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Bibliographic Details
Main Authors: Kearney, Fearghal, Shang, Han Lin, Zhao, Yuqian
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2311.18477
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author Kearney, Fearghal
Shang, Han Lin
Zhao, Yuqian
author_facet Kearney, Fearghal
Shang, Han Lin
Zhao, Yuqian
contents This paper seeks to forecast intraday volatility curves for major foreign exchange (FX) currencies using functional GARCH models. Intraday return curves are observed at a daily frequency, yet preserve the full high-frequency trading structure, enabling volatility analysis at the intraday level. We demonstrate that the USD/EUR, USD/GBP, and USD/JPY intraday return curves exhibit strong cross-dependence, while individually they are serially uncorrelated but display long-range conditional heteroskedasticity. Embedding cross-currency dependence via multi-level functional principal component analysis and adding intraday bid-ask spread curves as exogenous drivers significantly improves intraday and day-ahead volatility forecasts relative to functional and realised-volatility baselines. The precise volatility forecasts motivate the construction of intraday Value-at-Risk (VaR). An intraday risk management application highlights that predicted intraday VaR curves can help mitigate dramatic losses in intraday trading strategies, showcasing their practical economic benefits in FX markets.
format Preprint
id arxiv_https___arxiv_org_abs_2311_18477
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Intraday FX Volatility-Curve Forecasting with Functional GARCH Approaches
Kearney, Fearghal
Shang, Han Lin
Zhao, Yuqian
Methodology
Applications
62R10
This paper seeks to forecast intraday volatility curves for major foreign exchange (FX) currencies using functional GARCH models. Intraday return curves are observed at a daily frequency, yet preserve the full high-frequency trading structure, enabling volatility analysis at the intraday level. We demonstrate that the USD/EUR, USD/GBP, and USD/JPY intraday return curves exhibit strong cross-dependence, while individually they are serially uncorrelated but display long-range conditional heteroskedasticity. Embedding cross-currency dependence via multi-level functional principal component analysis and adding intraday bid-ask spread curves as exogenous drivers significantly improves intraday and day-ahead volatility forecasts relative to functional and realised-volatility baselines. The precise volatility forecasts motivate the construction of intraday Value-at-Risk (VaR). An intraday risk management application highlights that predicted intraday VaR curves can help mitigate dramatic losses in intraday trading strategies, showcasing their practical economic benefits in FX markets.
title Intraday FX Volatility-Curve Forecasting with Functional GARCH Approaches
topic Methodology
Applications
62R10
url https://arxiv.org/abs/2311.18477