volatility and persistence using the Hurst exponent. We determined the peaks, downturns and duration of the money laundering …

In this study, we predict the daily volatility of the S&P CNX NIFTY market index of India using the basic … jump and continuous component from the realized volatility. We also tried to investigate whether dividing volatility into … simple and threshold jumps and continuous variation yields a substantial improvement in volatility forecasting or not. The …

In this work we focus on the application of wavelet-based methods in volatility modeling. We introduce a new, wavelet …-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH-family model capturing long-memory and asymmetry in volatility …

Conditional Heteroscedasticity (FIEGARCH) model, often used for modeling long memory in volatility of financial assets. The newly …

prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to … simple daily ranges and explore the use of these more efficient volatility measures as predictors of daily ranges. The array … forecasts are produced by a realized range based HAR model with a GARCH volatility-of-volatility component. …

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. …

We propose a methodology to include night volatility estimates in the day volatility modeling problem with high … the natural relationship between the realized measure and the conditional variance. This improves volatility modeling by … leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that …