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Let τ be a stopping time and Y a positive ({mathcal {F}}_{T} -measurable random variable.

Let τ be a stopping time, and K a positive real number.

Let τ be a stopping time and Open image in new window an upper semianalytic function.

be a stopping time describing the maturity of the risky asset.

Let Open image in new window, let τ be a stopping time such that τ≥s and ({mathbb {P}}in {mathcal {P}}(s,bar {omega })).

be a stopping time describing the maturity of the risky asset and X τ be the final payoff or liquidation value at time τ.

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Similar(53)

If (W = {W_{t}}_{tgeq0}) is a measurable process and τ is a stopping time, then ({W_{tauwedge t}}_{tgeq0}) is called a stopped process of W.

In classical probability theory, a random time T is a stopping time in a filtration (Ft t⩾0 if and only if the optional sampling holds at T for all bounded martingales.

as (N to infty ) for any (tleq T), so that the local solution becomes a global solution where (tau_{N}) is a stopping time which is defined in Section 3.

The solution is defined on a random interval ([0,tau^ u_{0},omega))). Here (tau^ u_{0},omega)) is a stopping time such that tau^ u_{0},omega)=+inftyquad textit{or} quad lim _{trightarrowtau ^ u_{0},omega)}biglVert u t,omega bigrVert _{Sigma}=+ infty.

In this paper, the random time τ we consider does not necessarily satisfy the intensity nor the density hypothesis: it is a general stopping time in (mathbb {F}) and may also contain a predictable part.

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