the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …

One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH …) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative … subsequent shocks to volatility. However, there are as yet no statistical properties available for the (quasi-) maximum …

Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …

Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …

. They are applicable to the complete class of observation driven models and are valid for a wide range of estimation … that is embedded in the time-varying parameter path. We illustrate our findings in a volatility analysis for monthly …

In the class of univariate conditional volatility models, the three most popular are the generalized autoregressive … mathematical regularity properties, including invertibility, to determine the likelihood function for estimation, and the … effects on conditional volatility of positive and negative effects of equal magnitude, and possibly also leverage, which is …

-dimensional vector of financial returns. We identify common and idiosyncratic conditional volatility factors. The econometric framework … dimensionality. The relatively simple structure of the model leads to simple computations for the estimation of parameters and signal … conditional volatility factor are investigated by means of a Monte Carlo study. Finally, we illustrate our approach with two …

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the … microstructure noise has an adverse effect on both spot variance estimation and jump detection. In our approach we can analyze high …