We propose an improved binomial lattice approach for valuing complex option problems whose payoff depends on multiple state variables following correlated geometric Brownian processes. The proposed approach relies on two main ideas: a specific change of time scale as in the log-trasformed binomial approach by Trigeorgis (1991), and a change of basis of the asset span, to trasform them into unco...

Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informati...

In this paper we study different algorithms for reflected backward stochastic differential equations (BSDE in short) with two continuous barriers based on binomial tree framework. We introduce numerical algorithms by penalization method and reflected method respectively. In the end simulation results are also presented.

Assuming a zero order process, the beta-binomial distribution model is often used to describe consumers' brand switching behavior. A variety of methods have been used to estimate the parameters of the beta-binomial distribution, each of which assumes fixed number of purchase occasions across households . Consumer panel data, however, are typically available for a fixed duration of time (say, a ...

This article discusses convergence problems when calculating Vega (option sensitivity to volatility) that arise from discretization errors embedded in the lattice approach. Four alternative improvements to the traditional binomial method are discussed and investigated for performance. We also propose a new Modified Binomial (MB) Method to calculate Vegas. Numerical results show that although th...

SUMMARY A marginal model for the analysis of binomial data involving one or two random factors is presented. Two variance-covariance models are derived based on the multiplicative error formulation. The parameters of mean and variance components are estimated using the quasi-likelihood and method of moments, respectively. An application of the model is illustrated by an analysis of multivariate...

In this paper we investigate the problem of predicting the closed set identification performance of biometric matchers in large-scale applications given their corresponding performances in small-scale applications. We identify two major effects responsible for the prediction errors in previously proposed methods: the binomial approximation effect and the score mixing effect. We propose to use a...