Abstract We consider the problem of controlling drift and diffusion rate endowment processes two firms such that joint survival probability is maximized. assume are continuous diffusions, driven by independent Brownian motions, aggregate a motion with constant rate. Our results reveal maximal depends only on risk-adjusted return can be implemented in each firm. Here understood as divided squared

This paper aims to estimate the joint default probability under the structuralform model with a random environment; namely stochastic correlation. By means of a singular perturbation method, we obtain an asymptotic expansion of a two-name joint default probability under a fast mean-reverting stochastic correlation model. The leading order term in the expansion is a joint default probability wit...

The joint probability between two binary strings of different lengths has been demonstrated as a suitable basis for a correlation attack on the shrinking generator when the decimation probability is 0.5. As an extension of this, further computer simulations have been conducted to determine whether the joint probability can be used as a basis of similar correlation attacks on irregularly clocked...

Considering a small image region and specifying a joint probability distribution which describes the likelihood of nding a speciic pattern in this image region, arithmetic coding can provide an optimum code that reaches the Shannon limit for the given probability distribution. Data compression is thus reduced to estimating joint probability distributions of patterns. This paper demonstrates how...

This paper is devoted to the construction of sets of joint probability measures for the case that the marginal sets of probability measures are generated by probability measures with uncertain parameters where the uncertainty of these parameters is modelled by random sets. Further we show how different conditions on the choice of the weights of the joint focal sets and on the probability measur...

[ The definition of conditional probabilities is based upon the existence of a joint A probability. However, a reconstruction of the joint probability from given conditional probabilities imposes certain constraints upon the latter, so that if several condit.iomd probabilities are chosen arbitrarily, the corresponding joint probability may not exist, Such an incompleteness in conditional probab...

One of the approaches to statistical machine translation is based on joint probability distributions over some source and target languages. In this work we propose to model the joint probability distribution by stochastic regular bi-languages. Specifically we introduce the stochastic k-testable in the strict sense bi-languages to represent the joint probability distribution of source and target...

W present a new method for constructing joint probability distributions of continuous random variables using isoprobability contours—sets of points with the same joint cumulative probability. This approach reduces the joint probability assessment into a one-dimensional cumulative probability assessment using a sequence of binary choices between various combinations of the variables of interest....