Lending is associated with credit risk. Modelling the loss stochastically, the cost of credit risk is the expected loss. In credit business the probability that the debtor will default in payments within one year, often is the only reliable quantitative parameter. Modelling the time to default...

Lending is associated with credit risk. Modelling the loss stochastically, the cost of credit risk is the expected loss. In credit business the probability that the debtor will default in payments within one year, often is the only reliable quantitative parameter. Modelling the time to default...

We use point processes theory to describe the asymptotic distribution of all upper order statistics for observations collected at renewal times. As a corollary, we obtain limiting theorems for corresponding extremal processes.

During the past two decades, innovations protected by patents have played a key role in business strategies. This fact enhanced studies of the determinants of patents and the impact of patents on innovation and competitive advantage. Sustaining competitive advantages is as important as creating...

We describe a class of adaptive algorithms for approximating the global minimum of a function defined on a compact subset of Rd. The algorithms are adaptive versions of Monte Carlo search and use a memory of a fixed number of past observations. By choosing a large enough memory, the convergence...

We prove some heavy-traffic limit theorems for some nonstationary linear processes which encompass the fractionally differentiated random walk as well as some FARIMA processes, when the innovations are in the domain of attraction of a non-Gaussian stable distribution. The results are based on an...

A new version of dynamic time warping for samples of observed event times that are modeled as time-warped intensity processes is introduced. The approach is developed within a framework where for each experimental unit or subject in a sample, a random number of event times or random locations...

In many industries, managers face the problem of selling a given stock of items by a deadline. We investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm’s objective is to maximize expected revenues. Examples that fit this...

We study the first-order bifurcating autoregressive process Xt=ϕX⌊t/2⌋+ϵt with Weibull innovations. Using point process technique, we estimate the model parameter ϕ and the tail index α in the Weibull distribution and obtain the joint limit distribution of estimators.