Michael P. Clements
;
Nick Taylor
You're currently viewing an old version of this dataset. To see the current version, click here.

evaluating interval forecasts of high-frequency financial data (replication data)

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.

Data and Resources

This dataset has no data

Suggested Citation

Clements, Michael P.; Taylor, Nick (2003): Evaluating interval forecasts of high-frequency financial data (replication data). Version: 1. Journal of Applied Econometrics. Dataset. https://journaldata.zbw.eu/dataset/evaluating-interval-forecasts-of-highfrequency-financial-data?activity_id=e3c38293-c928-4f1a-9e9d-8fd9aa613ebd