Intraday volatility connectedness on the forex market: the role of uncertainty

Abstract

We quantify intraday volatility connectedness between major currencies and assess how it is related to various uncertainty measures. For that purpose, we integrate the well-known Diebold-Yilmaz spillover methodology with a TVP VAR model estimated on a unique, vast dataset of over 460K five-minute quotations from Jan. 1, 2018 to Feb. 29, 2024 for five most heavily traded currency pairs of USD against EUR, JPY, AUD, CAD and GBP. In contrast to existing studies, which either use data of lower sampling frequency or employ high-frequency data only to calculate daily realized moments, we use intraday data directly for model estimation. This enables us to show that volatility connectedness at intraday frequency presents a complementary picture to estimates based on daily data. Within the quantile regression framework we demonstrate that the level of total intraday connectedness is affected by the level of uncertainty proxied by the implied volatility at stock markets. Our study highlights the importance of using high-frequency data in order to better understand forex market dynamics.