Many common option pricing problems require numerical solution techniques. One standard tool is to solve a finite difference approximation to the instrument's fundamental partial differential equation (PDE), with appropriate boundary conditions. The approximation will converge to the true...

Many stochastic differential equations (SDEs) do not have readily available closed-form expressions for their transitional probability density functions (PDFs). As a result, a large number of competing estimation approaches have been proposed in order to obtain maximum-likelihood estimates of...

Compartmental models of dendrites are the most widely used tool for investigating their electrical behaviour. Traditional models assign a single potential to a compartment. This potential is associated with the membrane potential at the centre of the segment represented by the compartment. All...

The aim of this paper is to discuss the use of Bayesian methods in cost-effectiveness analysis (CEA) and the common ground between Bayesian and traditional frequentist approaches. A further aim is to explore the use of the net benefit statistic and its advantages over the incremental...

We propose a class of models in which the η-problem of supersymmetric hybrid inflation is resolved using a Heisenberg symmetry, where the associated modulus field is stabilized and made heavy with the help of the large vacuum energy during inflation without any fine-tuning. The proposed class...

The parameters of a finite mixture model cannot be consistently estimated when the data come from an embedded distribution with fewer components than that being fitted, because the distribution is represented by a subset in the parameter space, and not by a single point. Feng & McCulloch (1996)...

Empirical study of 25 years US Treasury bills data shows that even when the spot interest rate remains fixed, its volatility varies significantly over time. Constant-coefficient models cannot capture these changes as they give rise to time-homogeneous distributions. Maximum likelihood fitting of...

In most classical scheduling models, it is assumed that a job is dispatched to a customer immediately after its processing completes. In many practical situations, however, a set of delivery dates may be fixed before any jobs are processed. This is particularly relevant where delivery is an...

This paper investigates the optimal bidding strategy (supply function) for a generator offering power into a wholesale electricity market. The model has three characteristics: the uncertainties facing the generator are described by a single probability function, namely the market distribution...

In electricity wholesale markets, generators often sign long term contracts with purchasers of power in order to hedge risks. In this paper, we consider a market where demand is uncertain, but can be represented as a function of price together with a random shock. Each generator offers a smooth...