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Related papers: A note on large deviations in life insurance

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We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in…

Machine Learning · Computer Science 2013-11-12 Spencer Greenberg , Mehryar Mohri

Dependence among multiple lifetimes is a key factor for pricing and evaluating the risk of joint life insurance products. The dependence structure can be exposed to model uncertainty when available data and information are limited. We…

Risk Management · Quantitative Finance 2026-03-30 Takaaki Koike

We consider the general branching random walk under minimal assumptions, which in particular guarantee that the empirical particle distribution admits an almost sure central limit theorem. For such a process, we study the large time decay…

Probability · Mathematics 2017-12-07 Oren Louidor , Eliad Tsairi

The investor is interested in the expected return and he is also concerned about the risk and the uncertainty assumed by the investment. One of the most popular concepts used to measure the risk and the uncertainty is the variance and/or…

Statistical Finance · Quantitative Finance 2008-12-02 Andreia Dionisio , Rui Menezes , Diana A. Mendes

Modern risk modelling approaches deal with vectors of multiple components. The components could be, for example, returns of financial instruments or losses within an insurance portfolio concerning different lines of business. One of the…

Probability · Mathematics 2021-05-12 Miriam Hägele , Jaakko Lehtomaa

This paper studies an optimal insurance contracting problem in which the preferences of the decision maker given by the sum of the expected loss and a convex, increasing function of a deviation measure. As for the deviation measure, our…

Risk Management · Quantitative Finance 2023-12-05 Tim J. Boonen , Xia Han

We study the consistency of sample mean-variance portfolios of arbitrarily high dimension that are based on Bayesian or shrinkage estimation of the input parameters as well as weighted sampling. In an asymptotic setting where the number of…

Portfolio Management · Quantitative Finance 2015-05-30 Francisco Rubio , Xavier Mestre , Daniel P. Palomar

There is sustained and widespread interest in understanding the limit, if any, to the human lifespan. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social…

Applications · Statistics 2021-04-19 Léo R. Belzile , Anthony C. Davison , Jutta Gampe , Holger Rootzén , Dmitrii Zholud

For a risk vector $V$, whose components are shared among agents by some random mechanism, we obtain asymptotic lower and upper bounds for the individual agents' exposure risk and the aggregated risk in the market. Risk is measured by…

Risk Management · Quantitative Finance 2016-04-12 Oliver Kley , Claudia Kluppelberg

We consider a family of positive operator valued measures associated with representations of compact connected Lie groups. For many independent copies of a single state and a tensor power representation we show that the observed probability…

Mathematical Physics · Physics 2024-09-04 Alonso Botero , Matthias Christandl , Péter Vrana

We prove large deviation principles for two versions of fractional Poisson processes. Firstly we consider the main version which is a renewal process; we also present large deviation estimates for the ruin probabilities of an insurance…

Probability · Mathematics 2016-11-26 Luisa Beghin , Claudio Macci

We give exponential upper bounds for $P(S \le k)$, in particular $P(S=0)$, where $S$ is a sum of indicator random variables that are positively associated. These bounds allow, in particular, a comparison with the independent case. We give…

Probability · Mathematics 2014-12-22 Matthias Löwe , Franck Vermet

The purpose of the present paper is to establish moderate deviation principles for a rather general class of random variables fulfilling certain bounds of the cumulants. We apply a celebrated lemma of the theory of large deviations…

Probability · Mathematics 2012-09-28 Hanna Doering , Peter Eichelsbacher

We determine the optimal amount of life insurance for a household of two wage earners. We consider the simple case of exponential utility, thereby removing wealth as a factor in buying life insurance, while retaining the relationship among…

Portfolio Management · Quantitative Finance 2013-06-28 Erhan Bayraktar , Virginia R. Young

We establish a large deviation theorem for the empirical spectral distribution of random covariance matrices whose entries are independent random variables with mean 0, variance 1 and having controlled forth moments. Some new properties of…

Complex Variables · Mathematics 2017-07-25 Tien-Cuong Dinh , Duc-Viet Vu

This note presents a kind of the strong law of large numbers for an insurance risk caused by a single catastrophic event rather than by an accumulation of independent and identically distributed risks. We derive this result by a large…

Risk Management · Quantitative Finance 2016-01-14 Yumiharu Nakano

Localized sufficient conditions for the large deviation principle of the given stochastic differential equations will be presented for stochastic differential equations with non-Lipschitzian and time-inhomogeneous coefficients, which is…

Probability · Mathematics 2014-04-08 Yunjiao Hu , Guangqiang Lan

We establish sharp large deviation asymptotics for the maximum order statistic of independent and identically distributed heavy-tailed random variables, valid for all Borel subsets of the right tail. This result yields exact decay rates for…

Probability · Mathematics 2026-01-09 José M. Zapata

Using martingale methods, we obtain some upper bounds for large and moderate deviations of products of independent and identically distributed elements of GL d (R). We investigate all the possible moment conditions, from super-exponential…

Probability · Mathematics 2016-10-25 Christophe Cuny , Jérôme Dedecker , Florence Merlevède

A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution, is presented. No knowledge beyond the support of the…

Information Theory · Computer Science 2007-07-13 Joseph DeStefano , Erik Learned-Miller