A simple, empirical-based approach to decompose Realized Variance (RV) is proposed, with supportive theoretical argument and empirical evidence. Under the proposed framework, RV is interpreted as a product of the intensity and variance of relevant price changes. Holding the variance aspect...

In econometrics, long memory models for variance modeling like FIGARCH or FIAPARCH are characterized by a Fractional Differencing term. In order to estimate and apply these models, the infinite MacLaurin expansion of the differencing term has to be truncated at a certain level. We transfer the...

This paper introduces a VAR with stochastic volatility in mean where the residuals of the volatility equations and the observation equations are allowed to be correlated. This implies that exogeneity of shocks to volatility is not assumed apriori and structural shocks can be identified ex-post...

This paper extends the procedure developed by Jurado et al. (2015) to allow the estimation of measures of uncertainty that can be attributed to specific structural shocks. This enables researchers to investigate the "origin" of a change in overall macroeconomic uncertainty. To demonstrate the...

Despite the growing interest in realized stochastic volatility models, their estimation techniques, such as simulated maximum likelihood (SML), are computationally intensive. Based on the realized volatility equation, this study demonstrates that, in a finite sample, the quasi-maximum likelihood...