rate returns, can be the product of shifts in variance while other do not. Also, the behavior of the volatility is studied …, showing that the ARFIMA modeling is able to capture long memory, but, depending on the proxy used for the volatility, is not …

Volatility features of the Nordic day ahead power spot market for a 12-year period up till May 2004 are studied. The … daily logarithmic volatility was measured for this period to be about 16%. This level is well above what is observed for … most other well-studied financial markets. Volatility clustering, log-normal distribution, and long-range correlations are …

of RiskMetrics is the artifact of the choice of the risk measure. First, the outstanding performance of volatility … performance in obtaining Value-at-Risk by simply multiplying volatility with a constant factor is mainly due to the choice of the …

.0,b=5. The volatility auto-correlation function (c(τ)) is positive for several iterations. …

This paper tests whether volatility for equity returns for emerging markets possesses long-range dependence … empirical results suggest that there exists long-range dependence in emerging equity returns' volatility and also that it is … class of GARCH processes, which are currently employed to analyze volatility of financial time series, is misspecified. …

We study the unconditional volatility distribution of the Italian futures market, measuring it via Fourier analysis … volatility levels in its final part, because of the dramatic events following 11 September 2001. Our results show that the … standard assumption of lognormal unconditional volatility has to be rejected for such a turbulent sample, since it is unable to …

We study the volatility of the S&P500 stock index from 1984 to 1996 and find that the volatility distribution can be … very well described by a log-normal function. Further, using detrended fluctuation analysis we show that the volatility is …