Could you please someone explain very simply if the below are correct ?
Based on the below definitions for autocorrelation and stationarity my understanding is :
a non-stationary variable will express autocorrelation
a time series with no-autocorrelation is stationary
Autocorrleation = it is the correlation of a variable between its current value and a period before. Autocorrelation refers to the degree of correlation of the same variables between two successive time intervals
A stationary time serie is one whose properties do not depend on the time at which the series is observed. A stationary time series is one whose statistical properties such as mean, variance, autocorrelation, etc. are all constant over time. Thus, time series with trends, or with seasonality, are not stationary — the trend and seasonality will affect the value of the time series at different times. A stationarity test of the variables is required because Granger and Newbold (1974) found that regression models for non-stationary variables give spurious results.
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