capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in … evidence for time-varying volatility in the yield factors. This is mostly true for the level and slope volatility revealing … also the highest persistence. It turns out that the inclusion of stochastic volatility improves the model's goodness …

limit of an asymmetric GARCH model risk-neutralized via Wang's transform. The connection with stochastic volatility limits …

behaviour of ‘other factor’ z(t). I show that their implementation of Stock and Watson’s (1998) Median Unbiased Estimation (MUE …

. However, accurate long-term volatility estimation is difficult because of a general lack of tradable, liquid medium- and long … simple historical volatility estimation and econometric, deterministic and stochastic volatility models; and (2) introducing … remains relevant for all long-term volatility estimation …

volatility estimation in terms of volatility jumps being examined and modeled for the international equity market, using such a … properties of jumps. These volatility-estimation and jump properties are also evident in jump modeling based on statistical and …Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six …

using the bootstrap. Forecast intervals for returns and volatility are constructed using the linear estimator (LE) for ARCH …

, different channels were used to identify the source of inflation persistence and volatility. This was estimated using Bayesian … Nigeria can be modelled by assuming constant volatility as the evidence shows that stochastic volatility (SV) is not a source … an evidence of instability not volatility in the variance of the trend inflation. Secondly, we found that the inclusion …