The cryptocurrency market offers attractive but risky investment opportunities, characterized by rapid growth, extreme volatility, and uncertainty. Traditional risk management models, which rely on probabilistic assumptions and historical data, often fail to capture the market's unique dynamics...

The emergence of Covid-19 in late 2019 rapidly shattered the Asia-Pacific region (APR), a bastion of economic dynamism, and it became the epicenter of the global health crisis. This unprecedented pandemic not only triggered a public health catastrophe but also unleashed a financial storm,...

This paper presents a high-frequency structural VAR framework for identifying oil price shocks and examining their uncertainty transmission in the U.S. macroeconomy and financial markets. Leveraging the stylized features of financial data - specifically, volatility clustering effectively...

We analyze the predictive effect of monthly global, regional, and country-level financial uncertainties on daily gold market volatility using univariate and multivariate GARCH-MIDAS models, with the latter characterized by variable selection. Based on data over the period of July 1992 to May...

We explore the application of integrated nested Laplace approximations for the Bayesian estimation of stochastic volatility models characterized by long memory. The logarithmic variance persistence in these models is represented by a Fractional Gaussian Noise process, which we approximate as a...