accurate and low cost computational techniques which would permit extensive use of simulation methodology. Large samples are … simulation results. This paper investigates the tradeoffs available between computational accuracy and cost in simulation …

A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows …-known algorithm of Glover, and checked for non-negativity. The first non-negative point is an optimal solution of (GP). Advantages and … disadvantages of the algorithm are discussed; in particular, the implementation of the algorithm (which can be easily extended so as …

objective function for the algorithm designer and a model of their information sets and interaction. We build such a model that … allows the training data to exhibit a wide range of "biases." Prevailing wisdom is that biased data change how the algorithm … is trained and whether an algorithm should be used at all. In contrast, we find two striking irrelevance results. First …

algorithm in terms of model complexity or the number of predictors to accommodate. Each firm then appoints a data analyst that … uses the chosen algorithm to estimate demand for multiple consumer segments, based on which, it devises a targeting policy …

structure is relevant in many applications. We develop the theory underlying optimal menus of non-linear schedules and prove … monopolistic utility company increasing profits by offering a menu of price plans. The second is a simulation based on U …

We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection … approaches: we use simulation to approximate the ergodic measure of the solution, we construct a fixed grid covering the support … support of the ergodic measure roughly uniformly. The proposed algorithm is tractable in problems with high dimensionality …

This paper surveys the field of asset pricing. The emphasis is on the interplay between theory and empirical work, and …