zero for all i,
j within the time series.
It then states that a series is stationary with respect to time when its main parameters (mean,
variance and covariance between pairs of data) are constant in relation to it, therefore, we can not
conclude that the waste is a "white noise" .
For most of the data over two autoregressive parameters or two moving-average parameters in
the ARMA model are required.

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