Forecasting exchange rate volatility using high-frequency data: Is the euro different?

Georgios Chortareas, Ying Jiang, John C. Nankervis

Research output: Journal PublicationArticlepeer-review

54 Citations (Scopus)

Abstract

We assess the performances of alternative procedures for forecasting the daily volatility of the euro's bilateral exchange rates using 15 min data. We use realized volatility and traditional time series volatility models. Our results indicate that using high-frequency data and considering their long memory dimension enhances the performance of volatility forecasts significantly. We find that the intraday FIGARCH model and the ARFIMA model outperform other traditional models for all exchange rate series.

Original languageEnglish
Pages (from-to)1089-1107
Number of pages19
JournalInternational Journal of Forecasting
Volume27
Issue number4
DOIs
Publication statusPublished - Oct 2011

Keywords

  • Euro exchange rates
  • Forecast evaluation
  • GARCH model
  • High-frequency data
  • Long memory time series
  • Volatility forecasting

ASJC Scopus subject areas

  • Business and International Management

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