metal price series is investigated, as well as time-varying volatility. The results demonstrate that allowing for jumps and … time-varying volatility provides statistically important improvements in the modelling or prices, relative to GBM. These …

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

standard information criteria, volatility persistence and the log likelihood statistic, showed that results improved with … of volatility breaks reduces the level of persistence in most of the models. The study recommends the incorporation of …This paper examines exchange-rate volatility with GARCH models using monthly exchange-rate return series from 1985:1 to …

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 …-section. Buying stocks with shorter memory and selling stocks with longer memory in volatility generates significant excess returns of …

issue is particularly important for persistent time series, we focus on volatility modelling, specifically modelling of … realized volatility. We suggest a simple way of adjusting volatility models, which we illustrate on an AR(1) model and the HAR … more than 15 years, and we find that our extension improves the volatility models—both in sample and out of sample. For HAR …

electricity price volatility. We use emergency outages of coal generators as an exogenous source of variation in the power …

Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could … affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility … freedom. Moreover, we study volatility spillovers among a large number of assets. To this end, we use penalized estimation of …

This paper investigates volatility forecasting for crude oil and natural gas. The main objective of our research is to … from a related energy commodity. We find that on average, information from related commodity does not improve volatility …, superior volatility forecasts are produced by combining forecasts from various models. As a result, information from the …

We analyse the dynamic behavior of conditional volatility in commodity markets using a novel, manually collected … dataset of daily price ranges over a time span of more than 140 years, which allows more precise daily volatility estimates … not adequate to capture the very distinct long-run and short-run dynamic volatility components. While the long memory …