Càdlàg

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In mathematics, a càdlàg function (from the French "continue à droite, limite à gauche") is a function defined on the real numbers (or a subset of them) that is everywhere right-continuous and has left limits everywhere. Càdlàg functions are important in the study of stochastic processes that admit (or even require) jumps, unlike Brownian motion, which has continuous sample paths. The collection of càdlàg functions on a given domain is known as Skorokhod space.

1 Definition
2 Examples
3 Skorokhod space
4 Properties of Skorokhod space
5 References

[edit] Definition

Let $(M, d)$ be a metric space, and let $E \subseteq \mathbb{R}$ . A function $f : E \to M$ is called a càdlàg function if, for every $t \in E$ ,

the left limit $f(t-) := \lim_{s \uparrow t} f(s)$ exists; and
the right limit $f(t+) := \lim_{s \downarrow t} f(s)$ exists and equals $f (t)$ .

That is, $f$ is right-continuous with left limits (in French: continue à droite, limite à gauche, hence càdlàg — the English equivalent, corlol for "continuous on (the) right, limit on (the) left" is somewhat less common).

[edit] Examples

All continuous functions are càdlàg functions.
As a consequence of their definition, all cumulative distribution functions are càdlàg functions.

[edit] Skorokhod space

The set of all càdlàg functions from $E$ to $M$ is often denoted by $D (E; M)$ (or simply $D$ ) and is called Skorokhod space after the Ukrainian mathematician Anatoliy Skorokhod. Skorokhod space can be assigned a topology that, intuitively allows us to "wiggle space and time a bit" (whereas the traditional topology of uniform convergence only allows us to "wiggle space a bit"). For simplicity, take $E = [0, T]$ and $M = \mathbb{R}^{n}$ — see Billingsley for a more general construction.

We must first define an analogue of the modulus of continuity, $\varpi'_{f} (\delta)$ . For any $F \subseteq E$ , set

$w_{f} (F) := \sup_{s, t \in F} | f(s) - f(t) |$

and, for $δ > 0$ , define the càdlàg modulus to be

$\varpi'_{f} (\delta) := \inf_{\Pi} \max_{1 \leq i \leq k} w_{f} ([t_{i - 1}, t_{i})),$

where the infimum runs over all partitions $\Pi = \{ 0 = t_{0} < t_{1} < \dots < t_{k} = T \}$ , $k \in \mathbb{N}$ , with $min i (t i - t i - 1) > δ$ . This definition makes sense for non-càdlàg $f$ (just as the usual modulus of continuity makes sense for discontinuous functions) and it can be shown that $f$ is càdlàg if and only if $\varpi'_{f} (\delta) \to 0$ as $\delta \to 0$ .

Now let $Λ$ denote the set of all strictly increasing, continuous bijections from $E$ to itself (these are "wiggles in time"). Let

$\| f \| := \sup_{t \in E} | f(t) |$

denote the uniform norm on functions on $E$ . Define the Skorokhod metric $σ$ on $D$ by

$\sigma (f, g) := \inf_{\lambda \in \Lambda} \max \{ \| \lambda - I \|, \| f - g \circ \lambda \| \}$ ,

where $I : E \to E$ is the identity function. In terms of the "wiggle" intuition, $\| \lambda - I \|$ measures the size of the "wiggle in time", and $\| f - g \circ \lambda \|$ measures the size of the "wiggle in space".

It can be shown that the Skorokhod metric is, indeed a metric. The topology $Σ$ generated by $σ$ is called the Skorokhod topology on $D$ .

[edit] Properties of Skorokhod space

[edit] Generalization of the uniform topology

The space C of continuous functions on E is a subspace of D. The Skorokhod topology on D coincides with the topology of uniform convergence on C.

[edit] Completeness

It can be shown that, although D is not a complete space with respect to the Skorokhod metric σ, there is a topologically equivalent metric σ₀ with respect to which D is complete.

[edit] Separability

With respect to either σ or σ₀, D is a separable space. Thus, Skorokhod space is a Polish space.

[edit] Tightness in Skorokhod space

By an application of the Arzelà-Ascoli theorem, one can show that a sequence $(\mu_{n})_{n = 1}^{\infty}$ of probability measures on Skorokhod space D is tight if and only if both the following conditions are met: