estimation of the volatility in the market plays a key role in quantifying market risk exposure correctly. This paper presents … GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models … time-varying volatility. In this paper, the estimation of conditional volatility is applied to Value at Risk measurement …

estimation of the volatility in the market plays a key role in quantifying market risk exposure correctly. This paper presents … GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models … time-varying volatility. In this paper, the estimation of conditional volatility is applied to Value at Risk measurement …

estimation of the volatility in the market plays a key role in quantifying market risk exposure correctly. This paper presents … GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models … time-varying volatility. In this paper, the estimation of conditional volatility is applied to Value at Risk measurement …

Based on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of … discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized … realized measures in inflating the latent volatility persistence - the crucial parameter in pricing Standard and Poor's 500 …

stochastic volatility model, finding that the approach is efficient and effective. Applications to continuous time finance models …

display stochastic volatility …

volatility is a latent stochastic process, and we capture information about it using particle filter based "summary vectors … our pricing approximation against the full-state (observable volatility) result. Moreover, posterior inference, utilizing … market-observed American put option prices on the NYSE Arca Oil Index, is made on the volatility risk premium, which we …

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 …