Example getdoc0a3a. 341KB Jun 04 2011 12:04:04 AM

measures of subordinators. Recall that the scale function is positive and increasing, and is involved in computing double exit probabilities for spectrally negative Lévy processes X , i.e. processes that can jump only downwards. More precisely, with T [−a,b] = inf{t ≥ 0 : X t b or X t −a} P X T [− y,x] x = W y W x + y , for all x 0 and y 0. Finally, let us point out a possible extension. For atomic Lévy measures our main results, Theorem 2 and Theorem 3, link the atoms of Π to points of non-differentiability of u q . It seems possible to extend this to higher order singularities of ¯ Πx. Such a generalization would be extremely useful for numerical computations of the scale function which is a basic quantity in insurance mathemat- ics as it allows for estimation and calculation the double exit probabilities which in the actuarial mathematics context are ruin probabilities. For more background see [CY05] and [AKP04].

2.3 Example

To motivate our findings, here is an illustrative example for which the renewal density u can be calculated explicitly and some non-trivial connections between the atom of Π and differentiability of u can be observed. Example 1. Suppose δ = 1 and Π consists of just one atom at 1 with mass 1, i.e. Π = δ 1 , implying that ¯ Π = 1 [0,1] . For x 1 one immediately obtains ux = P[X T x = x] = P[no jump before x] = e −x ¯ Π0 = e −x . For x ∈ [n, n + 1 we exploit the structure of the process more carefully. Since x n + 1, on the event of creeping at x there can be at most n jumps of height one before exceeding x. If precisely i ≤ n jumps occur, they need to appear before x − i as otherwise the drift would have pushed X above level x before the final jump implying P[X T x = x] = n X i=0 P[exactly i jumps before x − i]. As the number of jumps before x − i is Poissonian with parameter x − i we obtain ux = e −x : x 1, e −x + P n i=1 x−i i i e −x−i : x ∈ [n, n + 1. The graphs of u and it’s derivative are plotted in Figure 1. This first representation already sheds some light on the possible behavior of u for atomic Lévy measures: in general u is not monotone, is asymptotically linear at zero, and possibly non-differentiable. Let us consider the issue of differentiability in more detail. Apparently u is infinitely differentiable in the open intervals n, n + 1, n = 0, 1, ..., with u ′ x = −e −x : x 1, −e −x + P n i=1 x−i i−1 i−1 e −x−i − P n i=1 x−i i i e −x−i : x ∈ n, n + 1. 474 0.5 1 1.5 2 2.5 3 1 0.8 0.6 0.4 0.2 0.2 0.4 0.6 0.8 1 x ux Figure 1: u solid curve, u ′ dashed curve for δ = 1 and Π = δ 1 The only problematic points are the integers at which the piecewise defined function u ′ gets the additional summands e −x−1 − x − 1e −x−1 : n = 1, x−n n−1 n−1 e −x−n − x−n n n e −x−n : n 1, when going from x n to x n. This sheds some light on differentiability as for x = 1 the right deriva- tive is 1 and the left derivative 0 whereas for n 1 the remainder summand vanishes. In particular, this implies that u is differentiable everywhere except at 1 with u ′ x+ − u ′ x− = Π{x}. Taking higher order derivatives, the same reasoning shows that at {n}, u is n−1-times but not n-times differentiable. The example reveals three properties which we aim to understand for general subordinators: higher order differentiability of u depends crucially on the atoms of Π, u is generally not monotone and u ′ vanishes at infinity and is asymptotically linear at zero. 3 Results Our Fourier analytic approach forces us to control the small jumps. To this end we recall the Blumenthal-Getoor index βΠ for subordinators: βΠ = inf n γ 0 : Z 1 x γ Πd x ∞ o . Some of our main results are formulated under the following assumption. Assumption A. Assume that βΠ 1. Note that property 1.1 implies that βΠ ≤ 1 so that the assumption only rules out boundary cases and in particular any stable subordinator with drift is included. More direct computations for particular examples of interest show that our results will be still valid for Blumenthal-Getoor index 1. 475

3.1 Series and Integral Representations

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