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 … implications of these findings, and 'time-span robust' tests indicate that the prevalence of jumps is not as universal as might be …

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …

We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both … return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we … estimate the size of positive and negative jumps and propose a methodology to estimate the size of jumps in the quadratic …

Implications of nonlinearity, nonstationarity and misspecification are considered from a forecasting perspective. My …

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a … models. In order to explain this poor performance, we use a forecasting error decomposition. We identify four components and …

noise is considered. A general stochastic volatility framework with jumps for the underlying asset dynamics is defined … parameter and average jumps size reveals that the characteristics of the dataset are crucial to determine which is the proper …