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

Georgios Chortareas; Ying Jiang; John C. Nankervis

doi:10.1016/j.ijforecast.2010.07.003

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

Georgios Chortareas, Ying Jiang, John C. Nankervis

Department of Finance, Accounting and Economics

Research output: Journal Publication › Article › peer-review

65 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 language	English
Pages (from-to)	1089-1107
Number of pages	19
Journal	International Journal of Forecasting
Volume	27
Issue number	4
DOIs	https://doi.org/10.1016/j.ijforecast.2010.07.003
Publication status	Published - 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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10.1016/j.ijforecast.2010.07.003

Cite this

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title = "Forecasting exchange rate volatility using high-frequency data: Is the euro different?",

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.",

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AU - Jiang, Ying

AU - Nankervis, John C.

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AB - 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.

KW - Euro exchange rates

KW - Forecast evaluation

KW - GARCH model

KW - High-frequency data

KW - Long memory time series

KW - Volatility forecasting

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VL - 27

SP - 1089

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JO - International Journal of Forecasting

JF - International Journal of Forecasting

IS - 4

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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