the Transformation of Sieve Function

In this paper, we will introduce the transformation of sieve function to improve sieve method. The sieve function can be transformed to similar sieve function and keep its value constant. However, the error terms of sieve function can be changed to smaller, even to be zero, such that the sieve function can be transformed to the calculable sieve function. Using this sieve method, Goldbach Conjecture and the Twin Prime Conjecture will be proved to be true.Comment: 7 page

Interplay of insurance and financial risks in a discrete-time model with strongly regular variation

Consider an insurance company exposed to a stochastic economic environment that contains two kinds of risk. The first kind is the insurance risk caused by traditional insurance claims, and the second kind is the financial risk resulting from investments. Its wealth process is described in a standard discrete-time model in which, during each period, the insurance risk is quantified as a real-valued random variable $X$ equal to the total amount of claims less premiums, and the financial risk as a positive random variable $Y$ equal to the reciprocal of the stochastic accumulation factor. This risk model builds an efficient platform for investigating the interplay of the two kinds of risk. We focus on the ruin probability and the tail probability of the aggregate risk amount. Assuming that every convex combination of the distributions of $X$ and $Y$ is of strongly regular variation, we derive some precise asymptotic formulas for these probabilities with both finite and infinite time horizons, all in the form of linear combinations of the tail probabilities of $X$ and $Y$. Our treatment is unified in the sense that no dominating relationship between $X$ and $Y$ is required.Comment: Published at http://dx.doi.org/10.3150/14-BEJ625 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm