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Checking Monotonicity and Marginals of the Clayton Copula

Article Quant Q&A · Author: MarissaB

Summary

The document examines how to verify two copula properties for the bivariate Clayton model: that the function is non-decreasing in each input and that its one-variable margins are uniform. It distinguishes these checks, showing that boundary identities such as setting one input to one establish the marginal property, while monotonicity requires comparing outputs at ordered input values with the other input held fixed.

The response derives monotonicity from the negative exponent on each input and the negative power applied to the combined expression, which reverses the inequality a second time. It also points out that a complete copula verification needs well-definedness on the unit square and the rectangle inequality. The discussion is limited to the stated properties and does not provide a full proof of the rectangle condition. A brief secondary answer suggests derivatives for monotonicity and integration for deriving a marginal density.

Key ideas

  • Uniform margins are checked by setting all but one argument to one.
  • Monotonicity requires comparing function values at ordered inputs while holding the other input fixed.
  • The negative power in the Clayton formula reverses the relevant inequality.
  • A complete copula proof also needs well-definedness and the rectangle inequality.

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Full text
# Verifying two properties of the Clayton Copula


# Verifying two properties of the Clayton Copula












So I'm trying to verify the first two properties of a copula for the Clayton model. The first two properties being:

- $C(u_1,…,u_d)$ is non-decreasing in each component, $u_i$

- The $i^{th}$ marginal distribution is obtained by setting $u_j=1$ for $j≠i$ and since it is uniformly distributed, $C(1,…,1,u_i,1,…,1)=u_i$.

The Clayton copula is defined as: $$C(u,v,\theta)=(u^{-\theta}+v^{-\theta}-1)^{- \frac{1}{\theta} }, \theta>0$$

I might be going about this completely wrong, but are these two properties the same as saying:

- $C(u,0,\theta)=C(0,v,\theta)=0$

- $C(u,1,\theta)=u$ and $C(1,v,\theta)=v$

In which case,

$$C(u,0,\theta)=(u^{-\theta}+1-1)^{-\frac{1}{\theta}}=(1+v^{-\theta}-1)^{- \frac{1}{\theta} }=C(0,v,\theta)$$

$$\implies C(u,0,\theta)=(u^{-\theta})^{-\frac{1}{\theta}}=(v^{-\theta})^{- \frac{1}{\theta} }=C(0,v,\theta)$$

$$\implies C(u,0,\theta)=u=v=C(0,v,\theta)$$

And for the second property:

$$C(u,1,\theta)=(u^{-\theta}+1^{-\theta}-1)^{-\frac{1}{\theta}}, C(1,v,\theta)= (1^{-\theta}+v^{-\theta}-1)^{- \frac{1}{\theta} }$$

$$\implies C(u,1,\theta)=(u^{-\theta}+1-1)^{-\frac{1}{\theta}}, C(1,v,\theta)=(1+v^{-\theta}-1)^{- \frac{1}{\theta} }$$

$$\implies C(u,1,\theta)=(u^{-\theta})^{-\frac{1}{\theta}}, C(1,v,\theta)=(v^{-\theta})^{- \frac{1}{\theta} }$$

$$\implies C(u,1,\theta)=u, C(1,v,\theta)=v$$

## Answer by g g (score 2, accepted)

https://quant.stackexchange.com/a/45084

Your reasoning for the first property does not look correct or at least I do not understand it. Your arguments for the second property seem sound. But your wording of the second property is a bit fuzzy. You should state this more clearly, for example: $C(1,\ldots,1,u_j,1,\ldots,1) = u_j$ for all $u_j\in [0,1]$ and $j\in 1,\ldots, d.$

You don't mention it but in addition to the two properties you state you would need to show two more properties to make sure Clayton is a proper copula. First that $C$ is a well defined function from the unit cube to $[0,1]$ and then the rectangle inequality, which is slightly more involved.

For your property 1. you need to show that $C(u_1,v) \le C(u_2,v)$ for all $v\in[0,1]$ and $0\le u_1\le u_2\le 1$ and the analogous statement for $v$.

Once you established well definedness, you can argue as follows: $-\theta <0$ hence $u_1^{-\theta}\ge u_2^{-\theta}$, which means $u_1^{-\theta} + v^{-\theta} -1 \ge u_2^{-\theta} + v^{-\theta} -1$. Now the exponential with $-\frac{1}{\theta}$ flips the inequality again and you conclude $$(u_1^{-\theta} + v^{-\theta} -1)^{-\frac{1}{\theta}} \le (u_2^{-\theta} + v^{-\theta} -1)^{-\frac{1}{\theta}}.$$

## Answer by Tak wa Ng (score 1)

https://quant.stackexchange.com/a/45079

- Fix u, obtain derivative of v. And do it again for fixing v.

- To get marginal density of v, one has to do the integration w.r.t. u

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.