demand and supply conditions. In three out of the four investigated cases, exchange rate posed as a main source of risk for … the commodity futures price. The significance and form of volatility spill-over effects of a bilateral exchange rate are … ; volatility ; forecasting …

In this study, we model realized volatility constructed from intraday high-frequency data. We explore the possibility … of confusing long memory and structural breaks in the realized volatility of the following spot exchange rates: EUR …' realized volatility. From the Bai – Perron test, we found structural breakpoints that match significant events in financial …

This paper examines and confirms the varying volatility of the relationship between cryptocurrency and currency markets … at different time periods, such as when the market encountered multiple risk events including the US-China trade war …, COVID-19, and the Russian-Ukraine war. We employ the Diagonal BEKK model and find that the co-volatility spillover effects …

robust with respect to a volatility measure and provide direct policy implications for portfolio composition and hedging. …We provide a comprehensive assessment of volatility connectedness between the currencies of Central European (CE … currencies before) and document domination of the negative volatility, especially during periods of economic distress. We further …

that divergence in monetary policy regimes affects forex volatility spillovers but that adding oil to a forex portfolio … shocks dominate forex volatility connectedness, positive shocks prevail when oil and forex markets are assessed jointly …

volatility have important implications for portfolio and risk management …This paper examines the contemporaneous spill-over effects among the CBOE implied volatility indices for stocks (VIX …) to decompose the contemporaneous relationship between these implied volatility indices into causal relationships. Our …

volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a … dataset which includes past values of the RV and additional predictors (composed by lagged returns and macroeconomic variables …