This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial inter-bank network. We prove that this problem is, generically, NP-hard....

Bernardo and Ledoit (2000) develop a very appealing framework to compute pricing bounds based on the so-called gain-loss ratio. Their method has many advantages and very interesting properties and so far one important drawback: the complexity of the numerical computation of the pricing bounds....

Telecommunication networks are characterised by a complex group of intermediaries and each one of them faces two types of operational costs: transmission costs and delivery cost. This scheme allows the operator to evaluate the market structure and to perform the telecommunication service. The...

This paper proposes a novel method of global optimization based on cuckoo-host co-evaluation. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 96 benchmark functions (of which the results of 30 relatively harder problems have been reported). The proposed...

In this contribution we propose a dynamic tracking error problem and we consider the problem of monitoring at discrete point the shortfall of the portfolio below a set of given reference levels of wealth. We formulate and solve the resulting dynamic optimization problem using stochastic...

We present a new way to solve generalized Nash equilibrium problems. We assume the feasible set to be compact. Furthermore all functions are assumed to be polynomials. However we do not need any convexity assumptions on either the utility functions or the action sets. The key idea is to use...

In this contribution we propose an approach to solve a multistage stochastic programming problem which allows us to obtain a time and nodal decomposition of the original problem. This double decomposition is achieved applying a discrete time optimal control formulation to the original stochastic...

We propose a new class of knapsack problems by assiuning that the sizes of the items to be put into a knapsack are known to be elements 0f a given subset S of the positive integers Z'^. The set S is treated as a parameter. We show that the family of knapsack problems obtained by varying the...

Economists who want to numerically approximate an elaborate dynamic stochastic programming problem (DSPP), either for structural estimation or policy evaluation purposes, are often confined by the curse of dimensionality: richer models with various state and control variables cannot be solved on...