The presence of long memory in Realized Volatility (RV) is a widespread stylized fact. The origins of long memory in RV …

This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an … extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models … Stochastic Volatility (SV), along with Mixed Data Sampling (MIDAS) regressions, which enable us to incorporate the impacts of …

Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good … forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this …, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily …

forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting … ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility … variation, we formally develop the links between the conditional covariancematrix and the concept of realized volatility. Next …

volatilities, we first discuss the evolution of the volatility of EU ETS allowances' returns from 2008 to 2021. Second, we study … the degree of co-movement and interdependence between the EU ETS returns' volatility and those of 37 large companies in … industries subject to the System; to this end, we employWavelet Coherence and Volatility Spillovers Analyses. Despite spotting …