We propose a flexible lattice model to evaluate the fair value of insurance contracts embedding both financial and actuarial risk factors. Flexibility relies on the ability of the model to manage different specifications of the correlated processes governing interest rate, mortality, and fund dynamics, thus allowing the insurer to make the most appropriate choices. The model is also able to handle additional guarantees like a surrender opportunity for which explicit formulae are not available being it similar to an American derivative. The model discretizes mortality and interest rate dynamics through two different binomial lattices and then combines them into a bivariate tree characterized by the presence of four branches for each node. The probability of each branch is defined to replicate the correlation affecting the two processes. The bivariate model is useful to compute the value of survival zero coupon bond. When adding another source of risk, such as the fund dynamics for evaluating fund-linked insurance products, we model it through a bivariate tree that captures the influence of the interest rate on its drift term. Then, the mortality risk is embedded by defining a trivariate tree presenting eight branches emanating from each node with probabilities defined in order to capture the correlations of the processes. Extensive numerical experiments assess the model accuracy by considering some stylized policies, but the model application is not limited to them being it able to manage different contract specifications.

We have developed a chemical kinetics simulation that can be used as both an educationaland research tool. The simulator is designed as an accessible, open-source project thatcan be run on a laptop with a student-friendly interface. The application can potentiallybe scaled to run in parallel for large simulations. The simulation has been successfullyused in a classroom setting for teaching basic electrochemical properties. We have shownthat this can be used for simulating fundamental molecular and chemical processes and evensimplified models of predator–prey interactions. By giving the simulated entities spatialextent in the lattice, the particles do not interpenetrate, and clusters of particles canspatially exclude one another. Our simulation demonstrates that spatial inhomogeneityleads to different results than those that are obtained by using standard ordinarydifferential equation models, as previously reported.

The superintegrable chiral Potts model has many resemblances to the Ising model, so it is natural to look for algebraic properties similar to those found for the Ising model by Onsager, Kaufman and Yang. The spontaneous magnetization ℳr can be written in terms of a sum over the elements of a matrix Sr. The author conjectured the form of the elements, and this conjecture has been verified by Iorgov et al. The author also conjectured in 2008 that this sum could be expressed as a determinant, and has recently evaluated the determinant to obtain the known result for ℳr. Here we prove that the sum and the determinant are indeed identical expressions. Since the order parameters of the superintegrable chiral Potts model are also those of the more general solvable chiral Potts model, this completes the algebraic calculation of ℳr for the general model.

It has been known for some time that the Boltzmann weights of the chiral Potts model can be parametrised in terms of hyperelliptic functions. but as yet no such parametrisation has been applied to the partition and correlation functions. Here we show that for N = 3 the function S(tp) that occurs in the recent calculation of the order parameters can he expressed quite simply in terms of such a parametrisation.

Computer simulations of protein models on lattices have been widely used as an aid in the study of protein folding process. Following the suggestion of Raghunathan and Jernigan (1997, Protein Sci 6:2072–2083) that the cubo-octahedral lattice can allow a more realistic representation of proteins than other lattices, we propose here the use of a new set of internal coordinates θ for the description of a protein model on this lattice. An easy procedure for the conversion of the θ coordinates to the Cartesian coordinates is also described. When the Contact Interaction approach, already proposed by us for simulations on square or cubic lattices, was applied to the cubo-octahedral lattice, the system obeyed the correct thermodynamics derived from the definition of energy. Thus, lattice simulations of protein models, in which secondary structure elements such as α-helices or β-strands can be easily identifiable, can be performed.

In previous papers (1976), (1977a), (1979) limit theorems were obtained for the classical Ising model, and these provided the basis for asymptotic inference. The present paper extends these results to more general Ising models.

In two and more dimensions, likelihood inference for the thermodynamic parameters (i.e. the interaction energies) is effectively impossible. The problem is that the error in locating critical and/or confidence regions is as large as their diameters. To remedy this requires more accurate characterizations of the partition functions, but these seem unlikely to be forthcoming. Besag's coding estimators for these parameters are inverse hyperbolic tangents of the roots of simultaneous polynomial equations and hence avoid such location errors. However, little is yet known about their sampling characteristics. Finally, likelihood inference for lattice averages (an alternative parametrization) is straightforward from the limit theorems.