Forecast comparisons in unstable environments
提出两种统计检验方法，用于比较两个竞争模型在不稳定环境中的样本外预测表现，并应用于汇率决定模型与随机游走的预测性能比较。
Abstract We propose new methods for comparing the out‐of‐sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a measure of the relative local forecasting performance for the two models, and to investigate its stability over time by means of statistical tests. We propose two tests (the Fluctuation test and the One‐Time Reversal test) that analyze the evolution of the models' relative performance over historical samples. In contrast to previous approaches to forecast comparison, which are based on measures of global performance, we focus on the entire time path of the models' relative performance, which may contain useful information that is lost when looking for the model that forecasts best on average. We apply our tests to the analysis of the time variation in the out‐of‐sample forecasting performance of monetary models of exchange rate determination relative to the random walk. Copyright © 2010 John Wiley & Sons, Ltd.