1,721,015 research outputs found

    Universal methods for generating random variables with a given characteristic function

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    Universal generators for absolutely-continuous and integer-valued random variables are introduced. The proposal is based on a generalization of the rejection technique proposed by Devroye [The computer generation of random variables with a given characteristic function. Computers and Mathematics with Applications. 1981;7:547–552]. The method involves a dominating function solely requiring the evaluation of integrals which depend on the characteristic function of the underlying random variable. The proposal gives rise to simple algorithms which may be implemented in a few code lines and which may show noticeable performance even if some classical families of distributions are considered

    On the Generalized Benford's law

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    We provide some properties of the Generalized Benford law – a flexible model for the distribution of significant digits – which accurately describes the pattern of leading digits in the sequences of prime numbers and of non-trivial Riemann zeta zeros. © 2020 Elsevier B.V

    Skorohod representation on a given probability space

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    Let (Ω,A,P)(\Omega,\mathcal{A},P) be a probability space, SS a metricspace, μ\mu a probability measure on the Borel σ\sigma-field ofSS, and Xn:ΩSX_n:\Omega\rightarrow S an arbitrary map,n=1,2,n=1,2,\ldots. If μ\mu is tight and XnX_n converges indistribution to μ\mu (in Hoffmann-J\o rgensen's sense), thenXμX\sim\mu for some SS-valued random variable XX on(Ω,A,P)(\Omega,\mathcal{A},P). If, in addition, the XnX_n aremeasurable and tight, there are SS-valued random variablesXn\overset{\sim}{X}_n and XX, defined on(Ω,A,P)(\Omega,\mathcal{A},P), such that XnXn\overset{\sim}{X}_n\sim X_n,XμX\sim\mu and XnkX\overset{\sim}{X}_{n_k}\rightarrow X a.s. forsome subsequence (nk)(n_k). Further, \overset{\sim}{X}_n\rightarrowX a.s. (without need of taking subsequences) if μ{x}=0\mu\{x\}=0 forall xx, or if P(Xn=x)=0P(X_n=x)=0 for some nn and all xx. When PP isperfect, the tightness assumption can be weakened intoseparability up to extending PP to σ(A{H})\sigma(\mathcal{A}\cup\{H\})for some HΩH\subset\Omega with P(H)=1P^*(H)=1. As a consequence, inapplying Skorohod representation theorem with separableprobability measures, the Skorohod space can be taken((0,1),σ(U{H}),mH)((0,1),\sigma(\mathcal{U}\cup\{H\}),m_H), for some H(0,1)H\subset(0,1) with outer Lebesgue measure 1, where U\mathcal{U} is theBorel σ\sigma-field on (0,1)(0,1) and mHm_H the only extension ofLebesgue measure such that mH(H)=1m_H(H)=1. In order to prove theprevious results, it is also shown that, if XnX_n converges indistribution to a separable limit, then XnkX_{n_k} converges stablyfor some subsequence (nk)(n_k)

    Aggregation of not independent experts' opinions under ambiguity

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    We consider an aggregation scheme of opinions expressed through different probability distributions or multiple priors decision model. The decision-maker adopts entropy maximization as a measure of risk diversification and a rational form of prudence for valuing uncertain outcomes. We show a new aggregation rule based on the composite value function that is able to represent asymmetric attitude on extreme events (optimism with respect to windfall gains and pessimism with respect to catastrophic events) and a rational prudence on ordinary events. We define when the new rule preserves stochastic dominance

    Two versions of the fundamental theorem of asset pricing

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    Let LL be a convex cone of real random variables on the probability space (Omega,mathcalA,P0)(Omega,mathcal{A},P_0). The existence of a probability PP on mathcalAmathcal{A} such that egin{equation*} Psim P_0,quad E_Pabs{X
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