Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent … countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate … particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic …

We develop a dynamic factor model with time-varying parameters and stochastic volatility, estimate it with several … findings, the estimates suggest that global uncertainty plays a primary role in explaining the volatility of inflation …

We build a dynamic factor model with time-varying parameters and stochastic volatility and use it to decompose the … common global uncertainty plays a primary role in explaining the volatility of inflation, interest rates and stock prices …, although to a varying extent over time. Region-specific uncertainty drives most of the exchange rate volatility for all Euro …

-varying parameter models that incorporate both stochastic volatility and a Heckman-type two-step estimation procedure that deals with …

volatility to estimate the changing spillover of global oil shocks into the Maltese economy during the period that goes from …

dynamic factor and a vector autoregressive model and includes stochastic volatility, denoted by FAVAR-SV. Next, a Bayesian … momentum strategy. The estimation of this modeling and strategy approach can be done using an extended and modified version of … risk features like volatility and largest loss, which indicates that complete densities provide useful information for risk. …

This paper studies the continuous-time dynamics of VIX with stochastic volatility and jumps in VIX and volatility …. Built on the general parametric affine model with stochastic volatility and jumps in the logarithm of VIX, we derive a … linear relationship between the stochastic volatility factor and the VVIX index. We detect the existence of a co-jump of VIX …

Given discrete time observations over a fixed time interval, we study a nonparametric Bayesian approach to estimation … of the volatility coefficient of a stochastic differential equation. We postulate a histogram-type prior on the … volatility with piecewise constant realisations on bins forming a partition of the time interval. The values on the bins are …

Non-parametric approach to financial time series jump estimation, using the L-Estimator, is compared with the … parametric approach utilizing a Stochastic-Volatility-Jump-Diffusion (SVJD) model, estimated with MCMC and extended with Particle …-sample estimation does the MCMC based parametric approach significantly outperform the L-Estimator. In the case of the out …