What does time series stationarity mean?

In t he most intuitive sense, stationarity means that the statistical properties of a process generating a time series do not change over time . It does not mean that the series does not change over time, just that the way it changes does not itself change over time.

Why is stationary a desirable property for a time series process?

17) Stationarity is a desirable property for a time series process. When the following conditions are satisfied then a time series is stationary. These conditions are essential prerequisites for mathematically representing a time series to be used for analysis and forecasting. Thus stationarity is a desirable property.

Which conditions are necessary for stationary time series?

A Time Series is stationary if has the following conditions: 1. Constant µ (mean) for all t. 2. Constant σ (variance) for all t.

Which of the following are characteristics of a stationary process?

Which of the following are characteristics of a stationary process? Part of the definition of a stationary process is that it has constant mean and constant variance. A series with constant mean would also cross that mean value frequently, and will obviously not contain a trend.

What are the 3 conditions for a time series to be covariance stationary?

In a time series, a variable is covariance stationary if the following are true (Watsham & Parramore, 1997): The expected value E(Xt), is a finite constant for all t, variance (σ2} is a finite constant for all t, The correlation coefficient between Xt and Xt – n is equal for all t.

What are the types of stationary explain its importance?

Types of Stationary First-order stationarity series have means that never changes with time. Any other statistics (like variance) can change. Second-order stationarity (also called weak stationarity) time series have a constant mean, variance and an autocovariance that doesn’t change with time.

What is an example of a stationary time series?

A time series is called stationary if it doesn’t wander off to infinity or it stays around the mean. In simple terms, a price series which doesn’t have much price movement is called stationary. Example of stationary price series (theoretical): Unfortunately, most price series are not stationary.

What is weak stationarity?

Stationary process is the one which generates time-series values such that distribution mean and variance is kept constant. Strictly speaking, this is known as weak form of stationarity or covariance/mean stationarity. Weak form of stationarity is when the time-series has constant mean and variance throughout the time.

What is a stationary variable?

A sequence of random variables is covariance stationary if all the terms of the sequence have the same mean, and if the covariance between any two terms of the sequence depends only on the relative positions of the two terms, that is, on how far apart they are located from each other, and not on their absolute position, that is, on where they are