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When a series follows a random walk model, it is said to be non-stationary. We can stationarize it by taking a first-order difference of the time series, which will produce a stationary series, that is, a Zero Mean White Noise series. For example, the stock prices of a stock follow a random walk model, and the series of returns (differencing of pricing series) will follow White Noise model.
