Characteristic Equation for AR(p) Processes

Property 1: An AR(p) process is stationary provided all the roots of the following polynomial equation (called the characteristic equation) have an absolute value greater than 1.

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This is equivalent to saying that if z that satisfies the characteristic equation then |z| > 1.

In fact, setting w = 1/z, this is equivalent to saying that |w| < 1 for any w that satisfies the following equation

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By the Fundamental Theorem of Algebra, any pth degree polynomial has p roots; i.e. there are p values of z that satisfy the above equation. Unfortunately, not all of these roots need to be real; some can involve “imaginary” numbers such as \sqrt{-1}, which is usually abbreviated by the letter i. For example, the equation z2 + 1 has the roots i and –i as can be seen by substituting either of these values for z in the equation z2 + 1.

We now give three properties of imaginary numbers, which will help us avoid discussing imaginary numbers in any further detail:

  • all values which involve imaginary numbers can be expressed in the form a + bi where a and b are real numbers
  • if a + bi is a root of a pth degree polynomial, then so is a – bi
  • if z = a + bi then the absolute value of z is defined by |z| = \sqrt{a^2+b^2}

Since a and b are real numbers, not involving \sqrt{-1}, we only need to deal with real numbers.

Property 2: An AR(1) process is stationary provided |φ1| < 1

Property 3: An AR(2) process is stationary provided

|φ2| < 1 and |φ1| + φ2 < 1

Example 1: Determine whether the following AR(2) process is stationary.

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The roots of w2 – 2w + .5 = 0 are

Roots of characteristic value

This process is not stationary since 1 + √1.5 ≥ 1. You get the same result via Property 3 since |φ1| + φ2 = 2 – .5 = 1.5 ≥ 1.

Example 2: Determine whether the following AR(2) process is stationary.

Since

the roots of the reverse characteristic equation are not real. In fact

Thus

and so we see that this AR(2) process is stationary. We get the same result via Property 3 since

Observation: It turns out that by Property 4 of Basic AR Concepts, for any k, ρk can be expressed as a linear combination

where w1, …, wp are the unique roots of the reverse characteristic equation

Real Statistics Function: The Real Statistics Resource Pack supplies the following array function where R1 is a p × 1 range containing the phi coefficients of the polynomial where φp is in the first position and φ1 is in the last position.

ARRoots(R1): returns a p × 3 range where each row contains one root, and where the first column consists of the real part of the roots, the second column consists of the imaginary part of the roots and the third column contains the absolute value of the roots

This function calls the ROOTS function described in Roots of a Polynomial. Note that just like in the ROOTS functions, the ARRoots function can take the following optional arguments:

ARRoots(R1, prec, iter, r, s)

prec = the precision of the result, i.e. how close to zero is acceptable. This value defaults to 0.00000001.

iter = the maximum number of iteration performed when performing Bairstow’s Method. The default is 50.

r, s = the initial seed values when using Bairstow’s Method. These default to zero.

4 thoughts on “Characteristic Equation for AR(p) Processes”

  1. Hi there,
    But if we have a AR with infinitely many parameters, then the necessary condition for
    AR to be stationary is that the squared sum of the parameters has to finite. So in terms
    of this definition, Aa AR with finitely many parameters is always stationary. Am I missing something?

    Best,
    Farzali

    Reply

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