Similar Search Results

Forecasting in a changing world : from the great recession to the COVID-19 pandemic

Artemova, Mariia; Blasques, Francisco; Koopman, Siem Jan; … - 2021

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified …-validation procedure. In a set of Monte Carlo experiments we reveal that the estimation method can significantly improve the forecasting …

Persistent link: https://www.econbiz.de/10012416341

An hourly periodic state space model for modelling French national electricity load

Dordonnat, V.; Koopman, Siem Jan; Ooms, Marius; … - 2008

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...

Persistent link: https://www.econbiz.de/10011373810

Analyzing the term structure of interest rates using the dynamic Nelson-Siegel model with time-varying parameters

Koopman, Siem Jan; Mallee, Max I. P.; Wel, Michel van der - 2007

In this discussion paper we introduce time-varying parameters in the dynamic Nelson–Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson–Siegel model has been recently reformulated as a dynamic factor model with vector...

Persistent link: https://www.econbiz.de/10011373825

Periodic unobserved cycles in seasonal time series with an application to US unemployment

Koopman, Siem Jan; Ooms, Marius; Hindrayanto, Irma - 2006

This paper discusses identification, specification, estimation and forecasting for a general class of periodic … formulations are introduced for exact maximum likelihood estimation, component estimation and forecasting. Identification issues …, the model is applied to postwar monthly US unemployment series and we discover a significantly periodic cycle. Furthermore …

Persistent link: https://www.econbiz.de/10011350384

Periodic heteroskedastic RegARFIMA models for daily electricity spot prices

Carnero, M. Angeles; Koopman, Siem Jan; Ooms, Marius - 2003

Although the main interest in the modelling of electricity prices is often on volatility aspects, we argue that stochastic heteroskedastic behaviour in prices can only be modelled correctly when the conditional mean of the time series is properly modelled. In this paper we consider different...

Persistent link: https://www.econbiz.de/10011334362

Generalized autoregressive method of moments

Creal, Drew; Koopman, Siem Jan; Lucas, André; … - 2015

We introduce a new estimation framework which extends the Generalized Method of Moments (GMM) to settings where a … approach is completely observation driven, rendering estimation and inference straightforward. It provides a unified framework …

Persistent link: https://www.econbiz.de/10011431471

A general framework for observation driven time-varying parameter models

Creal, Drew; Koopman, Siem Jan; Lucas, André - 2008

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

Persistent link: https://www.econbiz.de/10011377309

Observation-driven hierarchical density models for missing data imputation

Khanna, Yonas; Lucas, André - 2025

We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel data. The model exploits both serial and cross-sectional information in the data and can easily cope with time-variation in conditional means and variances, as well as with either...

Persistent link: https://www.econbiz.de/10015373862

Periodic seasonal Reg-ARFIMA-GARCH models for daily electricity spot prices

Koopman, Siem Jan; Ooms, Marius; Carnero, M. Angeles - 2005

Novel periodic extensions of dynamic long memory regression models with autoregressive conditional heteroskedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specifications are estimated simultaneously by the method...

Persistent link: https://www.econbiz.de/10011346471

Optimal formulations for nonlinear autoregressive processes

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

parameter estimation. The performance of our model in extracting the time-varying or the nonlinear dependence for finite samples … our model for a weekly time series of unemployment insurance claims. …

Persistent link: https://www.econbiz.de/10010390075