Conjectured distribution formula for the ascending Lévy process supremum

Let XtX_t be a Lévy process whose Lévy–Khintchine exponent ff is a balanced Rogers function. Let ζf\zeta_f be the canonical parametrisation of γf\gamma_f, let λf(r)=f(ζf(r))\lambda_f(r)=f(\zeta_f(r)), let f[ζ]f_{[\zeta]}^\uparrow be the Wiener–Hopf factor, and let Ff(r;x)F_{f\uparrow}(r;x) be the function described by the preceding definitions. Assume

sup{Imζf(r):r(0,)}<,\sup\{\operatorname{Im}\zeta_f(r):r\in(0,\infty)\}<\infty, sup{ϑf(r):r(0,)}<π2,\sup\{\vartheta_{f\uparrow}(r):r\in(0,\infty)\}<\frac{\pi}{2},

and, for some t0[0,)t_0\in[0,\infty),

1f[ζf(r)](iζf(r))f[ζf(r)](0+)et0λf(r)λf(r)dr<.\int_1^\infty \frac{|f_{[\zeta_f(r)]}^\uparrow(i\overline{\zeta_f(r)})|}{f_{[\zeta_f(r)]}^\uparrow(0^+)}e^{-t_0\lambda_f(r)}\lambda_f'(r)\,dr<\infty.

Conjectured supremum-distribution formula. For t>t0t>t_0 and x>0x>0,

P(Xt<x)=0f[ζf(r)](iζf(r))f[ζf(r)](0+)Ff(r;x)etλf(r)λf(r)dr.\mathbf{P}(X_t^\uparrow<x)=\int_0^\infty\frac{|f_{[\zeta_f(r)]}^\uparrow(i\overline{\zeta_f(r)})|}{f_{[\zeta_f(r)]}^\uparrow(0^+)}F_{f\uparrow}(r;x)e^{-t\lambda_f(r)}\lambda_f'(r)\,dr.

This would give a semi-explicit expression for the distribution of the ascending process supremum. The formula is expected to follow by interchanging integrations in the Laplace-transform representation and then inverting the transform; the required Fubini justification is not established here. The boundedness assumption on Imζf(r)\operatorname{Im}\zeta_f(r) may also be difficult to relax, even for strictly stable Lévy processes.

Sources & referencesView supporting material

Primary source

Mateusz Kwaśnicki, “Rogers functions and fluctuation theory”, arXiv:1312.1866 (2013).

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