In this paper, an evaluation method is suggested for selecting one of two competing models based on certain predictive ability ratings. The main focus is on the case of linear models that are not necessarily nested. In the context of such models, the test procedure is based on a sample statistic...

This paper presents a new methodology for evaluating the performance of a forecasting model. The evaluation-criterion utilizes a “credibility interval” centered at the model prediction. Given predicted and observed values, the length of the “credibility interval” is increased (or...

The paper proposes an approach to the two period inventory problem for items that have heterogeneous Poisson demands. A model is constructed whose appealing features reveals aspects of the nature of the optimal stocking problem that enable the manager to assess the degree to which demand is...

Most of the methods used in the ARCH literature for selecting the appropriate model are based on evaluating the ability of the models to describe the data. An alternative model selection approach is examined based on the evaluation of the predictability of the models on the basis of standardized...

The common way to measure the performance of a volatility prediction model is to assess its ability to predict future volatility. However, as volatility is unobservable, there is no natural metric for measuring the accuracy of any particular model. Noh et al. (1994) assessed the performance of a...

Autoregressive Conditional Heteroscedasticity (ARCH) models have successfully been applied in order to predict asset return volatility. Predicting volatility is of great importance in pricing financial derivatives, selecting portfolios, measuring and managing investment risk more accurately. In...

Degiannakis and Xekalaki (1999) compare the forecasting ability of Autoregressive Conditional Heteroscedastic (ARCH) models using the Correlated Gamma Ratio (CGR) distribution. According to the PEC model selection algorithm, the models with the lowest sum of squared standardized one-step-ahead...

In this report, two important issues that arise in the evaluation of the standardized prediction error criterion (SPEC) model selection method are investigated in the context of a simulated options market. The first refers to the question of whether the performance of the SPEC algorithm is...