generally, to observation-driven models, which include well-known models for conditional volatility. To overcome the problem of … Monte Carlo study and an empirical study concerning the measurement of conditional volatility from financial returns data. …

-Leibler divergence in empirically relevant settings. We illustrate the theory with an application to time-varying volatility models. We …

-dimensional vector of financial returns. We identify common and idiosyncratic conditional volatility factors. The econometric framework … conditional volatility factor are investigated by means of a Monte Carlo study. Finally, we illustrate our approach with two …

We study optimality properties in finite samples for time-varying volatility models driven by the score of the …-driven volatility models have optimality properties when they matter most. Score-driven models perform best when the data is fat …

This paper considers a stochastic volatility model featuring an asymmetric stable error distribution and a novel way of … filtering of time-varying volatility, and volatility forecasting. Specifically, we make use of the indirect inference method to … estimate the static parameters, and the extremum Monte Carlo method to extract latent volatility. Both methods can be easily …

that is embedded in the time-varying parameter path. We illustrate our findings in a volatility analysis for monthly …