Evaluating interval forecasts of high‐frequency financial data
分析了评估金融数据区间预测有效性的多种方法，并用日内FTSE100指数期货收益数据说明。研究发现，在存在周期性异方差时，传统马尔可夫链方法不适用，而回归检验和修正的独立性检验更合适。
Abstract A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen ( 1998 ), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression‐based test, and a modified version of Christoffersen's Markov chain test for independence, and analyse their properties when the financial time series exhibit periodic volatility. These approaches lead to different conclusions when interval forecasts of FTSE100 index futures returns generated by various GARCH(1,1) and periodic GARCH(1,1) models are evaluated. Copyright © 2003 John Wiley & Sons, Ltd.