Showing 1 - 10 of 201
In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate …
Persistent link: https://www.econbiz.de/10005556334
In this paper we study two statistical approaches to load forecasting. Both of them model electricity load as a sum of …
Persistent link: https://www.econbiz.de/10005119116
Implications of nonlinearity, nonstationarity and misspecification are considered from a forecasting perspective. My …
Persistent link: https://www.econbiz.de/10005408003
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 …
Persistent link: https://www.econbiz.de/10005556398
Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. These features must be taken into account to produce accurate forecasts of Value-at-Risk (VaR). We provide a comprehensive look at the problem by considering...
Persistent link: https://www.econbiz.de/10011755300
This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...
Persistent link: https://www.econbiz.de/10011755339
We consider the problem of testing for a structural break in the spatial lag parameter in a panel model (spatial autoregressive). We propose a likelihood ratio test of the null hypothesis of no break against the alternative hypothesis of a single break. The limiting distribution of the test is...
Persistent link: https://www.econbiz.de/10011755365
using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …
Persistent link: https://www.econbiz.de/10011123002
Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance targeting, which reduces the degree of parameterization and facilitates estimation. We compare the two approaches and investigate, via simulations, how non-normality features of the...
Persistent link: https://www.econbiz.de/10011755296
We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both … informative than "good" jump risk in forecasting future volatility. The volatility forecasting model proposed is able to capture …
Persistent link: https://www.econbiz.de/10011755317