In this paper, we present a new method for computing the first-order approximation of the price of derivatives on futures in the context of multiscale stochastic volatility studied in Fouque et al. (2011). It provides an alternative method to the singular perturbation technique presented in...

We describe algorithm to find higher order approximations of stochastic rational expectations models near the deterministic steady state. Using matrix representation of function derivatives instead of tensor representation we obtain simple expressions of matrix equations determining higher order...

We develop canonical correlation analysis in the context of two-step monotone incomplete data drawn from Np+q(μ,Σ), a multivariate normal population with mean μ and covariance matrix Σ. Our data consist of n observations on each group and an additional N−n observations on only one group,...

This paper presents a canonical dual approach for finding either an optimal or approximate solution to the maximum cut problem (MAX CUT). We show that, by introducing a linear perturbation term to the objective function, the maximum cut problem is perturbed to have a dual problem which is a...