subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of … the observed time series. We develop a simulated maximum likelihood estimation method based on importance sampling and … applied to quarterly and monthly US inflation in an empirical study. We find that the persistence of quarterly inflation has …

terms of returns and volatility, received much less attention. With the use of an econometric methodology, the paper aims to …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …

allows for a more flexible weighting of financial squared-returns for the filtering of volatility. The parameter for the …-return replaced by the product of the volatility innovation and its lagged value. This local estimate of the first order … autocorrelation of volatility innovations acts as an indicator of the importance of the squared-return for volatility updating. When …

This note discusses some aspects of the paper by Hu and Tsay (2014), "Principal Volatility Component Analysis". The key …

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 …

dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …

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 …