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Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series

Koopman, Siem Jan; Bos, Charles S. - Tinbergen Instituut - 2002

concerned with themodelling and forecasting of two U.S. macroeconomic time series:inflation and industrial production. …

Persistent link: https://www.econbiz.de/10011255780

Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks

Bos, C.S.; Koopman, S.J.; Ooms, M. - Tinbergen Instituut - 2007

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the … conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the … efficient estimates of the parameters using a monthly dataset of core inflation for which we consider different subsamples of …

Persistent link: https://www.econbiz.de/10011256451

Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation

Gatarek, Lukasz; Hoogerheide, Lennart; Hooning, Koen; … - Tinbergen Instituut - 2013

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

Persistent link: https://www.econbiz.de/10011255481

Modelling Issues in Kernel Ridge Regression

Exterkate, Peter - Tinbergen Instituut - 2011

Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels,...

Persistent link: https://www.econbiz.de/10011255762

Which Brands gain Share from which Brands? Inference from Store-Level Scanner Data

Oest, Rutger van; Franses, Philip Hans - Tinbergen Instituut - 2003

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specificperiod of time. It is for this purpose that we...

Persistent link: https://www.econbiz.de/10011256434

Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production

Bos, Charles S.; Koopman, Siem Jan - Tinbergen Instituut - 2010

Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...

Persistent link: https://www.econbiz.de/10011256745

Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting

Lucas, André; Zhang, Xin - Tinbergen Instituut - 2014

We present a simple new methodology to allow for time variation in volatilities using a recursive updating scheme similar to the familiar RiskMetrics approach. We update parameters using the score of the forecasting distribution rather than squared lagged observations. This allows the parameter...

Persistent link: https://www.econbiz.de/10011257169

Sparse and Robust Factor Modelling

Croux, Christophe; Exterkate, Peter - Tinbergen Instituut - 2011

Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively...

Persistent link: https://www.econbiz.de/10011257444

An Alternative Bayesian Approach to Structural Breaks in Time Series Models

Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick J.C. van - Tinbergen Instituut - 2011

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

Persistent link: https://www.econbiz.de/10011257521

A General Framework for Observation Driven Time-Varying Parameter Models

Creal, Drew; Koopman, Siem Jan; Lucas, André - Tinbergen Instituut - 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/10011255643

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