Strong predictor-corrector euler methods for stochastic differential equations

This paper introduces a new class of numerical schemes for the pathwise approximation of solutions of stochastic differential equations (SDEs). The proposed family of strong predictor-corrector Euler methods are designed to handle scenario simulation of solutions of SDEs. It has the potential to overcome some of the numerical instabilities that are often experienced when using the explicit Euler method. This is of importance, for instance, in finance where martingale dynamics arise for solutions of SDEs with multiplicative diffusion coefficients. Numerical experiments demonstrate the improved asymptotic stability properties of the proposed symmetric predictor-corrector Euler methods. © 2008 World Scientific Publishing Company

Regolazione indipendente e politica energetica

Gli anni pi\uf9 recenti hanno visto nei diversi paesi dell'UE, accanto allo sviluppo e al consolidamento del modello di intervento pubblico basato sulla regolazione indipendente dei mercati, la ripresa degli interventi di politica industriale dei governi e dei parlamenti. Questo pone, tra l'altro, delicati problemi di disegno istituzionale e in particolare relazione tra gli organi preposti alla regolazione indipendente e gli organi politici. Il saggio analizza tali problemi con riferimento ai diversi settori delle public utilities e in particolare a quello dell'energia, proponendo un'ipotesi ricostruttiva delle normative dettate a livello UE e italiano volta a garantire adeguatamente l'indipendenza dei regolatori pur nel necessario raccordo tra gli stessi e gli apparati di governo

A Hardware Generator of Multi-Point Distributed Random Numbers for Monte Carlo Simulation

Monte Carlo simulation of weak approximation of stochastic differential equations constitutes an intensive computational task. In applications such as finance, for instance, to achieve "real time" execution, as often required, one needs highly efficient implementations of the multi-point distributed random number generator underlying the simulations. In this paper, a fast and flexible dedicated hardware solution on a field programmable gate array is presented. A comparative performance analysis between a software-only and the poposed hardware solution demonstrated that the hardware solution is bottleneck-free, retains the flexibility of the software solution and significantly increases the computational efficiency. Moreover, simulations in Applications wuch as economics insurance, physics, population dynamics, epidemiology, structural mechanics, checmistry and biotechnology can benefit from the obtained speedups