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Some Remarks in Statistical Independence and Fractional Age Assumptions
1. In t roduct ion Consider a general status (u) and its future Lifetime random variable T. Let tP~ ... and the fractional portion of T be S = T - [T], i.e. T = K + S. Assumptions with respect to the joint ...- Authors: Gordon E Willmot
- Date: Jan 1996
- Competency: External Forces & Industry Knowledge>Actuarial theory in business context
- Publication Name: Actuarial Research Clearing House
- Topics: Demography>Longevity; Finance & Investments>Risk measurement - Finance & Investments
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Martingales and Ruin Probability
and then use it to give a short proof of Lundb(ng s inequality. Theorem 1.1. Let X = (X,,)n~r be a sub-martingale ... E(X~ +) < E(iXN]). (1) A.P( ,nax X,, > A) < E(XN : u<,<N o _ < , , < N - - - - _ _ - - - - - - ...- Authors: Gordon E Willmot, Hailiang Yang
- Date: Jan 1996
- Competency: External Forces & Industry Knowledge>Actuarial theory in business context
- Publication Name: Actuarial Research Clearing House
- Topics: Finance & Investments>Risk measurement - Finance & Investments; Modeling & Statistical Methods>Stochastic models
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Non-exponential Bounds on the Tails of Compound Distributions
Pr (X=n)=p~, n = 0 ,1 ,2 , . . . . (1) Let S = X 1 + X 2 -1- . . . + X N (2) We are interested ... in estimating the tail probability (~,(x) = Pr (S > x), x > O, 3) which has applications in many ...- Authors: Gordon E Willmot, Xiaodong Sheldon Lin
- Date: Jan 1996
- Competency: External Forces & Industry Knowledge>Actuarial theory in business context
- Publication Name: Actuarial Research Clearing House
- Topics: Finance & Investments>Risk measurement - Finance & Investments; Modeling & Statistical Methods>Stochastic models