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

volatility índices (namely the originally created RTSVX and the new RVI that has replaced it), using daily data over the period …

-varying volatility of the data generating process can have rather adverse effects when inferring about its persistence; e.g. unit root … conditional heteroskedasticity). The paper explores the influence of time-varying volatility on fractionally integrated processes …. Concretely, we discuss how to model long memory in the presence of time-varying volatility, and analyze the effects of such …

1.71% per annum. Consistent with theory, we find that the volatility of stocks with longer memory is more predictable …This paper examines long memory volatility in the cross-section of stock returns. We show that long memory volatility … capitalization, book-to-market ratio, prior performance and price jumps. Long memory volatility is negatively priced in the cross …

This paper investigates persistence in high-frequency, intraday data (and also daily and monthly ones) in the case of … exponent as a measure of persistence. The results indicate that persistence is sensitive to the data frequency. More … addition, persistence varies over time. These findings imply that the Efficient Market Hypothesis (EMH) only holds in the case …

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized …. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions … from returns to volatility and co-volatility. …

The three most popular univariate conditional volatility models are the generalized autoregressive conditional … models are important in estimating and forecasting volatility, as well as capturing asymmetry, which is the different effects … on conditional volatility of positive and negative effects of equal magnitude, and leverage, which is the negative …

The three most popular univariate conditional volatility models are the generalized autoregressive conditional … models are important in estimating and forecasting volatility, as well as in capturing asymmetry, which is the different … effects on conditional volatility of positive and negative effects of equal magnitude, and purportedly in capturing leverage …

volatility for estimating conditional variances and covariances; (2) alternative currencies; and (3) alternative maturities of … Chang et al. [17], we estimate four multivariate volatility models (namely CCC, VARMA-AGARCH, DCC and BEKK), and calculate …

In the class of univariate conditional volatility models, the three most popular are the generalized autoregressive … effects on conditional volatility of positive and negative effects of equal magnitude, and possibly also leverage, which is … the negative correlation between returns shocks and subsequent shocks to volatility (see Black 1979). McAleer (2014 …