We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...

Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Relevance Vector Machines (RVM) were used to predict daily returns for an FX carry basket. Market observable exogenous variables known to have a relationship with the basket along with lags of the basket's return were used as...

We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...

Economists typically make simplifying assumptions to make the solution and estimation of their highly complex models feasible. These simplifications include approximating the true nonlinear dynamics of the model, disregarding aggregate uncertainty or assuming that all agents are identical. While...

This paper discusses the need for a missing value technique to fill in gaps in time series representing foreign exchange (FX) prices and assist in the observation of potential arbitrage opportunities. It highlights the requirement for prediction methods to establish the persistence of these...

This paper presents a study of Artificial Neural Network (ANN) and Bayesian Network (BN) for use in stock index prediction. The data from Nigerian Stock Exchange (NSE) market are applied as a case study. Based on the rescaled range analysis, the neural network was used to capture the...

We propose a new nonlinear classification method based on a Bayesian "sum-of-trees" model, the Bayesian Additive Classification Tree (BACT), which extends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric additive...

I use a model of human causal learning, Causal Support (Tenenbaum & Griffiths, 2001), to derive a meaningful measure of Cognitive Distance – the degree to which two people differ in their opinions about the workings of the world. Next, I amend this measure to quantify the notion of Cognitive...

In this paper, we investigate the relationship between foreign aid and growth using recently developed sample splitting methods that allow us to uncover evidence for the existence of heterogeneity and nonlinearity simultaneously. We also implement a new methodology that allows us to deal with...

Economists typically make simplifying assumptions to make the solution and estimation of their highly complex models feasible. These simplifications include approximating the true nonlinear dynamics of the model, disregarding aggregate uncertainty or assuming that all agents are identical. While...