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W U Chuanj - One of the best experts on this subject based on the ideXlab platform.

Sheng Fan - One of the best experts on this subject based on the ideXlab platform.

  • A Stochastic String with a Compound Poisson Process
    Abstract and Applied Analysis, 2013
    Co-Authors: Sheng Fan
    Abstract:

    We investigate a Compound Poisson infinite factor diffusion model which describes the relationship between the infinite-dimension random risk resource and the corresponding stochastic Process. We derive the no-arbitrage condition on the drift of instantaneous forward rates in the Compound model and study the impact of random jump on the price of the zero-coupon bond.

Mohamed Abdelhameed - One of the best experts on this subject based on the ideXlab platform.

Peter Spreij - One of the best experts on this subject based on the ideXlab platform.

  • a kernel type nonparametric density estimator for deCompounding
    Bernoulli, 2007
    Co-Authors: A J Van Es, Shota Gugushvili, Peter Spreij
    Abstract:

    Abstract Given a sample from a discretely observed Compound Poisson Process, we consider estimation of the density of the jump sizes. We propose a kernel type nonparametric density estimator and study its asymptotic properties. An order bound for the bias and an asymptotic expansion of the variance of the estimator are given. Pointwise weak consistency and asymptotic normality are established. The results show that, asymptotically, the estimator behaves very much like an ordinary kernel estimator. Keywords: asymptotic normality; consistency; deCompounding; kernel estimation Full-text: Access by subscription (subscriber: Univ Biblio SZ (UVA))

  • a kernel type nonparametric density estimator for deCompounding
    arXiv: Statistics Theory, 2005
    Co-Authors: Bert Van Es, Shota Gugushvili, Peter Spreij
    Abstract:

    Given a sample from a discretely observed Compound Poisson Process, we consider estimation of the density of the jump sizes. We propose a kernel type nonparametric density estimator and study its asymptotic properties. An order bound for the bias and an asymptotic expansion of the variance of the estimator are given. Pointwise weak consistency and asymptotic normality are established. The results show that, asymptotically, the estimator behaves very much like an ordinary kernel estimator.

Elias S W Shiu - One of the best experts on this subject based on the ideXlab platform.

  • on optimal dividend strategies in the Compound Poisson model
    The North American Actuarial Journal, 2006
    Co-Authors: Hans U. Gerber, Elias S W Shiu
    Abstract:

    The optimal dividend problem goes back to a paper that Bruno De Finetti presented to the International Congress of Actuaries in New York (1957). For a stock company that pays dividends to its shareholders, what is the strategy that maximizes the expectation of the discounted dividends (until possible ruin)? Jeanblanc-Picque and Shiryaev (1995) and Asmussen and Taksar (1997) solved the problem in the Brownian motion model, when a ceiling is imposed for the dividend rate. Here we study the problem with the Brownian motion generalized to a Compound Poisson Process. In particular, we derive a rule for deciding between plowback and dividend payout, which is a key issue in corporate finance.