Autoregressive Conditionally Heteroskedastic (fGARCH) model were applied to study the volatility of the Autoregressive Fractionally …

regime in the late 1990s. In particular, we ask whether these interventions have dumped excess exchange rate volatility and … reduced its probability of being in a high volatility state. To do so, we rely on a high-frequency GARCH(1,1) volatility model … that FX interventions in Chile tend to occur during high exchange rate volatility periods, which correlate with domestic …

Industrial Metals volatility affects G7 stock markets. To this end, the BEKK-GARCH model is used. The sample period spans from 3 … January 2018 to 17 September 2024. The results show that lagged shocks and volatility significantly and positively influence … the current conditional volatility of commodity and stock returns during all periods. In fact, past shocks inversely …

This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets … (Brent oil and WTI oil) for the period 2011-2021. The main objective is to make step ahead volatility predictions for the … important for market participants, implying predictability. The paper estimates multifactor stochastic volatility models for …

This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and … bulk distribution components. This implies that the combination of a stochastic econometric model with extreme value theory …

Egypt from 2016 to 2030. Design/methodology/approach: The study applied generalized autoregressive conditional … evaluate the volatility of price of green beans, tomatoes, onions, oranges, grapes and strawberries, respectively. The results … of food price volatility in developing countries is essential, since a significant share of household budgets is spent on …