This paper seeks to analyse and predict conditional intraday volatility curves in FX markets using functional Generalised AutoRegressive Conditional Heteroscedasticity (GARCH) models. Remarkably, taking account of cross-dependency dynamics between the major currencies significantly improves intraday conditional volatility forecasting. Additionally, incorporating intraday bid-ask spread using a functional GARCH-X model further enhances predictability. 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.

翻译：本文旨在利用函数广义自回归条件异方差模型分析与预测外汇市场的日内条件波动率曲线。研究发现，考虑主要货币间的交叉依赖动态能显著提升日内条件波动率预测精度。此外，通过函数GARCH-X模型纳入日内买卖价差可进一步增强预测能力。精确的波动率预测为构建日内风险价值提供了基础。一项日内风险管理应用表明，预测的日内风险价值曲线有助于降低日内交易策略中的剧烈损失，体现了其实践经济价值。