The volatility of aggregate economic activity in the United States decreased markedly in the mid eighties. The decrease … document a negative relation between the volatility of GDP and some of its components and one such financial development: the …

breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng's algorithm … breaks in volatility, while Cheng's technique works well only when a single break occurs. …

) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This … distribution is very limited. -- Markov-switching multifractal ; scaling ; return volatility …

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management … the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns.In turn, this so …-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure …

data ; long memory ; volatility persistence ; structural breaks …

the Efficient Method of Moments implemented to estimatestochastic volatility models this will surely be the case … method of momentstechnique for a broad range of univariate stochastic volatility models. As a side effect of the … volatility models. It describes the program. Some examples are given from other workof the author. Technicalities are given in …

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …