The adjustment coefficient is a positive root of in the classical risk model. When the moment-generating function is finite at , the process is a continuous-time martingale. It yields the Lundberg inequality and, under the relevant tilted integrability, the Cramér–Lundberg ruin asymptotic.
If each claim includes an independent expense , replace its payment law by the convolution of independent random variables . Its moment-generating function is and its expected value is . Keeping the relative safety loading fixed therefore changes the premium rate as well. The new coefficient solves , within the common finite-transform domain.
For positive claims with finite nonzero expected value , the function is continuous and strictly increasing on the positive finite-transform domain, starting at . If diverges at a finite upper endpoint, or is finite for all positive arguments, the secant slope tends to infinity. In the latter case use for some of positive tail probability. Every target with positive relative safety loading therefore has exactly one positive root.
For a classical risk model with adjustment coefficient , the ultimate ruin probability from capital satisfies . Stop the exponential continuous-time martingale at ruin or a finite horizon, bound its value on the ruin event, and then increase the horizon.
In the classical risk model with positive relative safety loading and adjustment coefficient , tilting the ruin defective renewal equation gives a proper renewal equation. The key renewal theorem yields . The constant is positive if the denominator is finite and zero if it is infinite; the claim-size density provides the nonarithmetic hypothesis.
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