Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the … assumptions of jumps in prices and leverage effects for volatility. Findings suggest that daily-data models are preferred to HF …

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in … the financial econometrics literature. These tests differ from “long time span tests” that detect jumps by examining the … these findings, and “time-span robust” tests indicate that the prevalence of jumps is not as universal as might be expected. …

dependent and independent variables are co-integrated. In this paper, we investigate forecasting performance between first …-of-sample forecasting under the CCAR framework. A simple application for models constructed for banks’ Comprehensive Capital Analysis and …

that forecasts improve significantly if jumps in the log-price process are considered separately from continuous components …